Podcasts about Clod

Trouver sa place sans suivre les tendances - Entretien avec Clod illustrateurClod est illustrateur depuis plus de vingt ans. Il a collaboré avec de grands titres de presse, des maisons d'édition, des associations, des mutuelles, des marques, etc., mais ce n'est pas son CV qui rend notre échange si précieux, mais la manière dont il aborde notre métier avec philosophie et passion.Dans cet épisode, on parle de parcours non linéaire, de liberté, de détermination, et de ce que ça signifie réellement de construire une carrière d'illustrateur·trice sur le long terme.Clod partage son regard sur l'évolution du métier, les réseaux sociaux, la fameuse quête du style unique, la pression de la visibilité, et le plaisir qu'on peut retrouver quand on accepte de lâcher prise.

Thatch is joined by Clod 9 and Sharkfinnagen to discuss how the Pokemon Franchise Might be forever changed in the new era of Pokemon Champions + Pokemon HOME.Mailbag Question: What do you think the next Pokemon Games will be like? What Pokemon do you think would order a hamburger at a fast food restaurant? puclpodcast@gmail.comTimestamps:Intro: 0:01:09News: 0:16:43Quiz: 0:31:03Topic: 0:49:23PokeOpinion: 1:26:04Mailbag: 1:35:46Use Code PUCLPOD5 at trollandtoad.com for 5% off and support the show!Check us out on Discord!https://pucldiscord.comTwitter: https://twitter.com/puclpodcastFacebook: https://Facebook.com/puclpodcastBlusky: https://bsky.app/profile/puclpodcast.bsky.socialTwitch: https://twitch.tv/thepuclpodcastSupport us at https://Patreon! Patreon.com/puclpodcast#pokemonpodcast #pokecast #pokemontalk #pokemonxy #pokemonza #pokemontcg #pokemongo #pokemontalk #pokemon #nintendo #nintendoswitch #nintendoswitchlite #nintendoswitch2 #pokemonchampions Hosted on Acast. See acast.com/privacy for more information.

Thatch is joined by Clod 9 and R. Sigma to talk about the Best and Worst Pokemon From Generation 8!Mailbag Question: What are your top and bottom Gen 8 pokemon? puclpodcast@gmail.comTimestamps:Intro: 0:01:06News: 0:12:03Quiz: 0:25:17Topic: 0:37:47PokeOpinion: 1:10:35Mailbag: 1:18:32Use Code PUCLPOD5 at trollandtoad.com for 5% off and support the show!Check us out on Discord!https://pucldiscord.comTwitter: https://twitter.com/puclpodcastFacebook: https://Facebook.com/puclpodcastBlusky: https://bsky.app/profile/puclpodcast.bsky.socialTwitch: https://twitch.tv/thepuclpodcast Support us at https://Patreon! Patreon.com/puclpodcast#pokemonpodcast #pokecast #pokemontalk #pokemonxy #pokemonza #pokemontcg #pokemongo #pokemontalk #pokemon #nintendo #nintendoswitch #nintendoswitchlite #nintendoswitch2 #pokemonchampions Hosted on Acast. See acast.com/privacy for more information.

Clod has launched an investigation into her missing 1966 autograph book, and she's landed on Barney and Betty Hill. This is a true story which really does feature the Hills and other characters. Hilary has questions (Who the heck was Art Linkletter?) and Clod takes you behind the scenes of her investigative work.  This is a fun one!More Secrets:⁠⁠ www.mymothersdiaries.com⁠⁠Shop: ⁠www.mymothersdiaries.com/mymotherscloset⁠Listen: https://www.mymothersdiaries.com/mymotherspodcastFollow Us!Instagram: ⁠https://www.instagram.com/mymothersdiaries/TikTok: ⁠https://www.tiktok.com/@mymothersdiariesFacebook: ⁠https://www.facebook.com/mymothersdiariesThank you to Dead Gowns for our intro song!Listen to Kid 1 by Dead Gowns: https://www.deadgowns.com/

Learn more at TheCityLife.org

Mae Dylan Griffiths yn chwarae gêm beryglus. Nid yn unig ydi o'n penderfynu beirniadu Malcolm Allen am safon ei broffwydo, ond mae o hefyd yn mynd mor bell â dweud wrtho am ymddiheuro. Eithaf hawdd proffwydo pa fath o ymateb cafodd o i hyn...Mae Owain Tudur Jones yn ei chael hi hefyd, ac mae hwnnw yn ychwanegu cefnogwyr Aberystwyth arall i'w restr (hirfaith erbyn hyn) o bethau sy'n mynd "ar ei nyrfs". Tensiwn diwedd tymor bois bach, peidiwch â sôn!

In this enraging, we mean, engaging episode, Clod reads ridiculous tales of her teen-aged angst, while Hilary adds her usual comical insight (and one big epiphany). On top of this foolishness, while Clod is reading her diary, she randomly starts uttering the names of the punctuation marks.  Clod and Hilary still can't stop laughing about that (EXCLAMATION POINT)  More Secrets:⁠⁠ www.mymothersdiaries.com⁠⁠ Shop: ⁠www.mymothersdiaries.com/mymotherscloset⁠ Listen: https://www.mymothersdiaries.com/mymotherspodcast Follow Us! Instagram: ⁠https://www.instagram.com/mymothersdiaries/ TikTok: ⁠https://www.tiktok.com/@mymothersdiaries Facebook: ⁠https://www.facebook.com/mymothersdiaries Thank you to Dead Gowns for our intro song! Listen to Kid 1 by Dead Gowns: https://www.deadgowns.com/

Eine weitere LUNGDON Folge, diesmal mit Oliver und Peter. Wir besprechen Kapitel 22

Tune in to this episode to find out why Hilary says “In Retrospect I Acted Like an Idiot” should be the title  of Clod's memoir, with “How To Lose A Guy in 7 Weeks” as a close contender. You'll also discover how, as events unfolded live, Clod used to tap out what was happening minute by minute on her electric typewriter. More Secrets:⁠⁠ www.mymothersdiaries.com⁠⁠ Shop: ⁠www.mymothersdiaries.com/mymotherscloset⁠ Listen: https://www.mymothersdiaries.com/mymotherspodcast Follow Us! Instagram: ⁠https://www.instagram.com/mymothersdiaries/ TikTok: ⁠https://www.tiktok.com/@mymothersdiaries Facebook: ⁠https://www.facebook.com/mymothersdiaries Thank you to Dead Gowns for our intro song! Listen to Kid 1 by Dead Gowns: https://www.deadgowns.com/

Happy holidays! We'll be sharing snippets from Latent Space LIVE! through the break bringing you the best of 2024! We want to express our deepest appreciation to event sponsors AWS, Daylight Computer, Thoth.ai, StrongCompute, Notable Capital, and most of all all our LS supporters who helped fund the gorgeous venue and A/V production!For NeurIPS last year we did our standard conference podcast coverage interviewing selected papers (that we have now also done for ICLR and ICML), however we felt that we could be doing more to help AI Engineers 1) get more industry-relevant content, and 2) recap 2024 year in review from experts. As a result, we organized the first Latent Space LIVE!, our first in person miniconference, at NeurIPS 2024 in Vancouver.Our next keynote covers The State of LLM Agents, with the triumphant return of Professor Graham Neubig's return to the pod (his ICLR episode here!). OpenDevin is now a startup known as AllHands! The renamed OpenHands has done extremely well this year, as they end the year sitting comfortably at number 1 on the hardest SWE-Bench Full leaderboard at 29%, though on the smaller SWE-Bench Verified, they are at 53%, behind Amazon Q, devlo, and OpenAI's self reported o3 results at 71.7%.Many are saying that 2025 is going to be the year of agents, with OpenAI, DeepMind and Anthropic setting their sights on consumer and coding agents, vision based computer-using agents and multi agent systems. There has been so much progress on the practical reliability and applications of agents in all domains, from the huge launch of Cognition AI's Devin this year, to the sleeper hit of Cursor Composer and Codeium's Windsurf Cascade in the IDE arena, to the explosive revenue growth of Stackblitz's Bolt, Lovable, and Vercel's v0, and the unicorn rounds and high profile movements of customer support agents like Sierra (now worth $4 billion) and search agents like Perplexity (now worth $9 billion). We wanted to take a little step back to understand the most notable papers of the year in Agents, and Graham indulged with his list of 8 perennial problems in building agents in 2024.Must-Read Papers for the 8 Problems of Agents* The agent-computer interface: CodeAct: Executable Code Actions Elicit Better LLM Agents. Minimial viable tools: Execution Sandbox, File Editor, Web Browsing* The human-agent interface: Chat UI, GitHub Plugin, Remote runtime, …?* Choosing an LLM: See Evaluation of LLMs as Coding Agents on SWE-Bench at 30x - must understand instructions, tools, code, environment, error recovery* Planning: Single Agent Systems vs Multi Agent (CoAct: A Global-Local Hierarchy for Autonomous Agent Collaboration) - Explicit vs Implicit, Curated vs Generated* Reusable common workflows: SteP: Stacked LLM Policies for Web Actions and Agent Workflow Memory - Manual prompting vs Learning from Experience* Exploration: Agentless: Demystifying LLM-based Software Engineering Agents and BAGEL: Bootstrapping Agents by Guiding Exploration with Language* Search: Tree Search for Language Model Agents - explore paths and rewind* Evaluation: Fast Sanity Checks (miniWoB and Aider) and Highly Realistic (WebArena, SWE-Bench) and SWE-Gym: An Open Environment for Training Software Engineering Agents & VerifiersFull Talk on YouTubePlease like and subscribe!Timestamps* 00:00 Welcome to Latent Space Live at NeurIPS 2024* 00:29 State of LLM Agents in 2024* 02:20 Professor Graham Newbig's Insights on Agents* 03:57 Live Demo: Coding Agents in Action* 08:20 Designing Effective Agents* 14:13 Choosing the Right Language Model for Agents* 16:24 Planning and Workflow for Agents* 22:21 Evaluation and Future Predictions for Agents* 25:31 Future of Agent Development* 25:56 Human-Agent Interaction Challenges* 26:48 Expanding Agent Use Beyond Programming* 27:25 Redesigning Systems for Agent Efficiency* 28:03 Accelerating Progress with Agent Technology* 28:28 Call to Action for Open Source Contributions* 30:36 Q&A: Agent Performance and Benchmarks* 33:23 Q&A: Web Agents and Interaction Methods* 37:16 Q&A: Agent Architectures and Improvements* 43:09 Q&A: Self-Improving Agents and Authentication* 47:31 Live Demonstration and Closing RemarksTranscript[00:00:29] State of LLM Agents in 2024[00:00:29] Speaker 9: Our next keynote covers the state of LLM agents. With the triumphant return of Professor Graham Newbig of CMU and OpenDevon, now a startup known as AllHands. The renamed OpenHands has done extremely well this year, as they end the year sitting comfortably at number one on the hardest SWE Benchful leaderboard at 29%.[00:00:53] Speaker 9: Though, on the smaller SWE bench verified, they are at 53 percent behind Amazon Q [00:01:00] Devlo and OpenAI's self reported O3 results at 71. 7%. Many are saying that 2025 is going to be the year of agents, with OpenAI, DeepMind, and Anthropic setting their sights on consumer and coding agents. Vision based computer using agents and multi agent systems.[00:01:22] Speaker 9: There has been so much progress on the practical reliability and applications of agents in all domains, from the huge launch of Cognition AI's Devon this year, to the sleeper hit of Cursor Composer and recent guest Codium's Windsurf Cascade in the IDE arena. To the explosive revenue growth of recent guests StackBlitz's Bolt, Lovable, and Vercel's vZero.[00:01:44] Speaker 9: And the unicorn rounds and high profile movements of customer support agents like Sierra, now worth 4 billion, and search agents like Perplexity, now worth 9 billion. We wanted to take a little step back to understand the most notable papers of the year in [00:02:00] agents, and Graham indulged with his list of eight perennial problems in building agents.[00:02:06] Speaker 9: As always, don't forget to check our show notes for all the selected best papers of 2024, and for the YouTube link to their talk. Graham's slides were especially popular online, and we are honoured to have him. Watch out and take care![00:02:20] Professor Graham Newbig's Insights on Agents[00:02:20] Speaker: Okay hi everyone. So I was given the task of talking about agents in 2024, and this is An impossible task because there are so many agents, so many agents in 2024. So this is going to be strongly covered by like my personal experience and what I think is interesting and important, but I think it's an important topic.[00:02:41] Speaker: So let's go ahead. So the first thing I'd like to think about is let's say I gave you you know, a highly competent human, some tools. Let's say I gave you a web browser and a terminal or a file system. And the ability to [00:03:00] edit text or code. What could you do with that? Everything. Yeah.[00:03:07] Speaker: Probably a lot of things. This is like 99 percent of my, you know, daily daily life, I guess. When I'm, when I'm working. So, I think this is a pretty powerful tool set, and I am trying to do, and what I think some other people are trying to do, is come up with agents that are able to, you know, manipulate these things.[00:03:26] Speaker: Web browsing, coding, running code in successful ways. So there was a little bit about my profile. I'm a professor at CMU, chief scientist at All Hands AI, building open source coding agents. I'm maintainer of OpenHands, which is an open source coding agent framework. And I'm also a software developer and I, I like doing lots of coding and, and, you know, shipping new features and stuff like this.[00:03:51] Speaker: So building agents that help me to do this, you know, is kind of an interesting thing, very close to me.[00:03:57] Live Demo: Coding Agents in Action[00:03:57] Speaker: So the first thing I'd like to do is I'd like to try [00:04:00] some things that I haven't actually tried before. If anybody has, you know, tried to give a live demo, you know, this is, you know very, very scary whenever you do it and it might not work.[00:04:09] Speaker: So it might not work this time either. But I want to show you like three things that I typically do with coding agents in my everyday work. I use coding agents maybe five to 10 times a day to help me solve my own problems. And so this is a first one. This is a data science task. Which says I want to create scatter plots that show the increase of the SWE bench score over time.[00:04:34] Speaker: And so I, I wrote a kind of concrete prompt about this. Agents work better with like somewhat concrete prompts. And I'm gonna throw this into open hands and let it work. And I'll, I'll go back to that in a second. Another thing that I do is I create new software. And I, I've been using a [00:05:00] service a particular service.[00:05:01] Speaker: I won't name it for sending emails and I'm not very happy with it. So I want to switch over to this new service called resend. com, which makes it easier to send emails. And so I'm going to ask it to read the docs for the resend. com API and come up with a script that allows me to send emails. The input to the script should be a CSV file and the subject and body should be provided in Jinja2 templates.[00:05:24] Speaker: So I'll start another agent and and try to get it to do that for me.[00:05:35] Speaker: And let's go with the last one. The last one I do is. This is improving existing software and in order, you know, once you write software, you usually don't throw it away. You go in and, like, actually improve it iteratively. This software that I have is something I created without writing any code.[00:05:52] Speaker: It's basically software to monitor how much our our agents are contributing to the OpenHance repository. [00:06:00] And on the, let me make that a little bit bigger, on the left side, I have the number of issues where it like sent a pull request. I have the number of issues where it like sent a pull request, whether it was merged in purple, closed in red, or is still open in green. And so these are like, you know, it's helping us monitor, but one thing it doesn't tell me is the total number. And I kind of want that feature added to this software.[00:06:33] Speaker: So I'm going to try to add that too. So. I'll take this, I'll take this prompt,[00:06:46] Speaker: and here I want to open up specifically that GitHub repo. So I'll open up that repo and paste in the prompt asking it. I asked it to make a pie chart for each of these and give me the total over the entire time period that I'm [00:07:00] monitoring. So we'll do that. And so now I have let's see, I have some agents.[00:07:05] Speaker: Oh, this one already finished. Let's see. So this one already finished. You can see it finished analyzing the Swebench repository. It wrote a demonstration of, yeah, I'm trying to do that now, actually.[00:07:30] Speaker: It wrote a demonstration of how much each of the systems have improved over time. And I asked it to label the top three for each of the data sets. And so it labeled OpenHands as being the best one for SWE Bench Normal. For SWE Bench Verified, it has like the Amazon QAgent and OpenHands. For the SWE Bench Lite, it has three here over three over here.[00:07:53] Speaker: So you can see like. That's pretty useful, right? If you're a researcher, you do data analysis all the time. I did it while I was talking to all [00:08:00] of you and making a presentation. So that's, that's pretty nice. I, I doubt the other two are finished yet. That would be impressive if the, yeah. So I think they're still working.[00:08:09] Speaker: So maybe we'll get back to them at the end of the presentation. But so these are the kinds of the, these are the kinds of things that I do every day with coding agents now. And it's or software development agents. It's pretty impressive.[00:08:20] Designing Effective Agents[00:08:20] Speaker: The next thing I'd like to talk about a little bit is things I worry about when designing agents.[00:08:24] Speaker: So we're designing agents to, you know, do a very difficult task of like navigating websites writing code, other things like this. And within 2024, there's been like a huge improvement in the methodology that we use to do this. But there's a bunch of things we think about. There's a bunch of interesting papers, and I'd like to introduce a few of them.[00:08:46] Speaker: So the first thing I worry about is the agent computer interface. Like, how do we get an agent to interact with computers? And, How do we provide agents with the tools to do the job? And [00:09:00] within OpenHands we are doing the thing on the right, but there's also a lot of agents that do the thing on the left.[00:09:05] Speaker: So the thing on the left is you give like agents kind of granular tools. You give them tools like or let's say your instruction is I want to determine the most cost effective country to purchase the smartphone model, Kodak one the countries to consider are the USA, Japan, Germany, and India. And you have a bunch of available APIs.[00:09:26] Speaker: And. So what you do for some agents is you provide them all of these tools APIs as tools that they can call. And so in this particular case in order to solve this problem, you'd have to make about like 30 tool calls, right? You'd have to call lookup rates for Germany, you'd have to look it up for the US, Japan, and India.[00:09:44] Speaker: That's four tool goals. And then you go through and do all of these things separately. And the method that we adopt in OpenHands instead is we provide these tools, but we provide them by just giving a coding agent, the ability to call [00:10:00] arbitrary Python code. And. In the arbitrary Python code, it can call these tools.[00:10:05] Speaker: We expose these tools as APIs that the model can call. And what that allows us to do is instead of writing 20 tool calls, making 20 LLM calls, you write a program that runs all of these all at once, and it gets the result. And of course it can execute that program. It can, you know, make a mistake. It can get errors back and fix things.[00:10:23] Speaker: But that makes our job a lot easier. And this has been really like instrumental to our success, I think. Another part of this is what tools does the agent need? And I, I think this depends on your use case, we're kind of extreme and we're only giving the agent five tools or maybe six tools.[00:10:40] Speaker: And what, what are they? The first one is program execution. So it can execute bash programs, and it can execute Jupyter notebooks. It can execute cells in Jupyter notebooks. So that, those are two tools. Another one is a file editing tool. And the file editing tool allows you to browse parts of files.[00:11:00][00:11:00] Speaker: And kind of read them, overwrite them, other stuff like this. And then we have another global search and replace tool. So it's actually two tools for file editing. And then a final one is web browsing, web browsing. I'm kind of cheating when I call it only one tool. You actually have like scroll and text input and click and other stuff like that.[00:11:18] Speaker: But these are basically the only things we allow the agent to do. What, then the question is, like, what if we wanted to allow it to do something else? And the answer is, well, you know, human programmers already have a bunch of things that they use. They have the requests PyPy library, they have the PDF to text PyPy library, they have, like, all these other libraries in the Python ecosystem that they could use.[00:11:41] Speaker: And so if we provide a coding agent with all these libraries, it can do things like data visualization and other stuff that I just showed you. So it can also get clone repositories and, and other things like this. The agents are super good at using the GitHub API also. So they can do, you know, things on GitHub, like finding all of the, you know, [00:12:00] comments on your issues or checking GitHub actions and stuff.[00:12:02] Speaker: The second thing I think about is the human agent interface. So this is like how do we get humans to interact with agents? Bye. I already showed you one variety of our human agent interface. It's basically a chat window where you can browse through the agent's results and things like this. This is very, very difficult.[00:12:18] Speaker: I, I don't think anybody has a good answer to this, and I don't think we have a good answer to this, but the, the guiding principles that I'm trying to follow are we want to present enough info to the user. So we want to present them with, you know, what the agent is doing in the form of a kind of.[00:12:36] Speaker: English descriptions. So you can see here you can see here every time it takes an action, it says like, I will help you create a script for sending emails. When it runs a bash command. Sorry, that's a little small. When it runs a bash command, it will say ran a bash command. It won't actually show you the whole bash command or the whole Jupyter notebook because it can be really large, but you can open it up and see if you [00:13:00] want to, by clicking on this.[00:13:01] Speaker: So like if you want to explore more, you can click over to the Jupyter notebook and see what's displayed in the Jupyter notebook. And you get like lots and lots of information. So that's one thing.[00:13:16] Speaker: Another thing is go where the user is. So like if the user's already interacting in a particular setting then I'd like to, you know, integrate into that setting, but only to a point. So at OpenHands, we have a chat UI for interaction. We have a GitHub plugin for tagging and resolving issues. So basically what you do is you Do at open hands agent and the open hands agent will like see that comment and be able to go in and fix things.[00:13:42] Speaker: So if you say at open hands agent tests are failing on this PR, please fix the tests. It will go in and fix the test for you and stuff like this. Another thing we have is a remote runtime for launching headless jobs. So if you want to launch like a fleet of agents to solve, you know five different problems at once, you can also do [00:14:00] that through an API.[00:14:00] Speaker: So we have we have these interfaces and this probably depends on the use case. So like, depending if you're a coding agent, you want to do things one way. If you're a like insurance auditing agent, you'll want to do things other ways, obviously.[00:14:13] Choosing the Right Language Model for Agents[00:14:13] Speaker: Another thing I think about a lot is choosing a language model.[00:14:16] Speaker: And for agentic LMs we have to have a bunch of things work really well. The first thing is really, really good instruction following ability. And if you have really good instruction following ability, it opens up like a ton of possible applications for you. Tool use and coding ability. So if you provide tools, it needs to be able to use them well.[00:14:38] Speaker: Environment understanding. So it needs, like, if you're building a web agent, it needs to be able to understand web pages either through vision or through text. And error awareness and recovery ability. So, if it makes a mistake, it needs to be able to, you know, figure out why it made a mistake, come up with alternative strategies, and other things like this.[00:14:58] Speaker: [00:15:00] Under the hood, in all of the demos that I did now Cloud, we're using Cloud. Cloud has all of these abilities very good, not perfect, but very good. Most others don't have these abilities quite as much. So like GPT 4. 0 doesn't have very good error recovery ability. And so because of this, it will go into loops and do the same thing over and over and over again.[00:15:22] Speaker: Whereas Claude does not do this. Claude, if you, if you use the agents enough, you get used to their kind of like personality. And Claude says, Hmm, let me try a different approach a lot. So, you know, obviously it's been trained in some way to, you know, elicit this ability. We did an evaluation. This is old.[00:15:40] Speaker: And we need to update this basically, but we evaluated CLOD, mini LLAMA 405B, DeepSeq 2. 5 on being a good code agent within our framework. And CLOD was kind of head and shoulders above the rest. GPT 40 was kind of okay. The best open source model was LLAMA [00:16:00] 3. 1 405B. This needs to be updated because this is like a few months old by now and, you know, things are moving really, really fast.[00:16:05] Speaker: But I still am under the impression that Claude is the best. The other closed models are, you know, not quite as good. And then the open models are a little bit behind that. Grok, I, we haven't tried Grok at all, actually. So, it's a good question. If you want to try it I'd be happy to help.[00:16:24] Speaker: Cool.[00:16:24] Planning and Workflow for Agents[00:16:24] Speaker: Another thing is planning. And so there's a few considerations for planning. The first one is whether you have a curated plan or you have it generated on the fly. And so for solving GitHub issues, you can kind of have an overall plan. Like the plan is first reproduce. If there's an issue, first write tests to reproduce the issue or to demonstrate the issue.[00:16:50] Speaker: After that, run the tests and make sure they fail. Then go in and fix the tests. Run the tests again to make sure they pass and then you're done. So that's like a pretty good workflow [00:17:00] for like solving coding issues. And you could curate that ahead of time. Another option is to let the language model basically generate its own plan.[00:17:10] Speaker: And both of these are perfectly valid. Another one is explicit structure versus implicit structure. So let's say you generate a plan. If you have explicit structure, you could like write a multi agent system, and the multi agent system would have your reproducer agent, and then it would have your your bug your test writer agent, and your bug fixer agent, and lots of different agents, and you would explicitly write this all out in code, and then then use it that way.[00:17:38] Speaker: On the other hand, you could just provide a prompt that says, please do all of these things in order. So in OpenHands, we do very light planning. We have a single prompt. We don't have any multi agent systems. But we do provide, like, instructions about, like, what to do first, what to do next, and other things like this.[00:17:56] Speaker: I'm not against doing it the other way. But I laid [00:18:00] out some kind of justification for this in this blog called Don't Sleep on Single Agent Systems. And the basic idea behind this is if you have a really, really good instruction following agent it will follow the instructions as long as things are working according to your plan.[00:18:14] Speaker: But let's say you need to deviate from your plan, you still have the flexibility to do this. And if you do explicit structure through a multi agent system, it becomes a lot harder to do that. Like, you get stuck when things deviate from your plan. There's also some other examples, and I wanted to introduce a few papers.[00:18:30] Speaker: So one paper I liked recently is this paper called CoAct where you generate plans and then go in and fix them. And so the basic idea is like, if you need to deviate from your plan, you can You know, figure out that your plan was not working and go back and deviate from it.[00:18:49] Speaker: Another thing I think about a lot is specifying common workflows. So we're trying to tackle a software development and I already showed like three use cases where we do [00:19:00] software development and when we. We do software development, we do a ton of different things, but we do them over and over and over again.[00:19:08] Speaker: So just to give an example we fix GitHub actions when GitHub actions are failing. And we do that over and over and over again. That's not the number one thing that software engineers do, but it's a, you know, high up on the list. So how can we get a list of all of, like, the workflows that people are working on?[00:19:26] Speaker: And there's a few research works that people have done in this direction. One example is manual prompting. So there's this nice paper called STEP that got state of the art on the WebArena Web Navigation Benchmark where they came up with a bunch of manual workflows for solving different web navigation tasks.[00:19:43] Speaker: And we also have a paper recently called Agent Workflow Memory where the basic idea behind this is we want to create self improving agents that learn from their past successes. And the way it works is is we have a memory that has an example of lots of the previous [00:20:00] workflows that people have used. And every time the agent finishes a task and it self judges that it did a good job at that task, you take that task, you break it down into individual workflows included in that, and then you put it back in the prompt for the agent to work next time.[00:20:16] Speaker: And this we demonstrated that this leads to a 22. 5 percent increase on WebArena after 40 examples. So that's a pretty, you know, huge increase by kind of self learning and self improvement.[00:20:31] Speaker: Another thing is exploration. Oops. And one thing I think about is like, how can agents learn more about their environment before acting? And I work on coding and web agents, and there's, you know, a few good examples of this in, in both areas. Within coding, I view this as like repository understanding, understanding the code base that you're dealing with.[00:20:55] Speaker: And there's an example of this, or a couple examples of this, one example being AgentList. [00:21:00] Where they basically create a map of the repo and based on the map of the repo, they feed that into the agent so the agent can then navigate the repo and and better know where things are. And for web agents there's an example of a paper called Bagel, and basically what they do is they have the agent just do random tasks on a website, explore the website, better understand the structure of the website, and then after that they they feed that in as part of the product.[00:21:27] Speaker: Part seven is search. Right now in open hands, we just let the agent go on a linear search path. So it's just solving the problem once. We're using a good agent that can kind of like recover from errors and try alternative things when things are not working properly, but still we only have a linear search path.[00:21:45] Speaker: But there's also some nice work in 2024 that is about exploring multiple paths. So one example of this is there's a paper called Tree Search for Language Agents. And they basically expand multiple paths check whether the paths are going well, [00:22:00] and if they aren't going well, you rewind back. And on the web, this is kind of tricky, because, like, how do you rewind when you accidentally ordered something you don't want on Amazon?[00:22:09] Speaker: It's kind of, you know, not, not the easiest thing to do. For code, it's a little bit easier, because you can just revert any changes that you made. But I, I think that's an interesting topic, too.[00:22:21] Evaluation and Future Predictions for Agents[00:22:21] Speaker: And then finally evaluation. So within our development for evaluation, we want to do a number of things. The first one is fast sanity checks.[00:22:30] Speaker: And in order to do this, we want things we can run really fast, really really cheaply. So for web, we have something called mini world of bits, which is basically these trivial kind of web navigation things. We have something called the Adder Code Editing Benchmark, where it's just about editing individual files that we use.[00:22:48] Speaker: But we also want highly realistic evaluation. So for the web, we have something called WebArena that we created at CMU. This is web navigation on real real open source websites. So it's open source [00:23:00] websites that are actually used to serve shops or like bulletin boards or other things like this.[00:23:07] Speaker: And for code, we use Swebench, which I think a lot of people may have heard of. It's basically a coding benchmark that comes from real world pull requests on GitHub. So if you can solve those, you can also probably solve other real world pull requests. I would say we still don't have benchmarks for the fur full versatility of agents.[00:23:25] Speaker: So, for example We don't have benchmarks that test whether agents can code and do web navigation. But we're working on that and hoping to release something in the next week or two. So if that sounds interesting to you, come talk to me and I, I will tell you more about it.[00:23:42] Speaker: Cool. So I don't like making predictions, but I was told that I should be somewhat controversial, I guess, so I will, I will try to do it try to do it anyway, although maybe none of these will be very controversial. Um, the first thing is agent oriented LLMs like large language models for [00:24:00] agents.[00:24:00] Speaker: My, my prediction is every large LM trainer will be focusing on training models as agents. So every large language model will be a better agent model by mid 2025. Competition will increase, prices will go down, smaller models will become competitive as agents. So right now, actually agents are somewhat expensive to run in some cases, but I expect that that won't last six months.[00:24:23] Speaker: I, I bet we'll have much better agent models in six months. Another thing is instruction following ability, specifically in agentic contexts, will increase. And what that means is we'll have to do less manual engineering of agentic workflows and be able to do more by just prompting agents in more complex ways.[00:24:44] Speaker: Cloud is already really good at this. It's not perfect, but it's already really, really good. And I expect the other models will catch up to Cloud pretty soon. Error correction ability will increase, less getting stuck in loops. Again, this is something that Cloud's already pretty good at and I expect the others will, will follow.[00:25:00][00:25:01] Speaker: Agent benchmarks. Agent benchmarks will start saturating.[00:25:05] Speaker: And Swebench I think WebArena is already too easy. It, it is, it's not super easy, but it's already a bit too easy because the tasks we do in there are ones that take like two minutes for a human. So not, not too hard. And kind of historically in 2023 our benchmarks were too easy. So we built harder benchmarks like WebArena and Swebench were both built in 2023.[00:25:31] Future of Agent Development[00:25:31] Speaker: In 2024, our agents were too bad, so we built agents and now we're building better agents. In 2025, our benchmarks will be too easy, so we'll build better benchmarks, I'm, I'm guessing. So, I would expect to see much more challenging agent benchmarks come out, and we're already seeing some of them.[00:25:49] Speaker: In 2026, I don't know. I didn't write AGI, but we'll, we'll, we'll see.[00:25:56] Human-Agent Interaction Challenges[00:25:56] Speaker: Then the human agent computer interface. I think one thing that [00:26:00] we'll want to think about is what do we do at 75 percent success rate at things that we like actually care about? Right now we have 53 percent or 55 percent on Swebench verified, which is real world GitHub PRs.[00:26:16] Speaker: My impression is that the actual. Actual ability of models is maybe closer to 30 to 40%. So 30 to 40 percent of the things that I want an agent to solve on my own repos, it just solves without any human intervention. 80 to 90 percent it can solve without me opening an IDE. But I need to give it feedback.[00:26:36] Speaker: So how do we, how do we make that interaction smooth so that humans can audit? The work of agents that are really, really good, but not perfect is going to be a big challenge.[00:26:48] Expanding Agent Use Beyond Programming[00:26:48] Speaker: How can we expose the power of programming agents to other industries? So like as programmers, I think not all of us are using agents every day in our programming, although we probably will be [00:27:00] in in months or maybe a year.[00:27:02] Speaker: But I, I think it will come very naturally to us as programmers because we know code. We know, you know. Like how to architect software and stuff like that. So I think the question is how do we put this in the hands of like a lawyer or a chemist or somebody else and have them also be able to, you know, interact with it as naturally as we can.[00:27:25] Redesigning Systems for Agent Efficiency[00:27:25] Speaker: Another interesting thing is how can we redesign our existing systems for agents? So we had a paper on API based web agents, and basically what we showed is If you take a web agent and the agent interacts not with a website, but with APIs, the accuracy goes way up just because APIs are way easier to interact with.[00:27:42] Speaker: And in fact, like when I ask the, well, our agent, our agent is able to browse websites, but whenever I want it to interact with GitHub, I tell it do not browse the GitHub website. Use the GitHub API because it's way more successful at doing that. So maybe, you know, every website is going to need to have [00:28:00] an API because we're going to be having agents interact with them.[00:28:03] Accelerating Progress with Agent Technology[00:28:03] Speaker: About progress, I think progress will get faster. It's already fast. A lot of people are already overwhelmed, but I think it will continue. The reason why is agents are building agents. And better agents will build better agents faster. So I expect that you know, if you haven't interacted with a coding agent yet, it's pretty magical, like the stuff that it can do.[00:28:24] Speaker: So yeah.[00:28:28] Call to Action for Open Source Contributions[00:28:28] Speaker: And I have a call to action. I'm honestly, like I've been working on, you know, natural language processing and, and Language models for what, 15 years now. And even for me, it's pretty impressive what like AI agents powered by strong language models can do. On the other hand, I believe that we should really make these powerful tools accessible.[00:28:49] Speaker: And what I mean by this is I don't think like, you know, We, we should have these be opaque or limited to only a set, a certain set of people. I feel like they should be [00:29:00] affordable. They shouldn't be increasing the, you know, difference in the amount of power that people have. If anything, I'd really like them to kind of make it It's possible for people who weren't able to do things before to be able to do them well.[00:29:13] Speaker: Open source is one way to do that. That's why I'm working on open source. There are other ways to do that. You know, make things cheap, make things you know, so you can serve them to people who aren't able to afford them. Easily, like Duolingo is one example where they get all the people in the US to pay them 20 a month so that they can give all the people in South America free, you know, language education, so they can learn English and become, you know like, and become, you know, More attractive on the job market, for instance.[00:29:41] Speaker: And so I think we can all think of ways that we can do that sort of thing. And if that resonates with you, please contribute. Of course, I'd be happy if you contribute to OpenHands and use it. But another way you can do that is just use open source solutions, contribute to them, research with them, and train strong open source [00:30:00] models.[00:30:00] Speaker: So I see, you know, Some people in the room who are already training models. It'd be great if you could train models for coding agents and make them cheap. And yeah yeah, please. I, I was thinking about you among others. So yeah, that's all I have. Thanks.[00:30:20] Speaker 2: Slight, slightly controversial. Tick is probably the nicest way to say hot ticks. Any hot ticks questions, actual hot ticks?[00:30:31] Speaker: Oh, I can also show the other agents that were working, if anybody's interested, but yeah, sorry, go ahead.[00:30:36] Q&A: Agent Performance and Benchmarks[00:30:36] Speaker 3: Yeah, I have a couple of questions. So they're kind of paired, maybe. The first thing is that you said that You're estimating that your your agent is successfully resolving like something like 30 to 40 percent of your issues, but that's like below what you saw in Swebench.[00:30:52] Speaker 3: So I guess I'm wondering where that discrepancy is coming from. And then I guess my other second question, which is maybe broader in scope is that [00:31:00] like, if, if you think of an agent as like a junior developer, and I say, go do something, then I expect maybe tomorrow to get a Slack message being like, Hey, I ran into this issue.[00:31:10] Speaker 3: How can I resolve it? And, and, like you said, your agent is, like, successfully solving, like, 90 percent of issues where you give it direct feedback. So, are you thinking about how to get the agent to reach out to, like, for, for planning when it's, when it's stuck or something like that? Or, like, identify when it runs into a hole like that?[00:31:30] Speaker: Yeah, so great. These are great questions. Oh,[00:31:32] Speaker 3: sorry. The third question, which is a good, so this is the first two. And if so, are you going to add a benchmark for that second question?[00:31:40] Speaker: Okay. Great. Yeah. Great questions. Okay. So the first question was why do I think it's resolving less than 50 percent of the issues on Swebench?[00:31:48] Speaker: So first Swebench is on popular open source repos, and all of these popular open source repos were included in the training data for all of the language models. And so the language [00:32:00] models already know these repos. In some cases, the language models already know the individual issues in Swebench.[00:32:06] Speaker: So basically, like, some of the training data has leaked. And so it, it definitely will overestimate with respect to that. I don't think it's like, you know, Horribly, horribly off but I think, you know, it's boosting the accuracy by a little bit. So, maybe that's the biggest reason why. In terms of asking for help, and whether we're benchmarking asking for help yes we are.[00:32:29] Speaker: So one one thing we're working on now, which we're hoping to put out soon, is we we basically made SuperVig. Sweep edge issues. Like I'm having a, I'm having a problem with the matrix multiply. Please help. Because these are like, if anybody's run a popular open source, like framework, these are what half your issues are.[00:32:49] Speaker: You're like users show up and say like, my screen doesn't work. What, what's wrong or something. And so then you need to ask them questions and how to reproduce. So yeah, we're, we're, we're working on [00:33:00] that. I think. It, my impression is that agents are not very good at asking for help, even Claude. So like when, when they ask for help, they'll ask for help when they don't need it.[00:33:11] Speaker: And then won't ask for help when they do need it. So this is definitely like an issue, I think.[00:33:20] Speaker 4: Thanks for the great talk. I also have two questions.[00:33:23] Q&A: Web Agents and Interaction Methods[00:33:23] Speaker 4: It's first one can you talk a bit more about how the web agent interacts with So is there a VLM that looks at the web page layout and then you parse the HTML and select which buttons to click on? And if so do you think there's a future where there's like, so I work at Bing Microsoft AI.[00:33:41] Speaker 4: Do you think there's a future where the same web index, but there's an agent friendly web index where all the processing is done offline so that you don't need to spend time. Cleaning up, like, cleaning up these TML and figuring out what to click online. And any thoughts on, thoughts on that?[00:33:57] Speaker: Yeah, so great question. There's a lot of work on web [00:34:00] agents. I didn't go into, like, all of the details, but I think there's There's three main ways that agents interact with websites. The first way is the simplest way and the newest way, but it doesn't work very well, which is you take a screenshot of the website and then you click on a particular pixel value on the website.[00:34:23] Speaker: And Like models are not very good at that at the moment. Like they'll misclick. There was this thing about how like clawed computer use started like looking at pictures of Yellowstone national park or something like this. I don't know if you heard about this anecdote, but like people were like, oh, it's so human, it's looking for vacation.[00:34:40] Speaker: And it was like, no, it probably just misclicked on the wrong pixels and accidentally clicked on an ad. So like this is the simplest way. The second simplest way. You take the HTML and you basically identify elements in the HTML. You don't use any vision whatsoever. And then you say, okay, I want to click on this element.[00:34:59] Speaker: I want to enter text [00:35:00] in this element or something like that. But HTML is too huge. So it actually, it usually gets condensed down into something called an accessibility tree, which was made for screen readers for visually impaired people. And So that's another way. And then the third way is kind of a hybrid where you present the screenshot, but you also present like a textual summary of the output.[00:35:18] Speaker: And that's the one that I think will probably work best. What we're using is we're just using text at the moment. And that's just an implementation issue that we haven't implemented the. Visual stuff yet, but that's kind of like we're working on it now. Another thing that I should point out is we actually have two modalities for web browsing.[00:35:35] Speaker: Very recently we implemented this. And the reason why is because if you want to interact with full websites you will need to click on all of the elements or have the ability to click on all of the elements. But most of our work that we need websites for is just web browsing and like gathering information.[00:35:50] Speaker: So we have another modality where we convert all of it to markdown because that's like way more concise and easier for the agent to deal with. And then [00:36:00] can we create an index specifically for agents, maybe a markdown index or something like that would be, you know, would make sense. Oh, how would I make a successor to Swebench?[00:36:10] Speaker: So I mean, the first thing is there's like live code bench, which live code bench is basically continuously updating to make sure it doesn't leak into language model training data. That's easy to do for Swebench because it comes from real websites and those real websites are getting new issues all the time.[00:36:27] Speaker: So you could just do it on the same benchmarks that they have there. There's also like a pretty large number of things covering various coding tasks. So like, for example, Swebunch is mainly fixing issues, but there's also like documentation, there's generating tests that actually test the functionality that you want.[00:36:47] Speaker: And there there was a paper by a student at CMU on generating tests and stuff like that. So I feel like. Swebench is one piece of the puzzle, but you could also have like 10 different other tasks and then you could have like a composite [00:37:00] benchmark where you test all of these abilities, not just that particular one.[00:37:04] Speaker: Well, lots, lots of other things too, but[00:37:11] Speaker 2: Question from across. Use your mic, it will help. Um,[00:37:15] Speaker 5: Great talk. Thank you.[00:37:16] Q&A: Agent Architectures and Improvements[00:37:16] Speaker 5: My question is about your experience designing agent architectures. Specifically how much do you have to separate concerns in terms of tasks specific agents versus having one agent to do three or five things with a gigantic prompt with conditional paths and so on.[00:37:35] Speaker: Yeah, so that's a great question. So we have a basic coding and browsing agent. And I won't say basic, like it's a good, you know, it's a good agent, but it does coding and browsing. And it has instructions about how to do coding and browsing. That is enough for most things. Especially given a strong language model that has a lot of background knowledge about how to solve different types of tasks and how to use different APIs and stuff like that.[00:37:58] Speaker: We do have [00:38:00] a mechanism for something called micro agents. And micro agents are basically something that gets added to the prompt when a trigger is triggered. Right now it's very, very rudimentary. It's like if you detect the word GitHub anywhere, you get instructions about how to interact with GitHub, like use the API and don't browse.[00:38:17] Speaker: Also another one that I just added is for NPM, the like JavaScript package manager. And NPM, when it runs and it hits a failure, it Like hits in interactive terminals where it says, would you like to quit? Yep. Enter yes. And if that does it, it like stalls our agent for the time out until like two minutes.[00:38:36] Speaker: So like I added a new microagent whenever it started using NPM, it would Like get instructions about how to not use interactive terminal and stuff like that. So that's our current solution. Honestly, I like it a lot. It's simple. It's easy to maintain. It works really well and stuff like that. But I think there is a world where you would want something more complex than that.[00:38:55] Speaker 5: Got it. Thank you.[00:38:59] Speaker 6: I got a [00:39:00] question about MCP. I feel like this is the Anthropic Model Context Protocol. It seems like the most successful type of this, like, standardization of interactions between computers and agents. Are you guys adopting it? Is there any other competing standard?[00:39:16] Speaker 6: Anything, anything thought about it?[00:39:17] Speaker: Yeah, I think the Anth, so the Anthropic MCP is like, a way to It, it's essentially a collection of APIs that you can use to interact with different things on the internet. I, I think it's not a bad idea, but it, it's like, there's a few things that bug me a little bit about it.[00:39:40] Speaker: It's like we already have an API for GitHub, so why do we need an MCP for GitHub? Right. You know, like GitHub has an API, the GitHub API is evolving. We can look up the GitHub API documentation. So it seems like kind of duplicated a little bit. And also they have a setting where [00:40:00] it's like you have to spin up a server to serve your GitHub stuff.[00:40:04] Speaker: And you have to spin up a server to serve your like, you know, other stuff. And so I think it makes, it makes sense if you really care about like separation of concerns and security and like other things like this, but right now we haven't seen, we haven't seen that. To have a lot more value than interacting directly with the tools that are already provided.[00:40:26] Speaker: And that kind of goes into my general philosophy, which is we're already developing things for programmers. You know,[00:40:36] Speaker: how is an agent different than from a programmer? And it is different, obviously, you know, like agents are different from programmers, but they're not that different at this point. So we can kind of interact with the interfaces we create for, for programmers. Yeah. I might change my mind later though.[00:40:51] Speaker: So we'll see.[00:40:54] Speaker 7: Yeah. Hi. Thanks. Very interesting talk. You were saying that the agents you have right now [00:41:00] solve like maybe 30 percent of your, your issues out of the gate. I'm curious of the things that it doesn't do. Is there like a pattern that you observe? Like, Oh, like these are the sorts of things that it just seems to really struggle with, or is it just seemingly random?[00:41:15] Speaker: It's definitely not random. It's like, if you think it's more complex than it's. Like, just intuitively, it's more likely to fail. I've gotten a bit better at prompting also, so like, just to give an example it, it will sometimes fail to fix a GitHub workflow because it will not look at the GitHub workflow and understand what the GitHub workflow is doing before it solves the problem.[00:41:43] Speaker: So I, I think actually probably the biggest thing that it fails at is, um, er, that our, our agent plus Claude fails at is insufficient information gathering before trying to solve the task. And so if you provide all, if you provide instructions that it should do information [00:42:00] gathering beforehand, it tends to do well.[00:42:01] Speaker: If you don't provide sufficient instructions, it will try to solve the task without, like, fully understanding the task first, and then fail, and then you need to go back and give feedback. You know, additional feedback. Another example, like, I, I love this example. While I was developing the the monitor website that I, I showed here, we hit a really tricky bug where it was writing out a cache file to a different directory than it was reading the cache file from.[00:42:26] Speaker: And I had no idea what to do. I had no idea what was going on. I, I thought the bug was in a different part of the code, but what I asked it to do was come up with five possible reasons why this could be failing and decreasing order of likelihood and examine all of them. And that worked and it could just go in and like do that.[00:42:44] Speaker: So like I think a certain level of like scaffolding about like how it should sufficiently Gather all the information that's necessary in order to solve a task is like, if that's missing, then that's probably the biggest failure point at the moment. [00:43:00][00:43:01] Speaker 7: Thanks.[00:43:01] Speaker 6: Yeah.[00:43:06] Speaker 6: I'm just, I'm just using this as a chance to ask you all my questions.[00:43:09] Q&A: Self-Improving Agents and Authentication[00:43:09] Speaker 6: You had a, you had a slide on here about like self improving agents or something like that with memory. It's like a really throwaway slide for like a super powerful idea. It got me thinking about how I would do it. I have no idea how.[00:43:21] Speaker 6: So I just wanted you to chain a thought more on this.[00:43:25] Speaker: Yeah, self, self improving. So I think the biggest reason, like the simplest possible way to create a self improving agent. The problem with that is to have a really, really strong language model that with infinite context, and it can just go back and look at like all of its past experiences and, you know, learn from them.[00:43:46] Speaker: You might also want to remove the bad stuff just so it doesn't over index on it's like failed past experiences. But the problem is a really powerful language model is large. Infinite context is expensive. We don't have a good way to [00:44:00] index into it because like rag, Okay. At least in my experience, RAG from language to code doesn't work super well.[00:44:08] Speaker: So I think in the end, it's like, that's the way I would like to solve this problem. I'd like to have an infinite context and somehow be able to index into it appropriately. And I think that would mostly solve it. Another thing you can do is fine tuning. So I think like RAG is one way to get information into your model.[00:44:23] Speaker: Fine tuning is another way to get information into your model. So. That might be another way of continuously improving. Like you identify when you did a good job and then just add all of the good examples into your model.[00:44:34] Speaker 6: Yeah. So, you know, how like Voyager tries to write code into a skill library and then you reuse as a skill library, right?[00:44:40] Speaker 6: So that it improves in the sense that it just builds up the skill library over time.[00:44:44] Speaker: Yep.[00:44:44] Speaker 6: One thing I was like thinking about and there's this idea of, from, from Devin, your, your arch nemesis of playbooks. I don't know if you've seen them.[00:44:52] Speaker: Yeah, I mean, we're calling them workflows, but they're simpler.[00:44:55] Speaker 6: Yeah, so like, basically, like, you should, like, once a workflow works, you can kind of, [00:45:00] like, persist them as a skill library. Yeah. Right? Like I, I feel like that there's a, that's like some in between, like you said, you know, it's hard to do rag between language and code, but I feel like that is ragged for, like, I've done this before, last time I did it, this, this worked.[00:45:14] Speaker 6: So I'm just going to shortcut. All the stuff that failed before.[00:45:18] Speaker: Yeah, I totally, I think it's possible. It's just, you know, not, not trivial at the same time. I'll explain the two curves. So basically, the base, the baseline is just an agent that does it from scratch every time. And this curve up here is agent workflow memory where it's like adding the successful experiences back into the prompt.[00:45:39] Speaker: Why is this improving? The reason why is because just it failed on the first few examples and for the average to catch up it, it took a little bit of time. So it's not like this is actually improving it. You could just basically view the this one is constant and then this one is like improving.[00:45:56] Speaker: Like this, basically you can see it's continuing to go [00:46:00] up.[00:46:01] Speaker 8: How do you think we're going to solve the authentication problem for agents right now?[00:46:05] Speaker: When you say authentication, you mean like credentials, like, yeah.[00:46:09] Speaker 8: Yeah. Cause I've seen a few like startup solutions today, but it seems like it's limited to the amount of like websites or actual like authentication methods that it's capable of performing today.[00:46:19] Speaker: Yeah. Great questions. So. My preferred solution to this at the moment is GitHub like fine grained authentication tokens and GitHub fine grained authentication tokens allow you to specify like very free. On a very granular basis on this repo, you have permission to do this, on this repo, you have permission to do this.[00:46:41] Speaker: You also can prevent people from pushing to the main branch unless they get approved. You can do all of these other things. And I think these were all developed for human developers. Or like, the branch protection rules were developed for human developers. The fine grained authentication tokens were developed for GitHub apps.[00:46:56] Speaker: I think for GitHub, maybe [00:47:00] just pushing this like a little bit more is the way to do this. For other things, they're totally not prepared to give that sort of fine grained control. Like most APIs don't have something like a fine grained authentication token. And that goes into my like comment that we're going to need to prepare the world for agents, I think.[00:47:17] Speaker: But I think like the GitHub authentication tokens are like a good template for how you could start doing that maybe, but yeah, I don't, I don't, I don't have an answer.[00:47:25] Speaker 8: I'll let you know if I find one.[00:47:26] Speaker: Okay. Yeah.[00:47:31] Live Demonstration and Closing Remarks[00:47:31] Speaker: I'm going to finish up. Let, let me just see.[00:47:37] Speaker: Okay. So this one this one did write a script. I'm not going to actually read it for you. And then the other one, let's see.[00:47:51] Speaker: Yeah. So it sent a PR, sorry. What is, what is the PR URL?[00:48:00][00:48:02] Speaker: So I don't, I don't know if this sorry, that's taking way longer than it should. Okay, cool. Yeah. So this one sent a PR. I'll, I'll tell you later if this actually like successfully Oh, no, it's deployed on Vercel, so I can actually show you, but let's, let me try this real quick. Sorry. I know I don't have time.[00:48:24] Speaker: Yeah, there you go. I have pie charts now. So it's so fun. It's so fun to play with these things. Cause you could just do that while I'm giving a, you know, talk and things like that. So, yeah, thanks. Get full access to Latent Space at www.latent.space/subscribe

In this episode, Clod and Hilary share Christmas memories, some heartwarming, many ridiculous, and all meant to provide a little holiday cheer. More Secrets:⁠⁠ www.mymothersdiaries.com⁠⁠ Shop: ⁠www.mymothersdiaries.com/mymotherscloset⁠ Listen: https://www.mymothersdiaries.com/mymotherspodcast Follow Us! Instagram: ⁠https://www.instagram.com/mymothersdiaries/ TikTok: ⁠https://www.tiktok.com/@mymothersdiaries Facebook: ⁠https://www.facebook.com/mymothersdiaries Thank you to Dead Gowns for our intro song! Listen to Kid 1 by Dead Gowns: https://www.deadgowns.com/

Trigger warning: As usual, Clod and Hilary begin the episode by sharing zany moments. But when they shift into a discussion of inappropriate comments and behaviors they've experienced from healthcare professionals, the tone takes an unexpected serious turn. So please take care as you listen. More Secrets:⁠⁠ www.mymothersdiaries.com⁠⁠ Shop: ⁠www.mymothersdiaries.com/mymotherscloset⁠ Listen: https://www.mymothersdiaries.com/mymotherspodcast Follow Us! Instagram: ⁠https://www.instagram.com/mymothersdiaries/ TikTok: ⁠https://www.tiktok.com/@mymothersdiaries Facebook: ⁠https://www.facebook.com/mymothersdiaries Thank you to Dead Gowns for our intro song! Listen to Kid 1 by Dead Gowns: https://www.deadgowns.com/

The full schedule for Latent Space LIVE! at NeurIPS has been announced, featuring Best of 2024 overview talks for the AI Startup Landscape, Computer Vision, Open Models, Transformers Killers, Synthetic Data, Agents, and Scaling, and speakers from Sarah Guo of Conviction, Roboflow, AI2/Meta, Recursal/Together, HuggingFace, OpenHands and SemiAnalysis. Join us for the IRL event/Livestream! Alessio will also be holding a meetup at AWS Re:Invent in Las Vegas this Wednesday. See our new Events page for dates of AI Engineer Summit, Singapore, and World's Fair in 2025. LAST CALL for questions for our big 2024 recap episode! Submit questions and messages on Speakpipe here for a chance to appear on the show!When we first observed that GPT Wrappers are Good, Actually, we did not even have Bolt on our radar. Since we recorded our Anthropic episode discussing building Agents with the new Claude 3.5 Sonnet, Bolt.new (by Stackblitz) has easily cleared the $8m ARR bar, repeating and accelerating its initial $4m feat.There are very many AI code generators and VS Code forks out there, but Bolt probably broke through initially because of its incredible zero shot low effort app generation:But as we explain in the pod, Bolt also emphasized deploy (Netlify)/ backend (Supabase)/ fullstack capabilities on top of Stackblitz's existing WebContainer full-WASM-powered-developer-environment-in-the-browser tech. Since then, the team has been shipping like mad (with weekly office hours), with bugfixing, full screen, multi-device, long context, diff based edits (using speculative decoding like we covered in Inference, Fast and Slow).All of this has captured the imagination of low/no code builders like Greg Isenberg and many others on YouTube/TikTok/Reddit/X/Linkedin etc:Just as with Fireworks, our relationship with Bolt/Stackblitz goes a bit deeper than normal - swyx advised the launch and got a front row seat to this epic journey, as well as demoed it with Realtime Voice at the recent OpenAI Dev Day. So we are very proud to be the first/closest to tell the full open story of Bolt/Stackblitz!Flow Engineering + Qodo/AlphaCodium UpdateIn year 2 of the pod we have been on a roll getting former guests to return as guest cohosts (Harrison Chase, Aman Sanger, Jon Frankle), and it was a pleasure to catch Itamar Friedman back on the pod, giving us an update on all things Qodo and Testing Agents from our last catchup a year and a half ago:Qodo (they renamed in September) went viral in early January this year with AlphaCodium (paper here, code here) beating DeepMind's AlphaCode with high efficiency:With a simple problem solving code agent:* The first step is to have the model reason about the problem. They describe it using bullet points and focus on the goal, inputs, outputs, rules, constraints, and any other relevant details.* Then, they make the model reason about the public tests and come up with an explanation of why the input leads to that particular output. * The model generates two to three potential solutions in text and ranks them in terms of correctness, simplicity, and robustness. * Then, it generates more diverse tests for the problem, covering cases not part of the original public tests. * Iteratively, pick a solution, generate the code, and run it on a few test cases. * If the tests fail, improve the code and repeat the process until the code passes every test.swyx has previously written similar thoughts on types vs tests for putting bounds on program behavior, but AlphaCodium extends this to AI generated tests and code.More recently, Itamar has also shown that AlphaCodium's techniques also extend well to the o1 models:Making Flow Engineering a useful technique to improve code model performance on every model. This is something we see AI Engineers uniquely well positioned to do compared to ML Engineers/Researchers.Full Video PodcastLike and subscribe!Show Notes* Itamar* Qodo* First episode* Eric* Bolt* StackBlitz* Thinkster* AlphaCodium* WebContainersChapters* 00:00:00 Introductions & Updates* 00:06:01 Generic vs. Specific AI Agents* 00:07:40 Maintaining vs Creating with AI* 00:17:46 Human vs Agent Computer Interfaces* 00:20:15 Why Docker doesn't work for Bolt* 00:24:23 Creating Testing and Code Review Loops* 00:28:07 Bolt's Task Breakdown Flow* 00:31:04 AI in Complex Enterprise Environments* 00:41:43 AlphaCodium* 00:44:39 Strategies for Breaking Down Complex Tasks* 00:45:22 Building in Open Source* 00:50:35 Choosing a product as a founder* 00:59:03 Reflections on Bolt Success* 01:06:07 Building a B2C GTM* 01:18:11 AI Capabilities and Pricing Tiers* 01:20:28 What makes Bolt unique* 01:23:07 Future Growth and Product Development* 01:29:06 Competitive Landscape in AI Engineering* 01:30:01 Advice to Founders and Embracing AI* 01:32:20 Having a baby and completing an Iron ManTranscriptAlessio [00:00:00]: Hey everyone, welcome to the Latent Space Podcast. This is Alessio, partner and CTO at Decibel Partners, and I'm joined by my co-host Swyx, founder of Smol.ai.Swyx [00:00:12]: Hey, and today we're still in our sort of makeshift in-between studio, but we're very delighted to have a former returning guest host, Itamar. Welcome back.Itamar [00:00:21]: Great to be here after a year or more. Yeah, a year and a half.Swyx [00:00:24]: You're one of our earliest guests on Agents. Now you're CEO co-founder of Kodo. Right. Which has just been renamed. You also raised a $40 million Series A, and we can get caught up on everything, but we're also delighted to have our new guest, Eric. Welcome.Eric [00:00:42]: Thank you. Excited to be here. Should I say Bolt or StackBlitz?Swyx [00:00:45]: Like, is it like its own company now or?Eric [00:00:47]: Yeah. Bolt's definitely bolt.new. That's the thing that we're probably the most known for, I imagine, at this point.Swyx [00:00:54]: Which is ridiculous to say because you were working at StackBlitz for so long.Eric [00:00:57]: Yeah. I mean, within a week, we were doing like double the amount of traffic. And StackBlitz had been online for seven years, and we were like, what? But anyways, yeah. So we're StackBlitz, the company behind bolt.new. If you've heard of bolt.new, that's our stuff. Yeah.Swyx [00:01:12]: Yeah.Itamar [00:01:13]: Excellent. I see, by the way, that the founder mode, you need to know to capture opportunities. So kudos on doing that, right? You're working on some technology, and then suddenly you can exploit that to a new world. Yeah.Eric [00:01:24]: Totally. And I think, well, not to jump, but 100%, I mean, a couple of months ago, we had the idea for Bolt earlier this year, but we haven't really shared this too much publicly. But we actually had tried to build it with some of those state-of-the-art models back in January, February, you can kind of imagine which, and they just weren't good enough to actually do the code generation where the code was accurate and it was fast and whatever have you without a ton of like rag, but then there was like issues with that. So we put it on the shelf and then we got kind of a sneak peek of some of the new models that have come out in the past couple of months now. And so once we saw that, once we actually saw the code gen from it, we were like, oh my God, like, okay, we can build a product around this. And so that was really the impetus of us building the thing. But with that, it was StackBlitz, the core StackBlitz product the past seven years has been an IDE for developers. So the entire user experience flow we've built up just didn't make sense. And so when we kind of went out to build Bolt, we just thought, you know, if we were inventing our product today, what would the interface look like given what is now possible with the AI code gen? And so there's definitely a lot of conversations we had internally, but you know, just kind of when we logically laid it out, we were like, yeah, I think it makes sense to just greenfield a new thing and let's see what happens. If it works great, then we'll figure it out. If it doesn't work great, then it'll get deleted at some point. So that's kind of how it actually came to be.Swyx [00:02:49]: I'll mention your background a little bit. You were also founder of Thinkster before you started StackBlitz. So both of you are second time founders. Both of you have sort of re-founded your company recently. Yours was more of a rename. I think a slightly different direction as well. And then we can talk about both. Maybe just chronologically, should we get caught up on where Kodo is first and then you know, just like what people should know since the last pod? Sure.Itamar [00:03:12]: The last pod was two months after we launched and we basically had the vision that we talked about. The idea that software development is about specification, test and code, etc. We are more on the testing part as in essence, we think that if you solve testing, you solve software development. The beautiful chart that we'll put up on screen. And testing is a really big field, like there are many dimensions, unit testing, the level of the component, how big it is, how large it is. And then there is like different type of testing, is it regression or smoke or whatever. So back then we only had like one ID extension with unit tests as in focus. One and a half year later, first ID extension supports more type of testing as context aware. We index local, local repos, but also 10,000s of repos for Fortune 500 companies. We have another agent, another tool that is called, the pure agent is the open source and the commercial one is CodoMerge. And then we have another open source called CoverAgent, which is not yet a commercial product coming very soon. It's very impressive. It could be that already people are approving automated pull requests that they don't even aware in really big open sources. So once we have enough of these, we will also launch another agent. So for the first one and a half year, what we did is grew in our offering and mostly on the side of, does this code actually works, testing, code review, et cetera. And we believe that's the critical milestone that needs to be achieved to actually have the AI engineer for enterprise software. And then like for the first year was everything bottom up, getting to 1 million installation. 2024, that was 2023, 2024 was starting to monetize, to feel like how it is to make the first buck. So we did the teams offering, it went well with a thousand of teams, et cetera. And then we started like just a few months ago to do enterprise with everything you need, which is a lot of things that discussed in the last post that was just released by Codelm. So that's how we call it at Codelm. Just opening the brackets, our company name was Codelm AI, and we renamed to Codo and we call our models Codelm. So back to my point, so we started Enterprise Motion and already have multiple Fortune 100 companies. And then with that, we raised a series of $40 million. And what's exciting about it is that enables us to develop more agents. That's our focus. I think it's very different. We're not coming very soon with an ID or something like that.Swyx [00:06:01]: You don't want to fork this code?Itamar [00:06:03]: Maybe we'll fork JetBrains or something just to be different.Swyx [00:06:08]: I noticed that, you know, I think the promise of general purpose agents has kind of died. Like everyone is doing kind of what you're doing. There's Codogen, Codomerge, and then there's a third one. What's the name of it?Itamar [00:06:17]: Yeah. Codocover. Cover. Which is like a commercial version of a cover agent. It's coming soon.Swyx [00:06:23]: Yeah. It's very similar with factory AI, also doing like droids. They all have special purpose doing things, but people don't really want general purpose agents. Right. The last time you were here, we talked about AutoGBT, the biggest thing of 2023. This year, not really relevant anymore. And I think it's mostly just because when you give me a general purpose agent, I don't know what to do with it.Eric [00:06:42]: Yeah.Itamar [00:06:43]: I totally agree with that. We're seeing it for a while and I think it will stay like that despite the computer use, et cetera, that supposedly can just replace us. You can just like prompt it to be, hey, now be a QA or be a QA person or a developer. I still think that there's a few reasons why you see like a dedicated agent. Again, I'm a bit more focused, like my head is more on complex software for big teams and enterprise, et cetera. And even think about permissions and what are the data sources and just the same way you manage permissions for users. Developers, you probably want to have dedicated guardrails and dedicated approvals for agents. I intentionally like touched a point on not many people think about. And of course, then what you can think of, like maybe there's different tools, tool use, et cetera. But just the first point by itself is a good reason why you want to have different agents.Alessio [00:07:40]: Just to compare that with Bot.new, you're almost focused on like the application is very complex and now you need better tools to kind of manage it and build on top of it. On Bot.new, it's almost like I was using it the other day. There's basically like, hey, look, I'm just trying to get started. You know, I'm not very opinionated on like how you're going to implement this. Like this is what I want to do. And you build a beautiful app with it. What people ask as the next step, you know, going back to like the general versus like specific, have you had people say, hey, you know, this is great to start, but then I want a specific Bot.new dot whatever else to do a more vertical integration and kind of like development or what's the, what do people say?Eric [00:08:18]: Yeah. I think, I think you kind of hit the, hit it head on, which is, you know, kind of the way that we've, we've kind of talked about internally is it's like people are using Bolt to go from like 0.0 to 1.0, like that's like kind of the biggest unlock that Bolt has versus most other things out there. I mean, I think that's kind of what's, what's very unique about Bolt. I think the, you know, the working on like existing enterprise applications is, I mean, it's crazy important because, you know, there's a, you look, when you look at the fortune 500, I mean, these code bases, some of these have been around for 20, 30 plus years. And so it's important to be going from, you know, 101.3 to 101.4, et cetera. I think for us, so what's been actually pretty interesting is we see there's kind of two different users for us that are coming in and it's very distinct. It's like people that are developers already. And then there's people that have never really written software and more if they have, it's been very, very minimal. And so in the first camp, what these developers are doing, like to go from zero to one, they're coming to Bolt and then they're ejecting the thing to get up or just downloading it and, you know, opening cursor, like whatever to, to, you know, keep iterating on the thing. And sometimes they'll bring it back to Bolt to like add in a huge piece of functionality or something. Right. But for the people that don't know how to code, they're actually just, they, they live in this thing. And that was one of the weird things when we launched is, you know, within a day of us being online, one of the most popular YouTube videos, and there's been a ton since, which was, you know, there's like, oh, Bolt is the cursor killer. And I originally saw the headlines and I was like, thanks for the views. I mean, I don't know. This doesn't make sense to me. That's not, that's not what we kind of thought.Swyx [00:09:44]: It's how YouTubers talk to each other. Well, everything kills everything else.Eric [00:09:47]: Totally. But what blew my mind was that there was any comparison because it's like cursor is a, is a local IDE product. But when, when we actually kind of dug into it and we, and we have people that are using our product saying this, I'm not using cursor. And I was like, what? And it turns out there are hundreds of thousands of people that we have seen that we're using cursor and we're trying to build apps with that where they're not traditional software does, but we're heavily leaning on the AI. And as you can imagine, it is very complicated, right? To do that with cursor. So when Bolt came out, they're like, wow, this thing's amazing because it kind of inverts the complexity where it's like, you know, it's not an IDE, it's, it's a, it's a chat-based sort of interface that we have. So that's kind of the split, which is rather interesting. We've had like the first startups now launch off of Bolt entirely where this, you know, tomorrow I'm doing a live stream with this guy named Paul, who he's built an entire CRM using this thing and you know, with backend, et cetera. And people have made their first money on the internet period, you know, launching this with Stripe or whatever have you. So that's, that's kind of the two main, the two main categories of folks that we see using Bolt though.Itamar [00:10:51]: I agree that I don't understand the comparison. It doesn't make sense to me. I think like we have like two type of families of tools. One is like we re-imagine the software development. I think Bolt is there and I think like a cursor is more like a evolution of what we already have. It's like taking the IDE and it's, it's amazing and it's okay, let's, let's adapt the IDE to an era where LLMs can do a lot for us. And Bolt is more like, okay, let's rethink everything totally. And I think we see a few tools there, like maybe Vercel, Veo and maybe Repl.it in that area. And then in the area of let's expedite, let's change, let's, let's progress with what we already have. You can see Cursor and Kodo, but we're different between ourselves, Cursor and Kodo, but definitely I think that comparison doesn't make sense.Alessio [00:11:42]: And just to set the context, this is not a Twitter demo. You've made 4 million of revenue in four weeks. So this is, this is actually working, you know, it's not a, what, what do you think that is? Like, there's been so many people demoing coding agents on Twitter and then it doesn't really work. And then you guys were just like, here you go, it's live, go use it, pay us for it. You know, is there anything in the development that was like interesting and maybe how that compares to building your own agents?Eric [00:12:08]: We had no idea, honestly, like we, we, we've been pretty blown away and, and things have just kind of continued to grow faster since then. We're like, oh, today is week six. So I, I kind of came back to the point you just made, right, where it's, you, you kind of outlined, it's like, there's kind of this new market of like kind of rethinking the software development and then there's heavily augmenting existing developers. I think that, you know, both of which are, you know, AI code gen being extremely good, it's allowed existing developers, it's allowing existing developers to camera out software far faster than they could have ever before, right? It's like the ultimate power tool for an existing developer. But this code gen stuff is now so good. And then, and we saw this over the past, you know, from the beginning of the year when we tried to first build, it's actually lowered the barrier to people that, that aren't traditionally software engineers. But the kind of the key thing is if you kind of think about it from, imagine you've never written software before, right? My co-founder and I, he and I grew up down the street from each other in Chicago. We learned how to code when we were 13 together and we've been building stuff ever since. And this is back in like the mid 2000s or whatever, you know, there was nothing for free to learn from online on the internet and how to code. For our 13th birthdays, we asked our parents for, you know, O'Reilly books cause you couldn't get this at the library, right? And so instead of like an Xbox, we got, you know, programming books. But the hardest part for everyone learning to code is getting an environment set up locally, you know? And so when we built StackBlitz, like kind of the key thesis, like seven years ago, the insight we had was that, Hey, it seems like the browser has a lot of new APIs like WebAssembly and service workers, et cetera, where you could actually write an operating system that ran inside the browser that could boot in milliseconds. And you, you know, basically there's this missing capability of the web. Like the web should be able to build apps for the web, right? You should be able to build the web on the web. Every other platform has that, Visual Studio for Windows, Xcode for Mac. The web has no built in primitive for this. And so just like our built in kind of like nerd instinct on this was like, that seems like a huge hole and it's, you know, it will be very valuable or like, you know, very valuable problem to solve. So if you want to set up that environments, you know, this is what we spent the past seven years doing. And the reality is existing developers have running locally. They already know how to set up that environment. So the problem isn't as acute for them. When we put Bolt online, we took that technology called WebContainer and married it with these, you know, state of the art frontier models. And the people that have the most pain with getting stuff set up locally is people that don't code. I think that's been, you know, really the big explosive reason is no one else has been trying to make dev environments work inside of a browser tab, you know, for the past if since ever, other than basically our company, largely because there wasn't an immediate demand or need. So I think we kind of find ourselves at the right place at the right time. And again, for this market of people that don't know how to write software, you would kind of expect that you should be able to do this without downloading something to your computer in the same way that, hey, I don't have to download Photoshop now to make designs because there's Figma. I don't have to download Word because there's, you know, Google Docs. They're kind of looking at this as that sort of thing, right? Which was kind of the, you know, our impetus and kind of vision from the get-go. But you know, the code gen, the AI code gen stuff that's come out has just been, you know, an order of magnitude multiplier on how magic that is, right? So that's kind of my best distillation of like, what is going on here, you know?Alessio [00:15:21]: And you can deploy too, right?Eric [00:15:22]: Yeah.Alessio [00:15:23]: Yeah.Eric [00:15:24]: And so that's, what's really cool is it's, you know, we have deployment built in with Netlify and this is actually, I think, Sean, you actually built this at Netlify when you were there. Yeah. It's one of the most brilliant integrations actually, because, you know, effectively the API that Sean built, maybe you can speak to it, but like as a provider, we can just effectively give files to Netlify without the user even logging in and they have a live website. And if they want to keep, hold onto it, they can click a link and claim it to their Netlify account. But it basically is just this really magic experience because when you come to Bolt, you say, I want a website. Like my mom, 70, 71 years old, made her first website, you know, on the internet two weeks ago, right? It was about her nursing days.Swyx [00:16:03]: Oh, that's fantastic though. It wouldn't have been made.Eric [00:16:06]: A hundred percent. Cause even in, you know, when we've had a lot of people building personal, like deeply personal stuff, like in the first week we launched this, the sales guy from the East Coast, you know, replied to a tweet of mine and he said, thank you so much for building this to your team. His daughter has a medical condition and so for her to travel, she has to like line up donors or something, you know, so ahead of time. And so he actually used Bolt to make a website to do that, to actually go and send it to folks in the region she was going to travel to ahead of time. I was really touched by it, but I also thought like, why, you know, why didn't he use like Wix or Squarespace? Right? I mean, this is, this is a solved problem, quote unquote, right? And then when I thought, I actually use Squarespace for my, for my, uh, the wedding website for my wife and I, like back in 2021, so I'm familiar, you know, it was, it was faster. I know how to code. I was like, this is faster. Right. And I thought back and I was like, there's a whole interface you have to learn how to use. And it's actually not that simple. There's like a million things you can configure in that thing. When you come to Bolt, there's a, there's a text box. You just say, I need a, I need a wedding website. Here's the date. Here's where it is. And here's a photo of me and my wife, put it somewhere relevant. It's actually the simplest way. And that's what my, when my mom came, she said, uh, I'm Pat Simons. I was a nurse in the seventies, you know, and like, here's the things I did and a website came out. So coming back to why is this such a, I think, why are we seeing this sort of growth? It's, this is the simplest interface I think maybe ever created to actually build it, a deploy a website. And then that website, my mom made, she's like, okay, this looks great. And there's, there's one button, you just click it, deploy, and it's live and you can buy a domain name, attach it to it. And you know, it's as simple as it gets, it's getting even simpler with some of the stuff we're working on. But anyways, so that's, it's, it's, uh, it's been really interesting to see some of the usage like that.Swyx [00:17:46]: I can offer my perspective. So I, you know, I probably should have disclosed a little bit that, uh, I'm a, uh, stack list investor.Alessio [00:17:53]: Canceled the episode. I know, I know. Don't play it now. Pause.Eric actually reached out to ShowMeBolt before the launch. And we, you know, we talked a lot about, like, the framing of, of what we're going to talk about how we marketed the thing, but also, like, what we're So that's what Bolt was going to need, like a whole sort of infrastructure.swyx: Netlify, I was a maintainer but I won't take claim for the anonymous upload. That's actually the origin story of Netlify. We can have Matt Billman talk about it, but that was [00:18:00] how Netlify started. You could drag and drop your zip file or folder from your desktop onto a website, it would have a live URL with no sign in.swyx: And so that was the origin story of Netlify. And it just persists to today. And it's just like it's really nice, interesting that both Bolt and CognitionDevIn and a bunch of other sort of agent type startups, they all use Netlify to deploy because of this one feature. They don't really care about the other features.swyx: But, but just because it's easy for computers to use and talk to it, like if you build an interface for computers specifically, that it's easy for them to Navigate, then they will be used in agents. And I think that's a learning that a lot of developer tools companies are having. That's my bolt launch story and now if I say all that stuff.swyx: And I just wanted to come back to, like, the Webcontainers things, right? Like, I think you put a lot of weight on the technical modes. I think you also are just like, very good at product. So you've, you've like, built a better agent than a lot of people, the rest of us, including myself, who have tried to build these things, and we didn't get as far as you did.swyx: Don't shortchange yourself on products. But I think specifically [00:19:00] on, on infra, on like the sandboxing, like this is a thing that people really want. Alessio has Bax E2B, which we'll have on at some point, talking about like the sort of the server full side. But yours is, you know, inside of the browser, serverless.swyx: It doesn't cost you anything to serve one person versus a million people. It doesn't, doesn't cost you anything. I think that's interesting. I think in theory, we should be able to like run tests because you can run the full backend. Like, you can run Git, you can run Node, you can run maybe Python someday.swyx: We talked about this. But ideally, you should be able to have a fully gentic loop, running code, seeing the errors, correcting code, and just kind of self healing, right? Like, I mean, isn't that the dream?Eric: Totally.swyx: Yeah,Eric: totally. At least in bold, we've got, we've got a good amount of that today. I mean, there's a lot more for us to do, but one of the nice things, because like in web container, you know, there's a lot of kind of stuff you go Google like, you know, turn docker container into wasm.Eric: You'll find a lot of stuff out there that will do that. The problem is it's very big, it's slow, and that ruins the experience. And so what we ended up doing is just writing an operating system from [00:20:00] scratch that was just purpose built to, you know, run in a browser tab. And the reason being is, you know, Docker 2 awesome things will give you an image that's like out 60 to 100 megabits, you know, maybe more, you know, and our, our OS, you know, kind of clocks in, I think, I think we're in like a, maybe, maybe a megabyte or less or something like that.Eric: I mean, it's, it's, you know, really, really, you know, stripped down.swyx: This is basically the task involved is I understand that it's. Mapping every single, single Linux call to some kind of web, web assembly implementation,Eric: but more or less, and, and then there's a lot of things actually, like when you're looking at a dev environment, there's a lot of things that you don't need that a traditional OS is gonna have, right?Eric: Like, you know audio drivers or you like, there's just like, there's just tons of things. Oh, yeah. Right. Yeah. That goes . Yeah. You can just kind, you can, you can kind of tos them. Or alternatively, what you can do is you can actually be the nice thing. And this is, this kind of comes back to the origins of browsers, which is, you know, they're, they're at the beginning of the web and, you know, the late nineties, there was two very different kind of visions for the web where Alan Kay vehemently [00:21:00] disagree with the idea that should be document based, which is, you know, Tim Berners Lee, you know, that, and that's kind of what ended up winning, winning was this document based kind of browsing documents on the web thing.Eric: Alan Kay, he's got this like very famous quote where he said, you know, you want web browsers to be mini operating systems. They should download little mini binaries and execute with like a little mini virtualized operating system in there. And what's kind of interesting about the history, not to geek out on this aspect, what's kind of interesting about the history is both of those folks ended up being right.Eric: Documents were actually the pragmatic way that the web worked. Was, you know, became the most ubiquitous platform in the world to the degree now that this is why WebAssembly has been invented is that we're doing, we need to do more low level things in a browser, same thing with WebGPU, et cetera. And so all these APIs, you know, to build an operating system came to the browser.Eric: And that was actually the realization we had in 2017 was, holy heck, like you can actually, you know, service workers, which were designed for allowing your app to work offline. That was the kind of the key one where it was like, wait a second, you can actually now run. Web servers within a [00:22:00] browser, like you can run a server that you open up.Eric: That's wild. Like full Node. js. Full Node. js. Like that capability. Like, I can have a URL that's programmatically controlled. By a web application itself, boom. Like the web can build the web. The primitive is there. Everyone at the time, like we talked to people that like worked on, you know Chrome and V8 and they were like, uhhhh.Eric: You know, like I don't know. But it's one of those things you just kind of have to go do it to find out. So we spent a couple of years, you know, working on it and yeah. And, and, and got to work in back in 2021 is when we kind of put the first like data of web container online. Butswyx: in partnership with Google, right?swyx: Like Google actually had to help you get over the finish line with stuff.Eric: A hundred percent, because well, you know, over the years of when we were doing the R and D on the thing. Kind of the biggest challenge, the two ways that you can kind of test how powerful and capable a platform are, the two types of applications are one, video games, right, because they're just very compute intensive, a lot of calculations that have to happen, right?Eric: The second one are IDEs, because you're talking about actually virtualizing the actual [00:23:00] runtime environment you are in to actually build apps on top of it, which requires sophisticated capabilities, a lot of access to data. You know, a good amount of compute power, right, to effectively, you know, building app in app sort of thing.Eric: So those, those are the stress tests. So if your platform is missing stuff, those are the things where you find out. Those are, those are the people building games and IDEs. They're the ones filing bugs on operating system level stuff. And for us, browser level stuff.Eric [00:23:47]: yeah, what ended up happening is we were just hammering, you know, the Chromium bug tracker, and they're like, who are these guys? Yeah. And, and they were amazing because I mean, just making Chrome DevTools be able to debug, I mean, it's, it's not, it wasn't originally built right for debugging an operating system, right? They've been phenomenal working with us and just kind of really pushing the limits, but that it's a rising tide that's kind of lifted all boats because now there's a lot of different types of applications that you can debug with Chrome Dev Tools that are running a browser that runs more reliably because just the stress testing that, that we and, you know, games that are coming to the web are kind of pushing as well, but.Itamar [00:24:23]: That's awesome. About the testing, I think like most, let's say coding assistant from different kinds will need this loop of testing. And even I would add code review to some, to some extent that you mentioned. How is testing different from code review? Code review could be, for example, PR review, like a code review that is done at the point of when you want to merge branches. But I would say that code review, for example, checks best practices, maintainability, and so on. It's not just like CI, but more than CI. And testing is like a more like checking functionality, et cetera. So it's different. We call, by the way, all of these together code integrity, but that's a different story. Just to go back to the, to the testing and specifically. Yeah. It's, it's, it's since the first slide. Yeah. We're consistent. So if we go back to the testing, I think like, it's not surprising that for us testing is important and for Bolt it's testing important, but I want to shed some light on a different perspective of it. Like let's think about autonomous driving. Those startups that are doing autonomous driving for highway and autonomous driving for the city. And I think like we saw the autonomous of the highway much faster and reaching to a level, I don't know, four or so much faster than those in the city. Now, in both cases, you need testing and quote unquote testing, you know, verifying validation that you're doing the right thing on the road and you're reading and et cetera. But it's probably like so different in the city that it could be like actually different technology. And I claim that we're seeing something similar here. So when you're building the next Wix, and if I was them, I was like looking at you and being a bit scared. That's what you're disrupting, what you just said. Then basically, I would say that, for example, the UX UI is freaking important. And because you're you're more aiming for the end user. In this case, maybe it's an end user that doesn't know how to develop for developers. It's also important. But let alone those that do not know to develop, they need a slick UI UX. And I think like that's one reason, for example, I think Cursor have like really good technology. I don't know the underlying what's under the hood, but at least what they're saying. But I think also their UX UI is great. It's a lot because they did their own ID. While if you're aiming for the city AI, suddenly like there's a lot of testing and code review technology that it's not necessarily like that important. For example, let's talk about integration tests. Probably like a lot of what you're building involved at the moment is isolated applications. Maybe the vision or the end game is maybe like having one solution for everything. It could be that eventually the highway companies will go into the city and the other way around. But at the beginning, there is a difference. And integration tests are a good example. I guess they're a bit less important. And when you think about enterprise software, they're really important. So to recap, like I think like the idea of looping and verifying your test and verifying your code in different ways, testing or code review, et cetera, seems to be important in the highway AI and the city AI, but in different ways and different like critical for the city, even more and more variety. Actually, I was looking to ask you like what kind of loops you guys are doing. For example, when I'm using Bolt and I'm enjoying it a lot, then I do see like sometimes you're trying to catch the errors and fix them. And also, I noticed that you're breaking down tasks into smaller ones and then et cetera, which is already a common notion for a year ago. But it seems like you're doing it really well. So if you're willing to share anything about it.Eric [00:28:07]: Yeah, yeah. I realized I never actually hit the punchline of what I was saying before. I mentioned the point about us kind of writing an operating system from scratch because what ended up being important about that is that to your point, it's actually a very, like compared to like a, you know, if you're like running cursor on anyone's machine, you kind of don't know what you're dealing with, with the OS you're running on. There could be an error happens. It could be like a million different things, right? There could be some config. There could be, it could be God knows what, right? The thing with WebConnect is because we wrote the entire thing from scratch. It's actually a unified image basically. And we can instrument it at any level that we think is going to be useful, which is exactly what we did when we started building Bolt is we instrumented stuff at like the process level, at the runtime level, you know, et cetera, et cetera, et cetera. Stuff that would just be not impossible to do on local, but to do that in a way that works across any operating system, whatever is, I mean, would just be insanely, you know, insanely difficult to do right and reliably. And that's what you saw when you've used Bolt is that when an error actually will occur, whether it's in the build process or the actual web application itself is failing or anything kind of in between, you can actually capture those errors. And today it's a very primitive way of how we've implemented it largely because the product just didn't exist 90 days ago. So we're like, we got some work ahead of us and we got to hire some more a little bit, but basically we present and we say, Hey, this is, here's kind of the things that went wrong. There's a fix it button and then a ignore button, and then you can just hit fix it. And then we take all that telemetry through our agent, you run it through our agent and say, kind of, here's the state of the application. Here's kind of the errors that we got from Node.js or the browser or whatever, and like dah, dah, dah, dah. And it can take a crack at actually solving it. And it's actually pretty darn good at being able to do that. That's kind of been a, you know, closing the loop and having it be a reliable kind of base has seemed to be a pretty big upgrade over doing stuff locally, just because I think that's a pretty key ingredient of it. And yeah, I think breaking things down into smaller tasks, like that's, that's kind of a key part of our agent. I think like Claude did a really good job with artifacts. I think, you know, us and kind of everyone else has, has kind of taken their approach of like actually breaking out certain tasks in a certain order into, you know, kind of a concrete way. And, and so actually the core of Bolt, I know we actually made open source. So you can actually go and check out like the system prompts and et cetera, and you can run it locally and whatever have you. So anyone that's interested in this stuff, I'd highly recommend taking a look at. There's not a lot of like stuff that's like open source in this realm. It's, that was one of the fun things that we've we thought would be cool to do. And people, people seem to like it. I mean, there's a lot of forks and people adding different models and stuff. So it's been cool to see.Swyx [00:30:41]: Yeah. I'm happy to add, I added real-time voice for my opening day demo and it was really fun to hack with. So thank you for doing that. Yeah. Thank you. I'm going to steal your code.Eric [00:30:52]: Because I want that.Swyx [00:30:52]: It's funny because I built on top of the fork of Bolt.new that already has the multi LLM thing. And so you just told me you're going to merge that in. So then you're going to merge two layers of forks down into this thing. So it'll be fun.Eric [00:31:03]: Heck yeah.Alessio [00:31:04]: Just to touch on like the environment, Itamar, you maybe go into the most complicated environments that even the people that work there don't know how to run. How much of an impact does that have on your performance? Like, you know, it's most of the work you're doing actually figuring out environment and like the libraries, because I'm sure they're using outdated version of languages, they're using outdated libraries, they're using forks that have not been on the public internet before. How much of the work that you're doing is like there versus like at the LLM level?Itamar [00:31:32]: One of the reasons I was asking about, you know, what are the steps to break things down, because it really matters. Like, what's the tech stack? How complicated the software is? It's hard to figure it out when you're dealing with the real world, any environment of enterprise as a city, when I'm like, while maybe sometimes like, I think you do enable like in Bolt, like to install stuff, but it's quite a like controlled environment. And that's a good thing to do, because then you narrow down and it's easier to make things work. So definitely, there are two dimensions, I think, actually spaces. One is the fact just like installing our software without yet like doing anything, making it work, just installing it because we work with enterprise and Fortune 500, etc. Many of them want on prem solution.Swyx [00:32:22]: So you have how many deployment options?Itamar [00:32:24]: Basically, we had, we did a metric metrics, say 96 options, because, you know, they're different dimensions. Like, for example, one dimension, we connect to your code management system to your Git. So are you having like GitHub, GitLab? Subversion? Is it like on cloud or deployed on prem? Just an example. Which model agree to use its APIs or ours? Like we have our Is it TestGPT? Yeah, when we started with TestGPT, it was a huge mistake name. It was cool back then, but I don't think it's a good idea to name a model after someone else's model. Anyway, that's my opinion. So we gotSwyx [00:33:02]: I'm interested in these learnings, like things that you change your mind on.Itamar [00:33:06]: Eventually, when you're building a company, you're building a brand and you want to create your own brand. By the way, when I thought about Bolt.new, I also thought about if it's not a problem, because when I think about Bolt, I do think about like a couple of companies that are already called this way.Swyx [00:33:19]: Curse companies. You could call it Codium just to...Itamar [00:33:24]: Okay, thank you. Touche. Touche.Eric [00:33:27]: Yeah, you got to imagine the board meeting before we launched Bolt, one of our investors, you can imagine they're like, are you sure? Because from the investment side, it's kind of a famous, very notorious Bolt. And they're like, are you sure you want to go with that name? Oh, yeah. Yeah, absolutely.Itamar [00:33:43]: At this point, we have actually four models. There is a model for autocomplete. There's a model for the chat. There is a model dedicated for more for code review. And there is a model that is for code embedding. Actually, you might notice that there isn't a good code embedding model out there. Can you name one? Like dedicated for code?Swyx [00:34:04]: There's code indexing, and then you can do sort of like the hide for code. And then you can embed the descriptions of the code.Itamar [00:34:12]: Yeah, but you do see a lot of type of models that are dedicated for embedding and for different spaces, different fields, etc. And I'm not aware. And I know that if you go to the bedrock, try to find like there's a few code embedding models, but none of them are specialized for code.Swyx [00:34:31]: Is there a benchmark that you would tell us to pay attention to?Itamar [00:34:34]: Yeah, so it's coming. Wait for that. Anyway, we have our models. And just to go back to the 96 option of deployment. So I'm closing the brackets for us. So one is like dimensional, like what Git deployment you have, like what models do you agree to use? Dotter could be like if it's air-gapped completely, or you want VPC, and then you have Azure, GCP, and AWS, which is different. Do you use Kubernetes or do not? Because we want to exploit that. There are companies that do not do that, etc. I guess you know what I mean. So that's one thing. And considering that we are dealing with one of all four enterprises, we needed to deal with that. So you asked me about how complicated it is to solve that complex code. I said, it's just a deployment part. And then now to the software, we see a lot of different challenges. For example, some companies, they did actually a good job to build a lot of microservices. Let's not get to if it's good or not, but let's first assume that it is a good thing. A lot of microservices, each one of them has their own repo. And now you have tens of thousands of repos. And you as a developer want to develop something. And I remember me coming to a corporate for the first time. I don't know where to look at, like where to find things. So just doing a good indexing for that is like a challenge. And moreover, the regular indexing, the one that you can find, we wrote a few blogs on that. By the way, we also have some open source, different than yours, but actually three and growing. Then it doesn't work. You need to let the tech leads and the companies influence your indexing. For example, Mark with different repos with different colors. This is a high quality repo. This is a lower quality repo. This is a repo that we want to deprecate. This is a repo we want to grow, etc. And let that be part of your indexing. And only then things actually work for enterprise and they don't get to a fatigue of, oh, this is awesome. Oh, but I'm starting, it's annoying me. I think Copilot is an amazing tool, but I'm quoting others, meaning GitHub Copilot, that they see not so good retention of GitHub Copilot and enterprise. Ooh, spicy. Yeah. I saw snapshots of people and we have customers that are Copilot users as well. And also I saw research, some of them is public by the way, between 38 to 50% retention for users using Copilot and enterprise. So it's not so good. By the way, I don't think it's that bad, but it's not so good. So I think that's a reason because, yeah, it helps you auto-complete, but then, and especially if you're working on your repo alone, but if it's need that context of remote repos that you're code-based, that's hard. So to make things work, there's a lot of work on that, like giving the controllability for the tech leads, for the developer platform or developer experience department in the organization to influence how things are working. A short example, because if you have like really old legacy code, probably some of it is not so good anymore. If you just fine tune on these code base, then there is a bias to repeat those mistakes or old practices, etc. So you need, for example, as I mentioned, to influence that. For example, in Coda, you can have a markdown of best practices by the tech leads and Coda will include that and relate to that and will not offer suggestions that are not according to the best practices, just as an example. So that's just a short list of things that you need to do in order to deal with, like you mentioned, the 100.1 to 100.2 version of software. I just want to say what you're doing is extremelyEric [00:38:32]: impressive because it's very difficult. I mean, the business of Stackplus, kind of before bulk came online, we sold a version of our IDE that went on-prem. So I understand what you're saying about the difficulty of getting stuff just working on-prem. Holy heck. I mean, that is extremely hard. I guess the question I have for you is, I mean, we were just doing that with kind of Kubernetes-based stuff, but the spread of Fortune 500 companies that you're working with, how are they doing the inference for this? Are you kind of plugging into Azure's OpenAI stuff and AWS's Bedrock, you know, Cloud stuff? Or are they just like running stuff on GPUs? Like, what is that? How are these folks approaching that? Because, man, what we saw on the enterprise side, I mean, I got to imagine that that's a huge challenge. Everything you said and more, like,Itamar [00:39:15]: for example, like someone could be, and I don't think any of these is bad. Like, they made their decision. Like, for example, some people, they're, I want only AWS and VPC on AWS, no matter what. And then they, some of them, like there is a subset, I will say, I'm willing to take models only for from Bedrock and not ours. And we have a problem because there is no good code embedding model on Bedrock. And that's part of what we're doing now with AWS to solve that. We solve it in a different way. But if you are willing to run on AWS VPC, but run your run models on GPUs or inferentia, like the new version of the more coming out, then our models can run on that. But everything you said is right. Like, we see like on-prem deployment where they have their own GPUs. We see Azure where you're using OpenAI Azure. We see cases where you're running on GCP and they want OpenAI. Like this cross, like a case, although there is Gemini or even Sonnet, I think is available on GCP, just an example. So all the options, that's part of the challenge. I admit that we thought about it, but it was even more complicated. And it took us a few months to actually, that metrics that I mentioned, to start clicking each one of the blocks there. A few months is impressive. I mean,Eric [00:40:35]: honestly, just that's okay. Every one of these enterprises is, their networking is different. Just everything's different. Every single one is different. I see you understand. Yeah. So that just cannot be understated. That it is, that's extremely impressive. Hats off.Itamar [00:40:50]: It could be, by the way, like, for example, oh, we're only AWS, but our GitHub enterprise is on-prem. Oh, we forgot. So we need like a private link or whatever, like every time like that. It's not, and you do need to think about it if you want to work with an enterprise. And it's important. Like I understand like their, I respect their point of view.Swyx [00:41:10]: And this primarily impacts your architecture, your tech choices. Like you have to, you can't choose some vendors because...Itamar [00:41:15]: Yeah, definitely. To be frank, it makes us hard for a startup because it means that we want, we want everyone to enjoy all the variety of models. By the way, it was hard for us with our technology. I want to open a bracket, like a window. I guess you're familiar with our Alpha Codium, which is an open source.Eric [00:41:33]: We got to go over that. Yeah. So I'll do that quickly.Itamar [00:41:36]: Yeah. A pin in that. Yeah. Actually, we didn't have it in the last episode. So, so, okay.Swyx [00:41:41]: Okay. We'll come back to that later, but let's talk about...Itamar [00:41:43]: Yeah. So, so just like shortly, and then we can double click on Alpha Codium. But Alpha Codium is a open source tool. You can go and try it and lets you compete on CodeForce. This is a website and a competition and actually reach a master level level, like 95% with a click of a button. You don't need to do anything. And part of what we did there is taking a problem and breaking it to different, like smaller blocks. And then the models are doing a much better job. Like we all know it by now that taking small tasks and solving them, by the way, even O1, which is supposed to be able to do system two thinking like Greg from OpenAI like hinted, is doing better on these kinds of problems. But still, it's very useful to break it down for O1, despite O1 being able to think by itself. And that's what we presented like just a month ago, OpenAI released that now they are doing 93 percentile with O1 IOI left and International Olympiad of Formation. Sorry, I forgot. Exactly. I told you I forgot. And we took their O1 preview with Alpha Codium and did better. Like it just shows like, and there is a big difference between the preview and the IOI. It shows like that these models are not still system two thinkers, and there is a big difference. So maybe they're not complete system two. Yeah, they need some guidance. I call them system 1.5. We can, we can have it. I thought about it. Like, you know, I care about this philosophy stuff. And I think like we didn't see it even close to a system two thinking. I can elaborate later. But closing the brackets, like we take Alpha Codium and as our principle of thinking, we take tasks and break them down to smaller tasks. And then we want to exploit the best model to solve them. So I want to enable anyone to enjoy O1 and SONET and Gemini 1.5, etc. But at the same time, I need to develop my own models as well, because some of the Fortune 500 want to have all air gapped or whatever. So that's a challenge. Now you need to support so many models. And to some extent, I would say that the flow engineering, the breaking down to two different blocks is a necessity for us. Why? Because when you take a big block, a big problem, you need a very different prompt for each one of the models to actually work. But when you take a big problem and break it into small tasks, we can talk how we do that, then the prompt matters less. What I want to say, like all this, like as a startup trying to do different deployment, getting all the juice that you can get from models, etc. is a big problem. And one need to think about it. And one of our mitigation is that process of taking tasks and breaking them down. That's why I'm really interested to know how you guys are doing it. And part of what we do is also open source. So you can see.Swyx [00:44:39]: There's a lot in there. But yeah, flow over prompt. I do believe that that does make sense. I feel like there's a lot that both of you can sort of exchange notes on breaking down problems. And I just want you guys to just go for it. This is fun to watch.Eric [00:44:55]: Yeah. I mean, what's super interesting is the context you're working in is, because for us too with Bolt, we've started thinking because our kind of existing business line was going behind the firewall, right? We were like, how do we do this? Adding the inference aspect on, we're like, okay, how does... Because I mean, there's not a lot of prior art, right? I mean, this is all new. This is all new. So I definitely am going to have a lot of questions for you.Itamar [00:45:17]: I'm here. We're very open, by the way. We have a paper on a blog or like whatever.Swyx [00:45:22]: The Alphacodeum, GitHub, and we'll put all this in the show notes.Itamar [00:45:25]: Yeah. And even the new results of O1, we published it.Eric [00:45:29]: I love that. And I also just, I think spiritually, I like your approach of being transparent. Because I think there's a lot of hype-ium around AI stuff. And a lot of it is, it's just like, you have these companies that are just kind of keep their stuff closed source and then just max hype it, but then it's kind of nothing. And I think it kind of gives a bad rep to the incredible stuff that's actually happening here. And so I think it's stuff like what you're doing where, I mean, true merit and you're cracking open actual code for others to learn from and use. That strikes me as the right approach. And it's great to hear that you're making such incredible progress.Itamar [00:46:02]: I have something to share about the open source. Most of our tools are, we have an open source version and then a premium pro version. But it's not an easy decision to do that. I actually wanted to ask you about your strategy, but I think in your case, there is, in my opinion, relatively a good strategy where a lot of parts of open source, but then you have the deployment and the environment, which is not right if I get it correctly. And then there's a clear, almost hugging face model. Yeah, you can do that, but why should you try to deploy it yourself, deploy it with us? But in our case, and I'm not sure you're not going to hit also some competitors, and I guess you are. I wanted to ask you, for example, on some of them. In our case, one day we looked on one of our competitors that is doing code review. We're a platform. We have the code review, the testing, et cetera, spread over the ID to get. And in each agent, we have a few startups or a big incumbents that are doing only that. So we noticed one of our competitors having not only a very similar UI of our open source, but actually even our typo. And you sit there and you're kind of like, yeah, we're not that good. We don't use enough Grammarly or whatever. And we had a couple of these and we saw it there. And then it's a challenge. And I want to ask you, Bald is doing so well, and then you open source it. So I think I know what my answer was. I gave it before, but still interestingEric [00:47:29]: to hear what you think. GeoHot said back, I don't know who he was up to at this exact moment, but I think on comma AI, all that stuff's open source. And someone had asked him, why is this open source? And he's like, if you're not actually confident that you can go and crush it and build the best thing, then yeah, you should probably keep your stuff closed source. He said something akin to that. I'm probably kind of butchering it, but I thought it was kind of a really good point. And that's not to say that you should just open source everything, because for obvious reasons, there's kind of strategic things you have to kind of take in mind. But I actually think a pretty liberal approach, as liberal as you kind of can be, it can really make a lot of sense. Because that is so validating that one of your competitors is taking your stuff and they're like, yeah, let's just kind of tweak the styles. I mean, clearly, right? I think it's kind of healthy because it keeps, I'm sure back at HQ that day when you saw that, you're like, oh, all right, well, we have to grind even harder to make sure we stay ahead. And so I think it's actually a very useful, motivating thing for the teams. Because you might feel this period of comfort. I think a lot of companies will have this period of comfort where they're not feeling the competition and one day they get disrupted. So kind of putting stuff out there and letting people push it forces you to face reality soon, right? And actually feel that incrementally so you can kind of adjust course. And that's for us, the open source version of Bolt has had a lot of features people have been begging us for, like persisting chat messages and checkpoints and stuff. Within the first week, that stuff was landed in the open source versions. And they're like, why can't you ship this? It's in the open, so people have forked it. And we're like, we're trying to keep our servers and GPUs online. But it's been great because the folks in the community did a great job, kept us on our toes. And we've got to know most of these folks too at this point that have been building these things. And so it actually was very instructive. Like, okay, well, if we're going to go kind of land this, there's some UX patterns we can kind of look at and the code is open source to this stuff. What's great about these, what's not. So anyways, NetNet, I think it's awesome. I think from a competitive point of view for us, I think in particular, what's interesting is the core technology of WebContainer going. And I think that right now, there's really nothing that's kind of on par with that. And we also, we have a business of, because WebContainer runs in your browser, but to make it work, you have to install stuff from NPM. You have to make cores bypass requests, like connected databases, which all require server-side proxying or acceleration. And so we actually sell WebContainer as a service. One of the core reasons we open-sourced kind of the core components of Bolt when we launched was that we think that there's going to be a lot more of these AI, in-your-browser AI co-gen experiences, kind of like what Anthropic did with Artifacts and Clod. By the way, Artifacts uses WebContainers. Not yet. No, yeah. Should I strike that? I think that they've got their own thing at the moment, but there's been a lot of interest in WebContainers from folks doing things in that sort of realm and in the AI labs and startups and everything in between. So I think there'll be, I imagine, over the coming months, there'll be lots of things being announced to folks kind of adopting it. But yeah, I think effectively...Swyx [00:50:35]: Okay, I'll say this. If you're a large model lab and you want to build sandbox environments inside of your chat app, you should call Eric.Itamar [00:50:43]: But wait, wait, wait, wait, wait, wait. I have a question about that. I think OpenAI, they felt that people are not using their model as they would want to. So they built ChatGPT. But I would say that ChatGPT now defines OpenAI. I know they're doing a lot of business from their APIs, but still, is this how you think? Isn't Bolt.new your business now? Why don't you focus on that instead of the...Swyx [00:51:16]: What's your advice as a founder?Eric [00:51:18]: You're right. And so going into it, we, candidly, we were like, Bolt.new, this thing is super cool. We think people are stoked. We think people will be stoked. But we were like, maybe that's allowed. Best case scenario, after month one, we'd be mind blown if we added a couple hundred K of error or something. And we were like, but we think there's probably going to be an immediate huge business. Because there was some early poll on folks wanting to put WebContainer into their product offerings, kind of similar to what Bolt is doing or whatever. We were actually prepared for the inverse outcome here. But I mean, well, I guess we've seen poll on both. But I mean, what's happened with Bolt, and you're right, it's actually the same strategy as like OpenAI or Anthropic, where we have our ChatGPT to OpenAI's APIs is Bolt to WebContainer. And so we've kind of taken that same approach. And we're seeing, I guess, some of the similar results, except right now, the revenue side is extremely lopsided to Bolt.Itamar [00:52:16]: I think if you ask me what's my advice, I think you have three options. One is to focus on Bolt. The other is to focus on the WebContainer. The third is to raise one billion dollars and do them both. I'm serious. I think otherwise, you need to choose. And if you raise enough money, and I think it's big bucks, because you're going to be chased by competitors. And I think it will be challenging to do both. And maybe you can. I don't know. We do see these numbers right now, raising above $100 million, even without havingEric [00:52:49]: a product. You can see these. It's excellent advice. And I think what's been amazing, but also kind of challenging is we're trying to forecast, okay, well, where are these things going? I mean, in the initial weeks, I think us and all the investors in the company that we're sharing this with, it was like, this is cool. Okay, we added 500k. Wow, that's crazy. Wow, we're at a million now. Most things, you have this kind of the tech crunch launch of initiation and then the thing of sorrow. And if there's going to be a downtrend, it's just not coming yet. Now that we're kind of looking ahead, we're six weeks in. So now we're getting enough confidence in our convictions to go, okay, this se

Tell Me Something Funny: The election gutted millions, including Clod and me. In a future episode, we will grapple with this devastation. For now, we share this mostly lighthearted episode with the hope that it will brighten your day. Link to the music video by Dead Gowns ! : https://www.youtube.com/watch?v=9VmAMtomS_A More Secrets:⁠⁠ www.mymothersdiaries.com⁠⁠ Shop: ⁠www.mymothersdiaries.com/mymotherscloset⁠ Listen: https://www.mymothersdiaries.com/mymotherspodcastFollow Us! Instagram: ⁠https://www.instagram.com/mymothersdiaries/ TikTok: ⁠https://www.tiktok.com/@mymothersdiaries Facebook: ⁠https://www.facebook.com/mymothersdiaries Thank you to Dead Gowns for our intro song! Listen to Kid 1 by Dead Gowns: https://www.deadgowns.com/

What's this? What's this? Thatch isn't here this week. What's this? It is a bit unique. What's this? I can't believe my ears it's Clod and Jushi and it's Bo! What's this?Mailbag Question: What's your favorite scary parts of Pokemon? puclpodcast@gmail.comPUCL Survey Link: https://docs.google.com/forms/d/e/1FAIpQLSd7LPj9YErBGUx5GO2lSTWVAjmSL_IDLc8DItkxkaAVyCLhmA/viewform?usp=sf_linkThatch's Referral Code for PoGo: 9THMRXDP7Timestamps:Intro: 0:00:00News: 0:10:19Quiz: 0:22:49Topic: 0:44:39Pokemon of the Episode: 1:11:09Mailbag: 1:17:11Use Code PUCLPOD5 at trollandtoad.com for 5% off and support the show!Don't forget to like us on Facebook, follow us on Twitter, follow us on Tumblr, and most importantly Review us on iTunes!Check us out on Discord!http://pucldiscord.comTwitch: twitch.tv/thepuclpodcast Support PUCL by donating to our Patreon Hosted on Acast. See acast.com/privacy for more information.

Hard to believe, but Clod, the biggest clown I know, claims she was never into Halloween. Not as a child, not as a parent and not as a teacher… Yet in this episode she does tell several nostalgic wacky Halloween tales and I add my share of far-out, creepy tales too. More Secrets:⁠⁠ www.mymothersdiaries.com⁠⁠ Shop: ⁠www.mymothersdiaries.com/mymotherscloset⁠ Listen: https://www.mymothersdiaries.com/mymotherspodcastFollow Us! Instagram: ⁠https://www.instagram.com/mymothersdiaries/ TikTok: ⁠https://www.tiktok.com/@mymothersdiaries Facebook: ⁠https://www.facebook.com/mymothersdiaries Thank you to Dead Gowns for our intro song! Listen to Kid 1 by Dead Gowns: https://www.deadgowns.com/

“Your Time Has Expired ” the automated voice chimed as Clod and Hilary left the condominium. Overdue for a podcast, they took the voice as a sign, ditched their beach walking plans, found a picnic table, and pondered life's great mysteries. More Secrets:⁠⁠ www.mymothersdiaries.com⁠⁠ Shop: ⁠www.mymothersdiaries.com/mymotherscloset⁠ Listen: https://www.mymothersdiaries.com/mymotherspodcastFollow Us! Instagram: ⁠https://www.instagram.com/mymothersdiaries/ TikTok: ⁠https://www.tiktok.com/@mymothersdiaries Facebook: ⁠https://www.facebook.com/mymothersdiaries Thank you to Dead Gowns for our intro song! Listen to Kid 1 by Dead Gowns: https://www.deadgowns.com/

We like to mark every 25th episode of the podcast with some sort of special theme or format, and so on this episode we're taking up the hefty topic of to what degree goth is a subculture tied to music. Grab your snakebite and Aquanet and expect gatekeeping, gateletting, takes spicy and mild, and no small amount of cattiness. We're also talking about the passing of Roli Mossiman, the news of North American And One dates, and a Devours gig.

Two weeks ago, Clod and Hilary went to Broadway and landed on The Today Show. Seeing Cole Escola's Oh, Mary! was the best thing ever (indescribably brilliant and hysterically funny). Seeing and hearing ourselves on the Today Show Jumbotron? Not so much, but at least we walked away with Al's head on a stick. More Secrets:⁠⁠ www.mymothersdiaries.com⁠⁠ Shop: ⁠www.mymothersdiaries.com/mymotherscloset⁠ Listen: ⁠https://www.mymothersdiaries.com/mymotherspodcast Follow Us! Instagram: ⁠ https://www.instagram.com/mymothersdiaries/ TikTok: ⁠ https://www.tiktok.com/@mymothersdiaries Facebook: ⁠ https://www.facebook.com/mymothersdiaries Thank you to Dead Gowns for our intro song! Listen to Kid 1 by Dead Gowns: https://www.deadgowns.com/

Last week Clod fell, dislocated her finger, and nearly rolled into the river. If that's too serious for you, hang in for the last third of this episode when Clod accidentally swears as she reads entries set in Portland, Maine's Burger King circa 1970s. More Secrets:⁠⁠ www.mymothersdiaries.com⁠⁠ Shop: ⁠www.mymothersdiaries.com/mymotherscloset⁠ Listen: ⁠https://www.mymothersdiaries.com/mymotherspodcast Follow Us! Instagram: ⁠ https://www.instagram.com/mymothersdiaries/ TikTok: ⁠ https://www.tiktok.com/@mymothersdiaries Facebook: ⁠ https://www.facebook.com/mymothersdiaries Thank you to Dead Gowns for our intro song! Listen to Kid 1 by Dead Gowns: https://www.deadgowns.com/

According to her astrologer, Hilary found fame in past lives and she thinks she's finding it in this life. too. Clod is dubious until Hilary recounts tale after tale of celebrity connections – and missed opportunities – some involving VERY famous people. Clod chimes in with her share of B list celebrity meet-ups, starting with Fabian (who Hilary mistook for Fabio). More Secrets:⁠⁠ www.mymothersdiaries.com⁠⁠ Shop: ⁠www.mymothersdiaries.com/mymotherscloset⁠ Listen: ⁠https://www.mymothersdiaries.com/mymotherspodcast Follow Us! Instagram: ⁠ https://www.instagram.com/mymothersdiaries/ TikTok: ⁠ https://www.tiktok.com/@mymothersdiaries Facebook: ⁠ https://www.facebook.com/mymothersdiaries Thank you to Dead Gowns for our intro song! Listen to Kid 1 by Dead Gowns: https://www.deadgowns.com/

Podcast for a deep examination into the career and life choices of Adam Sandler, Dwayne 'The Rock' Johnson, Julia Roberts, Jack Nicholson, Whoopi Goldberg, Eddie Murphy, & Jim Carrey. In this first edition of "Pod People," Patrick interviews Grant Keller and Dimitri Keogh about their descent into madness (i.e. the podcast they record about minor Pixar characters). Should you give it a listen? Find out on this week's episode of 'What the Hell Happened to Them?' Email the cast at whathappenedtothem@gmail.com Disclaimer: This episode was recorded in July 2024. References may feel confusing and/or dated unusually quickly.   Artwork from BJ West   quixotic, united, skeyhill, vekeman, nicholson, sandler, roberts, rock, johnson, whoopi, goldberg, carrey, murphy, keller, keogh, clod, sox, pixar, elemental, lightyear

Although Sherlock Holmes does appear in this episode, really the only mystery is how Clod and Hilary have found themselves in the midst of so many antics. Here are some "clueless clues" from the episode: a fan encounter, a miniature PeeWee Herman, a day of animal run-ins, you the get drift. Enjoy! More Secrets:⁠⁠ www.mymothersdiaries.com⁠⁠ Shop: ⁠www.mymothersdiaries.com/mymotherscloset⁠ Listen: ⁠https://www.mymothersdiaries.com/mymotherspodcast Follow Us! Instagram: ⁠ https://www.instagram.com/mymothersdiaries/ TikTok: ⁠ https://www.tiktok.com/@mymothersdiaries Facebook: ⁠ https://www.facebook.com/mymothersdiaries Thank you to Dead Gowns for our intro song! Listen to Kid 1 by Dead Gowns: https://www.deadgowns.com/

In the 70s Clod and her sister Lorna fell for singer songwriter John Davidson when they saw him perform in Maine. Lorna, even more than Clod, fell in love with his talent and charm and, yes, his dimples. In what still seems unbelievable to these sisters, they've been lucky enough to see their idol perform several times in recent years, including just last week, which means, of course, they have funny tales to tell! More Secrets:⁠⁠ www.mymothersdiaries.com⁠⁠ Shop: ⁠www.mymothersdiaries.com/mymotherscloset⁠ Listen: ⁠https://www.mymothersdiaries.com/mymotherspodcast Follow Us! Instagram: ⁠ https://www.instagram.com/mymothersdiaries/ TikTok: ⁠ https://www.tiktok.com/@mymothersdiaries Facebook: ⁠ https://www.facebook.com/mymothersdiaries Thank you to Dead Gowns for our intro song! Listen to Kid 1 by Dead Gowns: https://www.deadgowns.com/

Thatch is joined by Sublimemanic and Clod 9 to talk about nuzlockes and why they like them and how they play them.Mailbag Question: What are some of your nuzlocke stories? puclpodcast@gmail.comPUCL Survey Link: https://docs.google.com/forms/d/e/1FAIpQLSd7LPj9YErBGUx5GO2lSTWVAjmSL_IDLc8DItkxkaAVyCLhmA/viewform?usp=sf_linkThatch's Referral Code for PoGo: 9THMRXDP7Timestamps:Intro: 0:00:00News: 0:12:23Quiz: 0:22:27Topic: 0:35:51Pokemon of the Episode: 0:58:55Mailbag: 1:08:30Use Code PUCLPOD5 at trollandtoad.com for 5% off and support the show!Don't forget to like us on Facebook, follow us on Twitter, follow us on Tumblr, and most importantly Review us on iTunes!Check us out on Discord!https://pucldiscord.comTwitch: twitch.tv/thepuclpodcast Support PUCL by donating to our Patreon Hosted on Acast. See acast.com/privacy for more information.

In this episode, Clod and Hilary are inspired to tell stories about shopping carts. Yes, shopping carts. Episode themes can be inspired by anything...truly anything. Naturally, the conversation does not stay on theme and Clod learns the meaning of a Luna Moth. Enjoy! More Secrets:⁠⁠ www.mymothersdiaries.com⁠⁠ Shop: ⁠www.mymothersdiaries.com/mymotherscloset⁠ Listen: ⁠https://www.mymothersdiaries.com/mymotherspodcast Follow Us! Instagram: ⁠ https://www.instagram.com/mymothersdiaries/ TikTok: ⁠ https://www.tiktok.com/@mymothersdiaries Facebook: ⁠ https://www.facebook.com/mymothersdiaries Thank you to Dead Gowns for our intro song! Listen to Kid 1 by Dead Gowns: https://www.deadgowns.com/

Clod and Hilary share a knack for missing – or misconstruing – the obvious. In this episode they share big and little moments where being oblivious has led to plenty of laughs and unexpected endings. More Secrets:⁠⁠ www.mymothersdiaries.com⁠⁠ Shop: ⁠www.mymothersdiaries.com/mymotherscloset⁠ Listen: ⁠https://www.mymothersdiaries.com/mymotherspodcast Follow Us! Instagram: ⁠ https://www.instagram.com/mymothersdiaries/ TikTok: ⁠ https://www.tiktok.com/@mymothersdiaries Facebook: ⁠ https://www.facebook.com/mymothersdiaries Thank you to Dead Gowns for our intro song! Listen to Kid 1 by Dead Gowns: https://www.deadgowns.com/

In this episode, Clod and Hilary regale each other with athletic mishaps and other foolish moments. More Secrets:⁠⁠ www.mymothersdiaries.com⁠⁠ Shop: ⁠www.mymothersdiaries.com/mymotherscloset⁠ Listen: ⁠https://www.mymothersdiaries.com/mymotherspodcast Follow Us! Instagram: ⁠ https://www.instagram.com/mymothersdiaries/ TikTok: ⁠ https://www.tiktok.com/@mymothersdiaries Facebook: ⁠ https://www.facebook.com/mymothersdiaries Thank you to Dead Gowns for our intro song! Listen to Kid 1 by Dead Gowns: https://www.deadgowns.com/

Lots of stuff happening in this episode: Hilary shares her newly-discovered diaries, Clod realizes (three decades later) that Hilary's ADHD led to using Flat Stanley as a coping mechanism, Clod confesses that her recently published micro-story, which she thought was true, was not. And Hilary learns a new vocabulary word: Penknife. More Secrets:⁠⁠ www.mymothersdiaries.com⁠⁠ Shop: ⁠www.mymothersdiaries.com/mymotherscloset⁠ Listen: ⁠https://www.mymothersdiaries.com/mymotherspodcast Follow Us! Instagram: ⁠ https://www.instagram.com/mymothersdiaries/ TikTok: ⁠ https://www.tiktok.com/@mymothersdiaries Facebook: ⁠ https://www.facebook.com/mymothersdiaries Thank you to Dead Gowns for our new intro song! Listen to Kid 1 by Dead Gowns: https://www.deadgowns.com/

Will and Anurag discuss new releases by Waxahatchee, Oort Clod, and Drahla, plus live reports and bonus songs.

Thatch is joined this week by R. Sigma and Clod 9 to discuss the worst pokemon moves in each generation!Mailbag Question: What do you think the worst move in Pokemon is? puclpodcast@gmail.comPUCL Survey Link: https://docs.google.com/forms/d/e/1FAIpQLSd7LPj9YErBGUx5GO2lSTWVAjmSL_IDLc8DItkxkaAVyCLhmA/viewform?usp=sf_linkThatch's Referral Code for PoGo: 9THMRXDP7Timestamps:Intro: 0:00:00News: 0:12:49Quiz: 0:21:46Topic: 0:32:37Pokemon of the Episode: 1:02:22Mailbag: 1:10:04Use Code PUCLPOD5 at trollandtoad.com for 5% off and support the show!Don't forget to like us on Facebook, follow us on Twitter, follow us on Tumblr, and most importantly Review us on iTunes!Check us out on Discord!https://pucldiscord.comTwitch: twitch.tv/thepuclpodcast Support PUCL by donating to our Patreon Hosted on Acast. See acast.com/privacy for more information.

www.iservalan.comwww.taletellerclub.comHome of great lyrics#taltellerlyrics

Welcome to Episode Four of Season Two where Clod, my Aunt Lorna, and I continue to share wacky, memorable experiences    The title comes from  the closing of one of Clod's letters to her sister. More Secrets:⁠⁠ www.mymothersdiaries.com⁠⁠ Shop: ⁠www.mymothersdiaries.com/mymotherscloset⁠ Listen: ⁠https://www.mymothersdiaries.com/mymotherspodcast Follow Us! Instagram: ⁠ https://www.instagram.com/mymothersdiaries/ TikTok: ⁠ https://www.tiktok.com/@mymothersdiaries Facebook: ⁠ https://www.facebook.com/mymothersdiaries Thank you to Dead Gowns for our new intro song! Listen to Kid 1 by Dead Gowns: https://www.deadgowns.com/

It's Episode 3 of Season 2, and we're excited to host our first guest, Clod's younger sister: Lorna. The episode, which we're calling The Only Normal Child because that's how Clod's father – who was dead serious – once referred to Lorna in the his 70s diary. Clod and Aunt Lorna reminisce about working together, sometimes dating the same boys, a little sibling rivalry and the fun they had… More Secrets:⁠⁠ www.mymothersdiaries.com⁠⁠ Shop: ⁠www.mymothersdiaries.com/mymotherscloset⁠ Listen: ⁠https://www.mymothersdiaries.com/mymotherspodcast Follow Us! Instagram: ⁠ https://www.instagram.com/mymothersdiaries/ TikTok: ⁠ https://www.tiktok.com/@mymothersdiaries Facebook: ⁠ https://www.facebook.com/mymothersdiaries Thank you to Dead Gowns for our new intro song! Listen to Kid 1 by Dead Gowns: https://www.deadgowns.com/

Thatch is stuck at the airport, so Clod, Sharkfinnegan, and the Fluffiest Whimsicott take over to talk about their pokemon day predictions!What are you rPokemon Day Predictions? What did you think of the Pokemon Day announcements? puclpodcast@gmail.comPUCL Survey Link: https://docs.google.com/forms/d/e/1FAIpQLSd7LPj9YErBGUx5GO2lSTWVAjmSL_IDLc8DItkxkaAVyCLhmA/viewform?usp=sf_linkThatch's Referral Code for PoGo: 9THMRXDP7Timestamps:Intro: 0:00:00News: 0:10:04Quiz: 0:17:29Topic: 0:38:33Pokemon of the Episode: 1:09:17Mailbag: 1:17:18Use Code PUCLPOD5 at trollandtoad.com for 5% off and support the show!Don't forget to like us on Facebook, follow us on Twitter, follow us on Tumblr, and most importantly Review us on iTunes!Check us out on Discord!https://pucldiscord.comTwitch: twitch.tv/thepuclpodcast Support PUCL by donating to our Patreon Hosted on Acast. See acast.com/privacy for more information.

In Episode 3, Why Would I Say That? Clod admits she's long had a big mouth and some bad habits, but insists she was a “square.” Hilary shares some zany adventures which prove she was definitely not a square. More Secrets:⁠⁠ www.mymothersdiaries.com⁠⁠ Shop: ⁠www.mymothersdiaries.com/mymotherscloset⁠ Listen: ⁠https://www.mymothersdiaries.com/mymotherspodcast Follow Us! Instagram: ⁠ https://www.instagram.com/mymothersdiaries/ TikTok: ⁠ https://www.tiktok.com/@mymothersdiaries Facebook: ⁠ https://www.facebook.com/mymothersdiaries Thank you to Dead Gowns for our new intro song! Listen to Kid 1 by Dead Gowns: https://www.deadgowns.com/

Voici le 8ème épisode du BOXON CREATIF !Quel est cet appel à l'aventure et pourquoi l'aventure nous appelle-t-elle ? Avons-nous d'ailleurs besoin de voyager pour y répondre ? Cela part bien souvent d'une question. Une question très personnelle. Une question qui touche à la petite flamme qui sommeille en nous. Et si cette question n'amenait pas de réponse ?Dans cet épisode exceptionnel de 15 minutes, Laurent fait des digressions sur les sujets suivants :- la force mystérieuse de l'appel de l'aventure- la dualité qui relie l'appel à la réponse- pourquoi La Légende de Zelda peut nous éclairer grâce à la Triforce- la théorie du tabouret à trois pieds- pourquoi il est inutile de réinventer la roue- le concept du monomythe- le mantra du premier pas qui compte- les bénéfices de ce mantra- pourquoi et comment embrasser son kokoro- la métaphore de TotoroNOTES ET RESSOURCESStar Wars et le monomytheL'épisode #2 de Sens Créatif avec ClodL'épisode #99 de Sens Créatif avec Sophie GuerriveLA QUÊTEle formulaire de pré-inscription en ligne+ d'infos sur le super bootcamp !

In Episode Two of Season 2, Clod and I have a funny, “spirited” discussion about our encounters with psychics, hypnotists, and homemade Ouija boards. Clod tells a wild college tale she'd completely forgotten until she found it in her diary, and I tell some crazy spirit-related tales, too, including one which explains my fear of people named Paul. More Secrets:⁠⁠ www.mymothersdiaries.com⁠⁠ Shop: ⁠www.mymothersdiaries.com/mymotherscloset⁠ Listen: ⁠https://www.mymothersdiaries.com/mymotherspodcast Follow Us! Instagram: ⁠ https://www.instagram.com/mymothersdiaries/ TikTok: ⁠ https://www.tiktok.com/@mymothersdiaries Facebook: ⁠ https://www.facebook.com/mymothersdiaries Thank you to Dead Gowns for our new intro song! Listen to Kid 1 by Dead Gowns: https://www.deadgowns.com/

The Dating Episode It's Episode One of Season 2 and we're taking a deep dive into our dating experiences. Tune in to find out why more than one date put Clod in the back seat (it's not what you think), why decades before it was a thing, Clod had phone FOMO, and why Clod's pre-date rituals included quite a combo: bathing and note-taking. We take a close look into why Hilary prefers a stupid date over a smart one, a surprise kiss that left her saying "hello?", and share the break-up song to end all break-up songs. More Secrets:⁠⁠ www.mymothersdiaries.com⁠⁠ Shop: ⁠www.mymothersdiaries.com/mymotherscloset⁠ Listen: ⁠https://www.mymothersdiaries.com/mymotherspodcast Follow Us! Instagram: ⁠ https://www.instagram.com/mymothersdiaries/ TikTok: ⁠ https://www.tiktok.com/@mymothersdiaries Facebook: ⁠ https://www.facebook.com/mymothersdiaries Thank you to Dead Gowns for our new intro song! Listen to Kid 1 by Dead Gowns: https://www.deadgowns.com/ Thank you to Josh for allowing me to share this song with the world! Listen to Sideways by Joshua Comeau: https://soundcloud.com/joshua-comeau

Ralph and Kasim welcome Matt Wolfe, founder of Future Tools and a renowned AI YouTube expert. Matt delves into his 15-year journey of content creation, exploring various tools and tactics before carving his niche in AI. He shares insights on leveraging AI tools like ChatGPT and Clod for generating creative ideas, summaries, and analogies for videos and presentations. Matt discusses top AI tools essential for marketers and addresses the challenges and opportunities presented by AI in the marketing realm. His transition from a content creator to an AI influencer provides invaluable lessons for those looking to integrate AI into their business strategies, offering a unique perspective for marketers and entrepreneurs on the cutting edge of digital marketing and technology.Chapters:00:00:00 Welcome to Perpetual Traffic and Introduction of Matt Wolfe00:01:07 How Matt Wolfe Became an AI Expert and YouTube Star00:03:19 Haygen: A Tool to Create and Translate Videos with Your Voice and Face00:05:55 The Evolution and Future of AI Tools for Content Creation and Marketing00:09:47 Special Offer: Win a Free Ticket to Traffic and Conversion Summit00:12:16 Future Tools: How Matt Wolfe Built a Directory of AI Tools00:17:35 ChatGPT and Clod: Two Powerful AI Tools for Generating Ideas, Summaries, and More00:31:26 How Matt Wolfe Uses AI Tools to Create YouTube Videos and Presentations00:35:23 The Best AI Tools for Marketers and Entrepreneurs00:38:29 The Impact of AI on Content Quality, SEO, and Marketing Campaigns00:48:33 The Future of AI: Open Source Tools and Quantum Computing01:01:53 The Potential Risks and Benefits of Quantum Computing for AI01:04:49 The Future of AI: Predictions and Implications for Content and MarketingLINKS AND RESOURCES:Tier 11 JobsPerpetual Traffic on YouTubeTiereleven.comSolutions 8 Perpetual Traffic SurveyPerpetual Traffic WebsiteFollow Perpetual Traffic on TwitterConnect with Kasim on Twitter and Connect with Ralph on LinkedInThanks so much for joining us this week. Want to subscribe to Perpetual Traffic? Have some feedback you'd like to share? Connect with us on iTunes and leave us a review!Mentioned in this episode:Free Audit

Thatch is joined by Sharkfinnagen and Clod 9 to do some pokemon trivia! We'll be back with regular PUCL next week! puclpodcast@gmail.comThatch's Referral Code for PoGo: 9THMRXDP7Use Code PUCLPOD5 at trollandtoad.com for 5% off and support the show!Don't forget to like us on Facebook, follow us on Twitter, follow us on Tumblr, and most importantly Review us on iTunes!Check us out on Discord!https://pucldiscord.comTwitch: twitch.tv/thepuclpodcast Support PUCL by donating to our Patreon Hosted on Acast. See acast.com/privacy for more information.

Welcome to episode 237 of The Cloud Pod Podcast - where the forecast is always cloudy! It's the most wonderful time of the year - it's almost time for re:Invent! That means it's also time for our wishlist and predictions. Follow along, and see which ones you think have the greatest likelihood of coming to fruition.  A big thanks to this week's sponsor: Foghorn Consulting provides top-notch cloud and DevOps engineers to the world's most innovative companies. Initiatives stalled because you have trouble hiring?  Foghorn can be burning down your DevOps and Cloud backlogs as soon as next week. AWS Predictions  Jonathan GPU Support for Lambda functions   Chat Bot integration for the support portal that pulls from documentation New Baremetal Instance with more GPU's for AI Training Justin Graviton AI Chip Capabilities Olympus with a bigger data set than Open AI and publicly available Major Improvements to Quicksight Ryan AppMesh will support serverless workloads Data Sovereignty on stage Just in time IAM Permissions powered by AI Matthew AI Chat feature in the AWS Console Carbon Emissions and Green Technology talked about during the keynote.  Predictive typing thing integrated into AWS Shell (cloud 9).  Tie Breaker:   Number of times the word Artificial Intelligence and/or AI.   Matt - 72 Ryan - 563 Justin - 142 Jonathan - 90 Honorable Mentions: Reinvent announcement of Clippy/Mascot (Jonathan) Chip Fab (Jonathan) Astro Bot upgrade (Ryan) Astrobot Robot Wars (Ryan) Extra effort/hardware on energy usage (Jonathan) IAM Permissions reducer (Matt) Security/Guardduty/SOC AI (Justin) DuckDB (Justin) AI for Opensearch (Justin) Werner masterclass on AI (Justin) Simulated worlds (Jonathan)

From a toe in one ditch to a cow in a different ditch, from a flaming bra to a fleeing falsie, Clod and I continue sharing silly truths behind our This Is Where TikToks. More Secrets:⁠⁠ www.mymothersdiaries.com⁠⁠ Shop: ⁠www.mymothersdiaries.com/mymotherscloset⁠ Listen: ⁠https://www.mymothersdiaries.com/mymothersdiaries Follow Us! Instagram: ⁠ @mymothersdiaries TikTok: ⁠ @mymothersdiaries Facebook: ⁠ @mymothersdiaries

This is Where Deep Dive Due to popular TikTok demand, Clod shares the back stories behind her mini-memoirs. Watch closely, because we've added in some visual fun along the way! More Secrets:⁠⁠ www.mymothersdiaries.com⁠⁠ Shop: ⁠www.mymothersdiaries.com/mymotherscloset⁠ Listen: ⁠https://www.mymothersdiaries.com/mymotherspodcast Follow Us! Instagram: ⁠https://www.instagram.com/mymothersdiaries TikTok: ⁠https://www.tiktok.com/@mymothersdiaries Facebook: ⁠https://www.facebook.com/mymothersdiaries

It's Episode Eight and as only Clod can, she shares some hair-raising adventures. She confesses why she hid her shorn braid in the attic (and what she secretly did with it), why she wore pink sponge curlers for ten years, and why after one memorable haircut, she headed straight for a tetanus shot. Clod also shares parts of a hair-related story she actually submitted to Glamour magazine in the 80s. Oh and if you're lucky enough to catch us on Youtube, you'll catch us both in curlers. More Secrets:⁠⁠ www.mymothersdiaries.com⁠⁠ Shop: ⁠www.mymothersdiaries.com/mymotherscloset⁠ Listen: ⁠https://www.mymothersdiaries.com/mymothersdiaries Follow Us!Instagram: ⁠https://www.instagram.com/mymothersdiaries TikTok: ⁠https://www.tiktok.com/@mymothersdiaries Facebook: ⁠https://www.facebook.com/mymothersdiaries

131 The boys are back! In this episode Corwin is upset over the wedding of Tony Stark and Emma Frost, and then he tries miserably to get Scott to read Hellfire Gala. Meanwhile Scott talks about how Zom 100 is relatable to him, and then spreads the hype for Clod. The Deadpool books of late July and August are covered and surprise Deadpool is canceled! In Past-O-Vision they finally say goodbye to Cable & Deadpool with Deadpool/GLI: Summer Fun Spectacular. In Monty's Predictions old and new predictions are visited. Waiting in the Review covers the third and fourth episodes of Waiting in the Summer, just in time for summer to start in the show as summer ends in real life. And as always, Robot Chicken Hulk wraps the show up with a PSA.   0:03:48 News 0:17:00 Deadpool Badder Blood (2023) #3 Past-O-Vision 0:30:36 Deadpool GLI Summer Special (2007) #1 0:40:57 Retro Ads 0:53:43 Deadpool (2022) #9 0:58:51 Deadpool (2022) #10 1:07:53 Monty's Predictions 1:22:06 Waiting in the Summer Ep #3 1:29:47 Waiting in the Summer Ep #4 [MwaP RSS] Subscribe [RSS All] Subscribe [Google Podcasts] Subscribe [Apple Podcasts] Subscribe   Music by Jenki Girls of Los Angeles Email: HipsterDaken@gmail.com Website: http://www.EarthsMightiestPodcast.comFacebook Group: https://www.facebook.com/MercWithaPodcast/ Episodes #1-26 can be found @ Cultural Wormhole.com The Merc Report has now joined the EMP family of podcasts and has now become The Merc With a Podcast! -EXPLICIT CONTENT

In Episode Seven, Clod and I share tales where good intentions sometimes turn aggressive and moral dilemmas follow.  Who knew that being a Leo could get you out of a speeding ticket?  That driving well could get you accolades at a Dunkin' drive through?  Or that an owl could could wreak so much havoc and hilarity at the same time?  We want to hear from you! Email us at mymothersdiaries@gmail.com with funny stories of your own or, even better, a reading from your diary. More Secrets:⁠⁠ www.mymothersdiaries.com⁠⁠Shop: ⁠www.mymothersdiaries.com/mymotherscloset⁠Listen: ⁠https://www.mymothersdiaries.com/mymothersdiariesFollow Us!Instagram: ⁠https://www.instagram.com/mymothersdiariesTikTok: ⁠https://www.tiktok.com/@mymothersdiariesFacebook: ⁠https://www.facebook.com/mymothersdiaries

A 70s note left on the bathroom mirror sets the stage for some of what has gone awry in Clod's life – and spilled over into mine. Clod shares wacky advice from her mother, her dermatologist, and even an upscale neighbor hosting a yard sale. We want to hear from you! Email us at mymothersdiaries@gmail.com with funny stories of your own or, even better, a reading from your diary. More Secrets:⁠⁠ www.mymothersdiaries.com⁠⁠ Shop: ⁠www.mymothersdiaries.com/mymotherscloset⁠ Listen: ⁠https://www.mymothersdiaries.com/mymothersdiaries Follow Us!Instagram: ⁠https://www.instagram.com/mymothersdiaries TikTok: ⁠https://www.tiktok.com/@mymothersdiaries Facebook: ⁠https://www.facebook.com/mymothersdiaries

Thatch is joined by Seth Vilo and Clod, they discuss their thoughts on the new meta, what decks they like, and also how to learn to be successful playing the TCG from their personal journies learning the game. Mailbag: What is your personal Pokemon Journey? What questions do you have about the VGC and TCG metas and games puclpodcast@gmail.comThatch's Referral Code for PoGo: 9THMRXDP7PUCL SurveyTimestamps:Intro: 0:00:00News: 0:09:05Quiz: 0:25:21Topic: 0:42:29Pokemon of the Episode: 1:33:43Mailbag: 1:42:52Use Code PUCLPOD5 at trollandtoad.com for 5% off and support the show!Don't forget to like us on Facebook, follow us on Twitter, follow us on Tumblr, and most importantly Review us on iTunes!Check us out on Discord!https://pucldiscord.comTwitch: twitch.tv/thepuclpodcast Support PUCL by donating to our Patreon Hosted on Acast. See acast.com/privacy for more information.

Thatch is joined by the Clod and Mark and they talk about theirMailbag: What is your personal Pokemon Journey? puclpodcast@gmail.comThatch's Referral Code for PoGo: 9THMRXDP7PUCL SurveyTimestamps:Intro: 0:00:00News: 0:12:37Quiz: 0:22:48Topic: 0:38:48Pokemon of the Episode: 1:09:47Mailbag: 1:20:51Use Code PUCLPOD5 at trollandtoad.com for 5% off and support the show!Don't forget to like us on Facebook, follow us on Twitter, follow us on Tumblr, and most importantly Review us on iTunes!Check us out on Discord!https://pucldiscord.comTwitch: twitch.tv/thepuclpodcast Support PUCL by donating to our Patreon Hosted on Acast. See acast.com/privacy for more information.