POPULARITY
3 episodes with Timeboxing
3 episodes with Timeboxing
2 episodes with Timeboxing
2 episodes with Timeboxing
2 episodes with Timeboxing
2 episodes with Timeboxing
2 episodes with Timeboxing
2 episodes with Timeboxing
2 episodes with Timeboxing
Timeboxing is the most powerful time-management technique. However, there is no one way to timebox. Some people keep the same schedule every week and review it on Sundays. Others change their timeboxed calendar daily and review it the night before.Some people use a spreadsheet in 30 or 15-minute increments, others use Google Calendar, and others use one of the many timeboxing apps available.This step-by-step guide, plus timeboxing examples from real people, will help you figure out what timeboxing looks like for you.Remember: No productivity technique is effective and easy. It's going to be effective and hard. Nothing will magically solve time management without some effort.You can read the Nir And Far blog post on: How Successful People Timebox here.Nir And Far, a podcast about business, behaviour and the brain by Nir Eyal. If you enjoy this podcast, please subscribe on iTunes and leave an iTunes review. It will greatly help new listeners discover the show. Please visit my website Nir and Far for other info about my writing, books and teaching: http://www.nirandfar.com/
Send us a textEver finish your day feeling exhausted but unproductive? You're not alone! Join Jena and Kelly McLaughlin, founder of From Scratch Fundraising, as they get real about nonprofit productivity tactics that make a meaningful difference in combating overwhelm. Learn how to prioritize effectively, manage your energy instead of your time, and harness powerful tools like CRMs and project management systems.Discover:Why urgent tasks often overshadow important ones (and how to fix it!)The power of brain dumping and daily reviews for clarity and focusHow to combine or choose between Time Boxing and Time Blocking for your scheduleReserve your spot at Kelly's Friday Focus Session: Productivity Hacks for Fundraising on Friday, April 18, here. Chapters00:00 Introduction to Nonprofit Productivity Challenges03:06 Understanding Urgency vs. Importance in Nonprofits06:02 Strategies for Effective Time Management08:51 The Importance of Goal Setting and Energy Management12:04 Timeboxing vs. Time Blocking: Finding Your Fit15:09 Leveraging Tools for Enhanced Productivity17:55 Implementing Daily Reviews for Continuous Improvement20:53 Actionable Tips to Overcome OverwhelmWhat makes Donorbox the Best Nonprofit Fundraising Platform to Achieve Your Strategic Goals?Easy to customize, available in multiple languages and currencies, and supported by leading payment processors (Stripe and PayPal), Donorbox's nonprofit fundraising solution is used by 80,000+ global organizations and individuals. From animal rescue to schools, places of worship, and research groups, nonprofits use Donorbox to raise more funds, manage donors efficiently, and make a bigger impact.Discover how Donorbox can help you help others! The Nonprofit Podcast and a wealth of nonprofit leadership tutorials, expert advice, tips, and tactics are available on the Donorbox YouTube channel. Subscribe today and never miss an episode:
There are all kinds of productivity tools out there promising to help you make the most of your day. Some people swear by timeboxing: the method of reserving time on your calendar each day for each task you want to get done, and then truly focusing on that one thing at a time. The return on merging your to-do list with your calendar like this, says Marc Zao-Sanders, is higher productivity, better collaboration, and less distraction and anxiety. He explains how try to the method yourself and the how your team and organization benefit from it, not just you. Zao-Sanders is author of the book "Timeboxing: The Power of Doing One Thing at a Time."
Carole Lamarque is ondernemer, auteur en een van de meest invloedrijke marketeers van België. Met onaflatend enthousiasme deelt ze haar ervaring regelmatig in keynotes, met haar 30k volgers op LinkedIn en nu ook op Ben's Mentors. In deze aflevering hoor je van Carole:- Hoe je jouw marketing strategisch aanpakt.- Hoe je influencer marketing effectief inzet voor je bedrijf.- Waarom je moet denken en handelen als een jachtluipaard.- Hoe timeboxing en time squeezing leiden tot een waardevol leven.- Hoe het mantra ‘
Kennst du das Gefühl, dass der Tag einfach nicht genug Stunden hat? Dann ist Timeboxing genau das Richtige für dich. Diese Methode hilft dir, deine Konzentration zu steigern, deine Zeit effektiver zu nutzen und Prokrastination zu vermeiden.
Listen now on Apple, Spotify, and YouTube.—Hannah is a UX researcher with over a decade of experience helping product teams make smarter, faster decisions. She has a thing for working on public sector services, the grittier, the better and nothing is grittier than healthcare (especially women's health). Hannah worked her way up the chain to be head of research, but she just couldn't keep away from the hustle of a product team. Instead, she focused on scaling down UX research methods so even the leanest teams can get some insight.Her mantra? Good research comes in small packages. In our conversation, we discuss:* The importance of bridging the gap between research and business decisions* Challenges of getting research used by teams and keeping it actionable* The value of workshops in facilitating collaboration and decision-making* Tips for structuring workshops in an agile, time-constrained environmentAny links to courses or somethingSome takeaways:* Research doesn't end with analysis. To ensure your findings are applied, you need to facilitate discussions that help teams translate insights into actionable decisions. After completing research, schedule a workshop where key stakeholders (designers, product managers, and developers) collaborate to prioritize insights based on business needs and feasibility.* Workshops are vital for creating alignment between cross-functional teams. Hannah emphasized how they enable everyone to share perspectives and make collaborative decisions, ensuring that research gets implemented. Start by introducing short workshops (like assumption mapping) into existing meetings, ensuring that decisions are made as a group rather than individually by stakeholders.* In agile teams, traditional long-form research methods can be broken down into smaller, digestible tasks spread across multiple sessions. This makes them more manageable and ensures participation without overwhelming the team. Use methods like problem clarity vs. risk mapping in agile sprints by integrating them into existing meetings like retrospectives or standups. Limit activities to 10-15 minutes to fit the team's schedule.* A well-structured workshop ensures that participants stay focused and engaged. Timeboxing each part of the workshop, as Hannah suggested, keeps discussions on track and maximizes productivity. For every workshop, clearly define time limits for each activity. Use visible countdowns to ensure that no one person dominates the conversation, allowing equal participation from all team members.* The misconception that workshops must be long or formal is outdated. Short, frequent sessions can be just as effective in driving decisions and maintaining momentum. Create “minimum viable workshops” by breaking a larger activity into smaller chunks across multiple shorter meetings. For example, instead of a three-hour workshop, spread exercises across a two-week sprint, completing small tasks during existing ceremonies or standups.Where to find Hannah:* LinkedIn* WebsiteFor inquiries about sponsoring the podcast, email nikki@userresearchacademy.com This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit userresearchacademy.substack.com/subscribe
“Most people don't want to acknowledge the uncomfortable truth that distraction is always an unhealthy escape from reality.” My latest guest, Nir Eyal, writes, consults, and teaches about the intersection of psychology, technology, and business. Nir previously taught as a Lecturer in Marketing at the Stanford Graduate School of Business and the Hasso Plattner Institute of Design at Stanford. In our conversation, Nir gives it to us straight. Distraction is killing us, and stopping us from reaching our full potential. In a world that is constantly conspiring to keep us distracted, Nir provides an alternative: we can take back control. We can regain our agency. All of these ideas are presented in his book, Indistractable: How to Control Your Attention and Choose Your Life (co-authored with Julie Li). This book is a clear guide to understanding the psychology behind our impulses and is chock-full of great anecdotes and peer-reviewed studies to help you better manage your time, and your life. Nir's framework is not only interesting, it is practical, so I suggest you check out our Substack, where you'll find the episode transcript and some actionable takeaways. I also encourage you to buy Nir's excellent book and start applying his strategies to your own life. I hope you enjoy our conversation as much as I did! Important Links: Nir's personal blog Nir's LinkedIn Nir's Twitter Nir's YouTube channel Nir's Habit Tracking Tool Nir's Schedule Maker Tool Show Notes: What Being Indistractable Is All About Etymology of the Word Distraction The Strong Pull of Internal Triggers The Tyranny of the To-Do List The Difference Between High Performers and Low Performers The Dangers of Labelling Ourselves Using the Psychology of Identity Using Self-Determination Theory to Diagnose Distraction The Perils of Snowplow Parenting Believe the Good Science Nir as Emperor of the World Books / Articles Mentioned: Indistractable; by Nir Eyal (+ bonus content) Nir's articles on Timeboxing, Values, FOMO and Wage slavery Free to Learn: Why Unleashing the Instinct to Play Will Make Our Children Happier, More Self-Reliant, and Better Students for Life; by Peter Gray
016 | In dieser Episode gibt Susanne, selbstständige Strukturmentorin, Einblicke in effizientes Zeitmanagement, den Nutzen von Automatisierungen und das Setzen klarer Prioritäten. Erfahre, wie sie anderen Soloselbstständigen hilft, Struktur in ihren Alltag zu bringen, und welche Methoden sie verwendet, um ihre Arbeitsweise zu optimieren. Lass dich von Susannes Erfahrungen und Tipps inspirieren, um deinen eigenen Weg zur erfolgreichen Selbstständigkeit zu finden!
Today's guest, Nicholas Carlini, a research scientist at DeepMind, argues that we should be focusing more on what AI can do for us individually, rather than trying to have an answer for everyone."How I Use AI" - A Pragmatic ApproachCarlini's blog post "How I Use AI" went viral for good reason. Instead of giving a personal opinion about AI's potential, he simply laid out how he, as a security researcher, uses AI tools in his daily work. He divided it in 12 sections:* To make applications* As a tutor* To get started* To simplify code* For boring tasks* To automate tasks* As an API reference* As a search engine* To solve one-offs* To teach me* Solving solved problems* To fix errorsEach of the sections has specific examples, so we recommend going through it. It also includes all prompts used for it; in the "make applications" case, it's 30,000 words total!My personal takeaway is that the majority of the work AI can do successfully is what humans dislike doing. Writing boilerplate code, looking up docs, taking repetitive actions, etc. These are usually boring tasks with little creativity, but with a lot of structure. This is the strongest arguments as to why LLMs, especially for code, are more beneficial to senior employees: if you can get the boring stuff out of the way, there's a lot more value you can generate. This is less and less true as you go entry level jobs which are mostly boring and repetitive tasks. Nicholas argues both sides ~21:34 in the pod.A New Approach to LLM BenchmarksWe recently did a Benchmarks 201 episode, a follow up to our original Benchmarks 101, and some of the issues have stayed the same. Notably, there's a big discrepancy between what benchmarks like MMLU test, and what the models are used for. Carlini created his own domain-specific language for writing personalized LLM benchmarks. The idea is simple but powerful:* Take tasks you've actually needed AI for in the past.* Turn them into benchmark tests.* Use these to evaluate new models based on your specific needs.It can represent very complex tasks, from a single code generation to drawing a US flag using C:"Write hello world in python" >> LLMRun() >> PythonRun() >> SubstringEvaluator("hello world")"Write a C program that draws an american flag to stdout." >> LLMRun() >> CRun() >> VisionLLMRun("What flag is shown in this image?") >> (SubstringEvaluator("United States") | SubstringEvaluator("USA")))This approach solves a few problems:* It measures what's actually useful to you, not abstract capabilities.* It's harder for model creators to "game" your specific benchmark, a problem that has plagued standardized tests.* It gives you a concrete way to decide if a new model is worth switching to, similar to how developers might run benchmarks before adopting a new library or framework.Carlini argues that if even a small percentage of AI users created personal benchmarks, we'd have a much better picture of model capabilities in practice.AI SecurityWhile much of the AI security discussion focuses on either jailbreaks or existential risks, Carlini's research targets the space in between. Some highlights from his recent work:* LAION 400M data poisoning: By buying expired domains referenced in the dataset, Carlini's team could inject arbitrary images into models trained on LAION 400M. You can read the paper "Poisoning Web-Scale Training Datasets is Practical", for all the details. This is a great example of expanding the scope beyond the model itself, and looking at the whole system and how ti can become vulnerable.* Stealing model weights: They demonstrated how to extract parts of production language models (like OpenAI's) through careful API queries. This research, "Extracting Training Data from Large Language Models", shows that even black-box access can leak sensitive information.* Extracting training data: In some cases, they found ways to make models regurgitate verbatim snippets from their training data. Him and Milad Nasr wrote a paper on this as well: Scalable Extraction of Training Data from (Production) Language Models. They also think this might be applicable to extracting RAG results from a generation.These aren't just theoretical attacks. They've led to real changes in how companies like OpenAI design their APIs and handle data. If you really miss logit_bias and logit results by token, you can blame Nicholas :)We had a ton of fun also chatting about things like Conway's Game of Life, how much data can fit in a piece of paper, and porting Doom to Javascript. Enjoy!Show Notes* How I Use AI* My Benchmark for LLMs* Doom Javascript port* Conway's Game of Life* Tic-Tac-Toe in one printf statement* International Obfuscated C Code Contest* Cursor* LAION 400M poisoning paper* Man vs Machine at Black Hat* Model Stealing from OpenAI* Milad Nasr* H.D. Moore* Vijay Bolina* Cosine.sh* uuencodeTimestamps* [00:00:00] Introductions* [00:01:14] Why Nicholas writes* [00:02:09] The Game of Life* [00:05:07] "How I Use AI" blog post origin story* [00:08:24] Do we need software engineering agents?* [00:11:03] Using AI to kickstart a project* [00:14:08] Ephemeral software* [00:17:37] Using AI to accelerate research* [00:21:34] Experts vs non-expert users as beneficiaries of AI* [00:24:02] Research on generating less secure code with LLMs.* [00:27:22] Learning and explaining code with AI* [00:30:12] AGI speculations?* [00:32:50] Distributing content without social media* [00:35:39] How much data do you think you can put on a single piece of paper?* [00:37:37] Building personal AI benchmarks* [00:43:04] Evolution of prompt engineering and its relevance* [00:46:06] Model vs task benchmarking* [00:52:14] Poisoning LAION 400M through expired domains* [00:55:38] Stealing OpenAI models from their API* [01:01:29] Data stealing and recovering training data from models* [01:03:30] Finding motivation in your workTranscriptAlessio [00:00:00]: Hey everyone, welcome to the Latent Space podcast. This is Alessio, partner and CTO-in-Residence 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 in the in-person studio, which Alessio has gorgeously set up for us, with Nicholas Carlini. Welcome. Thank you. You're a research scientist at DeepMind. You work at the intersection of machine learning and computer security. You got your PhD from Berkeley in 2018, and also your BA from Berkeley as well. And mostly we're here to talk about your blogs, because you are so generous in just writing up what you know. Well, actually, why do you write?Nicholas [00:00:41]: Because I like, I feel like it's fun to share what you've done. I don't like writing, sufficiently didn't like writing, I almost didn't do a PhD, because I knew how much writing was involved in writing papers. I was terrible at writing when I was younger. I do like the remedial writing classes when I was in university, because I was really bad at it. So I don't actually enjoy, I still don't enjoy the act of writing. But I feel like it is useful to share what you're doing, and I like being able to talk about the things that I'm doing that I think are fun. And so I write because I think I want to have something to say, not because I enjoy the act of writing.Swyx [00:01:14]: But yeah. It's a tool for thought, as they often say. Is there any sort of backgrounds or thing that people should know about you as a person? Yeah.Nicholas [00:01:23]: So I tend to focus on, like you said, I do security work, I try to like attacking things and I want to do like high quality security research. And that's mostly what I spend my actual time trying to be productive members of society doing that. But then I get distracted by things, and I just like, you know, working on random fun projects. Like a Doom clone in JavaScript.Swyx [00:01:44]: Yes.Nicholas [00:01:45]: Like that. Or, you know, I've done a number of things that have absolutely no utility. But are fun things to have done. And so it's interesting to say, like, you should work on fun things that just are interesting, even if they're not useful in any real way. And so that's what I tend to put up there is after I have completed something I think is fun, or if I think it's sufficiently interesting, write something down there.Alessio [00:02:09]: Before we go into like AI, LLMs and whatnot, why are you obsessed with the game of life? So you built multiplexing circuits in the game of life, which is mind boggling. So where did that come from? And then how do you go from just clicking boxes on the UI web version to like building multiplexing circuits?Nicholas [00:02:29]: I like Turing completeness. The definition of Turing completeness is a computer that can run anything, essentially. And the game of life, Conway's game of life is a very simple cellular 2D automata where you have cells that are either on or off. And a cell becomes on if in the previous generation some configuration holds true and off otherwise. It turns out there's a proof that the game of life is Turing complete, that you can run any program in principle using Conway's game of life. I don't know. And so you can, therefore someone should. And so I wanted to do it. Some other people have done some similar things, but I got obsessed into like, if you're going to try and make it work, like we already know it's possible in theory. I want to try and like actually make something I can run on my computer, like a real computer I can run. And so yeah, I've been going on this rabbit hole of trying to make a CPU that I can run semi real time on the game of life. And I have been making some reasonable progress there. And yeah, but you know, Turing completeness is just like a very fun trap you can go down. A while ago, as part of a research paper, I was able to show that in C, if you call into printf, it's Turing complete. Like printf, you know, like, which like, you know, you can print numbers or whatever, right?Swyx [00:03:39]: Yeah, but there should be no like control flow stuff.Nicholas [00:03:42]: Because printf has a percent n specifier that lets you write an arbitrary amount of data to an arbitrary location. And the printf format specifier has an index into where it is in the loop that is in memory. So you can overwrite the location of where printf is currently indexing using percent n. So you can get loops, you can get conditionals, and you can get arbitrary data rates again. So we sort of have another Turing complete language using printf, which again, like this has essentially zero practical utility, but like, it's just, I feel like a lot of people get into programming because they enjoy the art of doing these things. And then they go work on developing some software application and lose all joy with the boys. And I want to still have joy in doing these things. And so on occasion, I try to stop doing productive, meaningful things and just like, what's a fun thing that we can do and try and make that happen.Alessio [00:04:39]: Awesome. So you've been kind of like a pioneer in the AI security space. You've done a lot of talks starting back in 2018. We'll kind of leave that to the end because I know the security part is, there's maybe a smaller audience, but it's a very intense audience. So I think that'll be fun. But everybody in our Discord started posting your how I use AI blog post and we were like, we should get Carlini on the podcast. And then you were so nice to just, yeah, and then I sent you an email and you're like, okay, I'll come.Swyx [00:05:07]: And I was like, oh, I thought that would be harder.Alessio [00:05:10]: I think there's, as you said in the blog posts, a lot of misunderstanding about what LLMs can actually be used for. What are they useful at? What are they not good at? And whether or not it's even worth arguing what they're not good at, because they're obviously not. So if you cannot count the R's in a word, they're like, it's just not what it does. So how painful was it to write such a long post, given that you just said that you don't like to write? Yeah. And then we can kind of run through the things, but maybe just talk about the motivation, why you thought it was important to do it.Nicholas [00:05:39]: Yeah. So I wanted to do this because I feel like most people who write about language models being good or bad, some underlying message of like, you know, they have their camp and their camp is like, AI is bad or AI is good or whatever. And they like, they spin whatever they're going to say according to their ideology. And they don't actually just look at what is true in the world. So I've read a lot of things where people say how amazing they are and how all programmers are going to be obsolete by 2024. And I've read a lot of things where people who say like, they can't do anything useful at all. And, you know, like, they're just like, it's only the people who've come off of, you know, blockchain crypto stuff and are here to like make another quick buck and move on. And I don't really agree with either of these. And I'm not someone who cares really one way or the other how these things go. And so I wanted to write something that just says like, look, like, let's sort of ground reality and what we can actually do with these things. Because my actual research is in like security and showing that these models have lots of problems. Like this is like my day to day job is saying like, we probably shouldn't be using these in lots of cases. I thought I could have a little bit of credibility of in saying, it is true. They have lots of problems. We maybe shouldn't be deploying them lots of situations. And still, they are also useful. And that is the like, the bit that I wanted to get across is to say, I'm not here to try and sell you on anything. I just think that they're useful for the kinds of work that I do. And hopefully, some people would listen. And it turned out that a lot more people liked it than I thought. But yeah, that was the motivation behind why I wanted to write this.Alessio [00:07:15]: So you had about a dozen sections of like how you actually use AI. Maybe we can just kind of run through them all. And then maybe the ones where you have extra commentary to add, we can... Sure.Nicholas [00:07:27]: Yeah, yeah. I didn't put as much thought into this as maybe was deserved. I probably spent, I don't know, definitely less than 10 hours putting this together.Swyx [00:07:38]: Wow.Alessio [00:07:39]: It took me close to that to do a podcast episode. So that's pretty impressive.Nicholas [00:07:43]: Yeah. I wrote it in one pass. I've gotten a number of emails of like, you got this editing thing wrong, you got this sort of other thing wrong. It's like, I haven't just haven't looked at it. I tend to try it. I feel like I still don't like writing. And so because of this, the way I tend to treat this is like, I will put it together into the best format that I can at a time, and then put it on the internet, and then never change it. And this is an aspect of like the research side of me is like, once a paper is published, like it is done as an artifact that exists in the world. I could forever edit the very first thing I ever put to make it the most perfect version of what it is, and I would do nothing else. And so I feel like I find it useful to be like, this is the artifact, I will spend some certain amount of hours on it, which is what I think it is worth. And then I will just...Swyx [00:08:22]: Yeah.Nicholas [00:08:23]: Timeboxing.Alessio [00:08:24]: Yeah. Stop. Yeah. Okay. We just recorded an episode with the founder of Cosine, which is like an AI software engineer colleague. You said it took you 30,000 words to get GPT-4 to build you the, can GPT-4 solve this kind of like app. Where are we in the spectrum where chat GPT is all you need to actually build something versus I need a full on agent that does everything for me?Nicholas [00:08:46]: Yeah. Okay. So this was an... So I built a web app last year sometime that was just like a fun demo where you can guess if you can predict whether or not GPT-4 at the time could solve a given task. This is, as far as web apps go, very straightforward. You need basic HTML, CSS, you have a little slider that moves, you have a button, sort of animate the text coming to the screen. The reason people are going here is not because they want to see my wonderful HTML, right? I used to know how to do modern HTML in 2007, 2008. I was very good at fighting with IE6 and these kinds of things. I knew how to do that. I have no longer had to build any web app stuff in the meantime, which means that I know how everything works, but I don't know any of the new... Flexbox is new to me. Flexbox is like 10 years old at this point, but it's just amazing being able to go to the model and just say, write me this thing and it will give me all of the boilerplate that I need to get going. Of course it's imperfect. It's not going to get you the right answer, and it doesn't do anything that's complicated right now, but it gets you to the point where the only remaining work that needs to be done is the interesting hard part for me, the actual novel part. Even the current models, I think, are entirely good enough at doing this kind of thing, that they're very useful. It may be the case that if you had something, like you were saying, a smarter agent that could debug problems by itself, that might be even more useful. Currently though, make a model into an agent by just copying and pasting error messages for the most part. That's what I do, is you run it and it gives you some code that doesn't work, and either I'll fix the code, or it will give me buggy code and I won't know how to fix it, and I'll just copy and paste the error message and say, it tells me this. What do I do? And it will just tell me how to fix it. You can't trust these things blindly, but I feel like most people on the internet already understand that things on the internet, you can't trust blindly. And so this is not like a big mental shift you have to go through to understand that it is possible to read something and find it useful, even if it is not completely perfect in its output.Swyx [00:10:54]: It's very human-like in that sense. It's the same ring of trust, I kind of think about it that way, if you had trust levels.Alessio [00:11:03]: And there's maybe a couple that tie together. So there was like, to make applications, and then there's to get started, which is a similar you know, kickstart, maybe like a project that you know the LLM cannot solve. It's kind of how you think about it.Nicholas [00:11:15]: Yeah. So for getting started on things is one of the cases where I think it's really great for some of these things, where I sort of use it as a personalized, help me use this technology I've never used before. So for example, I had never used Docker before January. I know what Docker is. Lucky you. Yeah, like I'm a computer security person, like I sort of, I have read lots of papers on, you know, all the technology behind how these things work. You know, I know all the exploits on them, I've done some of these things, but I had never actually used Docker. But I wanted it to be able to, I could run the outputs of language model stuff in some controlled contained environment, which I know is the right application. So I just ask it like, I want to use Docker to do this thing, like, tell me how to run a Python program in a Docker container. And it like gives me a thing. I'm like, step back. You said Docker compose, I do not know what this word Docker compose is. Is this Docker? Help me. And like, you'll sort of tell me all of these things. And I'm sure there's this knowledge that's out there on the internet, like this is not some groundbreaking thing that I'm doing, but I just wanted it as a small piece of one thing I was working on. And I didn't want to learn Docker from first principles. Like I, at some point, if I need it, I can do that. Like I have the background that I can make that happen. But what I wanted to do was, was thing one. And it's very easy to get bogged down in the details of this other thing that helps you accomplish your end goal. And I just want to like, tell me enough about Docker so I can do this particular thing. And I can check that it's doing the safe thing. I sort of know enough about that from, you know, my other background. And so I can just have the model help teach me exactly the one thing I want to know and nothing more. I don't need to worry about other things that the writer of this thinks is important that actually isn't. Like I can just like stop the conversation and say, no, boring to me. Explain this detail. I don't understand. I think that's what that was very useful for me. It would have taken me, you know, several hours to figure out some things that take 10 minutes if you could just ask exactly the question you want the answer to.Alessio [00:13:05]: Have you had any issues with like newer tools? Have you felt any meaningful kind of like a cutoff day where like there's not enough data on the internet or? I'm sure that the answer to this is yes.Nicholas [00:13:16]: But I tend to just not use most of these things. Like I feel like this is like the significant way in which I use machine learning models is probably very different than most people is that I'm a researcher and I get to pick what tools that I use and most of the things that I work on are fairly small projects. And so I can, I can entirely see how someone who is in a big giant company where they have their own proprietary legacy code base of a hundred million lines of code or whatever and like you just might not be able to use things the same way that I do. I still think there are lots of use cases there that are entirely reasonable that are not the same ones that I've put down. But I wanted to talk about what I have personal experience in being able to say is useful. And I would like it very much if someone who is in one of these environments would be able to describe the ways in which they find current models useful to them. And not, you know, philosophize on what someone else might be able to find useful, but actually say like, here are real things that I have done that I found useful for me.Swyx [00:14:08]: Yeah, this is what I often do to encourage people to write more, to share their experiences because they often fear being attacked on the internet. But you are the ultimate authority on how you use things and there's this objectively true. So they cannot be debated. One thing that people are very excited about is the concept of ephemeral software or like personal software. This use case in particular basically lowers the activation energy for creating software, which I like as a vision. I don't think I have taken as much advantage of it as I could. I feel guilty about that. But also, we're trending towards there.Nicholas [00:14:47]: Yeah. No, I mean, I do think that this is a direction that is exciting to me. One of the things I wrote that was like, a lot of the ways that I use these models are for one-off things that I just need to happen that I'm going to throw away in five minutes. And you can.Swyx [00:15:01]: Yeah, exactly.Nicholas [00:15:02]: Right. It's like the kind of thing where it would not have been worth it for me to have spent 45 minutes writing this, because I don't need the answer that badly. But if it will only take me five minutes, then I'll just figure it out, run the program and then get it right. And if it turns out that you ask the thing, it doesn't give you the right answer. Well, I didn't actually need the answer that badly in the first place. Like either I can decide to dedicate the 45 minutes or I cannot, but like the cost of doing it is fairly low. You see what the model can do. And if it can't, then, okay, when you're using these models, if you're getting the answer you want always, it means you're not asking them hard enough questions.Swyx [00:15:35]: Say more.Nicholas [00:15:37]: Lots of people only use them for very small particular use cases and like it always does the thing that they want. Yeah.Swyx [00:15:43]: Like they use it like a search engine.Nicholas [00:15:44]: Yeah. Or like one particular case. And if you're finding that when you're using these, it's always giving you the answer that you want, then probably it has more capabilities than you're actually using. And so I oftentimes try when I have something that I'm curious about to just feed into the model and be like, well, maybe it's just solved my problem for me. You know, most of the time it doesn't, but like on occasion, it's like, it's done things that would have taken me, you know, a couple hours that it's been great and just like solved everything immediately. And if it doesn't, then it's usually easier to verify whether or not the answer is correct than to have written in the first place. And so you check, you're like, well, that's just, you're entirely misguided. Nothing here is right. It's just like, I'm not going to do this. I'm going to go write it myself or whatever.Alessio [00:16:21]: Even for non-tech, I had to fix my irrigation system. I had an old irrigation system. I didn't know how I worked to program it. I took a photo, I sent it to Claude and it's like, oh yeah, that's like the RT 900. This is exactly, I was like, oh wow, you know, you know, a lot of stuff.Swyx [00:16:34]: Was it right?Alessio [00:16:35]: Yeah, it was right.Swyx [00:16:36]: It worked. Did you compare with OpenAI?Alessio [00:16:38]: No, I canceled my OpenAI subscription, so I'm a Claude boy. Do you have a way to think about this like one-offs software thing? One way I talk to people about it is like LLMs are kind of converging to like semantic serverless functions, you know, like you can say something and like it can run the function in a way and then that's it. It just kind of dies there. Do you have a mental model to just think about how long it should live for and like anything like that?Nicholas [00:17:02]: I don't think I have anything interesting to say here, no. I will take whatever tools are available in front of me and try and see if I can use them in meaningful ways. And if they're helpful, then great. If they're not, then fine. And like, you know, there are lots of people that I'm very excited about seeing all these people who are trying to make better applications that use these or all these kinds of things. And I think that's amazing. I would like to see more of it, but I do not spend my time thinking about how to make this any better.Alessio [00:17:27]: What's the most underrated thing in the list? I know there's like simplified code, solving boring tasks, or maybe is there something that you forgot to add that you want to throw in there?Nicholas [00:17:37]: I mean, so in the list, I only put things that people could look at and go, I understand how this solved my problem. I didn't want to put things where the model was very useful to me, but it would not be clear to someone else that it was actually useful. So for example, one of the things that I use it a lot for is debugging errors. But the errors that I have are very much not the errors that anyone else in the world will have. And in order to understand whether or not the solution was right, you just have to trust me on it. Because, you know, like I got my machine in a state that like CUDA was not talking to whatever some other thing, the versions were mismatched, something, something, something, and everything was broken. And like, I could figure it out with interaction with the model, and it gave it like told me the steps I needed to take. But at the end of the day, when you look at the conversation, you just have to trust me that it worked. And I didn't want to write things online that were this, like, you have to trust me that what I'm saying. I want everything that I said to like have evidence that like, here's the conversation, you can go and check whether or not this actually solved the task as I said that the model does. Because a lot of people I feel like say, I used a model to solve this very complicated task. And what they mean is the model did 10%, and I did the other 90% or something, I wanted everything to be verifiable. And so one of the biggest use cases for me, I didn't describe even at all, because it's not the kind of thing that other people could have verified by themselves. So that maybe is like, one of the things that I wish I maybe had said a little bit more about, and just stated that the way that this is done, because I feel like that this didn't come across quite as well. But yeah, of the things that I talked about, the thing that I think is most underrated is the ability of it to solve the uninteresting parts of problems for me right now, where people always say, this is one of the biggest arguments that I don't understand why people say is, the model can only do things that people have done before. Therefore, the model is not going to be helpful in doing new research or like discovering new things. And as someone whose day job is to do new things, like what is research? Research is doing something literally no one else in the world has ever done before. So this is what I do every single day, 90% of this is not doing something new, 90% of this is doing things a million people have done before, and then a little bit of something that was new. There's a reason why we say we stand on the shoulders of giants. It's true. Almost everything that I do is something that's been done many, many times before. And that is the piece that can be automated. Even if the thing that I'm doing as a whole is new, it is almost certainly the case that the small pieces that build up to it are not. And a number of people who use these models, I feel like expect that they can either solve the entire task or none of the task. But now I find myself very often, even when doing something very new and very hard, having models write the easy parts for me. And the reason I think this is so valuable, everyone who programs understands this, like you're currently trying to solve some problem and then you get distracted. And whatever the case may be, someone comes and talks to you, you have to go look up something online, whatever it is. You lose a lot of time to that. And one of the ways we currently don't think about being distracted is you're solving some hard problem and you realize you need a helper function that does X, where X is like, it's a known algorithm. Any person in the world, you say like, give me the algorithm that, have a dense graph or a sparse graph, I need to make it dense. You can do this by doing some matrix multiplies. It's like, this is a solved problem. I knew how to do this 15 years ago, but it distracts me from the problem I'm thinking about in my mind. I needed this done. And so instead of using my mental capacity and solving that problem and then coming back to the problem I was originally trying to solve, you could just ask model, please solve this problem for me. It gives you the answer. You run it. You can check that it works very, very quickly. And now you go back to solving the problem without having lost all the mental state. And I feel like this is one of the things that's been very useful for me.Swyx [00:21:34]: And in terms of this concept of expert users versus non-expert users, floors versus ceilings, you had some strong opinion here that like, basically it actually is more beneficial for non-experts.Nicholas [00:21:46]: Yeah, I don't know. I think it could go either way. Let me give you the argument for both of these. Yes. So I can only speak on the expert user behalf because I've been doing computers for a long time. And so yeah, the cases where it's useful for me are exactly these cases where I can check the output. I know, and anything the model could do, I could have done. I could have done better. I can check every single thing that the model is doing and make sure it's correct in every way. And so I can only speak and say, definitely it's been useful for me. But I also see a world in which this could be very useful for the kinds of people who do not have this knowledge, with caveats, because I'm not one of these people. I don't have this direct experience. But one of these big ways that I can see this is for things that you can check fairly easily, someone who could never have asked or have written a program themselves to do a certain task could just ask for the program that does the thing. And you know, some of the times it won't get it right. But some of the times it will, and they'll be able to have the thing in front of them that they just couldn't have done before. And we see a lot of people trying to do applications for this, like integrating language models into spreadsheets. Spreadsheets run the world. And there are some people who know how to do all the complicated spreadsheet equations and various things, and other people who don't, who just use the spreadsheet program but just manually do all of the things one by one by one by one. And this is a case where you could have a model that could try and give you a solution. And as long as the person is rigorous in testing that the solution does actually the correct thing, and this is the part that I'm worried about most, you know, I think depending on these systems in ways that we shouldn't, like this is what my research says, my research says is entirely on this, like, you probably shouldn't trust these models to do the things in adversarial situations, like, I understand this very deeply. And so I think that it's possible for people who don't have this knowledge to make use of these tools in ways, but I'm worried that it might end up in a world where people just blindly trust them, deploy them in situations that they probably shouldn't, and then someone like me gets to come along and just break everything because everything is terrible. And so I am very, very worried about that being the case, but I think if done carefully it is possible that these could be very useful.Swyx [00:23:54]: Yeah, there is some research out there that shows that when people use LLMs to generate code, they do generate less secure code.Nicholas [00:24:02]: Yeah, Dan Bonet has a nice paper on this. There are a bunch of papers that touch on exactly this.Swyx [00:24:07]: My slight issue is, you know, is there an agenda here?Nicholas [00:24:10]: I mean, okay, yeah, Dan Bonet, at least the one they have, like, I fully trust everything that sort of.Swyx [00:24:15]: Sorry, I don't know who Dan is.Swyx [00:24:17]: He's a professor at Stanford. Yeah, he and some students have some things on this. Yeah, there's a number. I agree that a lot of the stuff feels like people have an agenda behind it. There are some that don't, and I trust them to have done the right thing. I also think, even on this though, we have to be careful because the argument, whenever someone says x is true about language models, you should always append the suffix for current models because I'll be the first to admit I was one of the people who was very much on the opinion that these language models are fun toys and are going to have absolutely no practical utility. If you had asked me this, let's say, in 2020, I still would have said the same thing. After I had seen GPT-2, I had written a couple of papers studying GPT-2 very carefully. I still would have told you these things are toys. And when I first read the RLHF paper and the instruction tuning paper, I was like, nope, this is this thing that these weird AI people are doing. They're trying to make some analogies to people that makes no sense. It's just like, I don't even care to read it. I saw what it was about and just didn't even look at it. I was obviously wrong. These things can be useful. And I feel like a lot of people had the same mentality that I did and decided not to change their mind. And I feel like this is the thing that I want people to be careful about. I want them to at least know what is true about the world so that they can then see that maybe they should reconsider some of the opinions that they had from four or five years ago that may just not be true about today's models.Swyx [00:25:47]: Specifically because you brought up spreadsheets, I want to share my personal experience because I think Google has done a really good job that people don't know about, which is if you use Google Sheets, Gemini is integrated inside of Google Sheets and it helps you write formulas. Great.Nicholas [00:26:00]: That's news to me.Swyx [00:26:01]: Right? They don't maybe do a good job. Unless you watch Google I.O., there was no other opportunity to learn that Gemini is now in your Google Sheets. And so I just don't write formulas manually anymore. It just prompts Gemini to do it for me. And it does it.Nicholas [00:26:15]: One of the problems that these machine learning models have is a discoverability problem. I think this will be figured out. I mean, it's the same problem that you have with any assistant. You're given a blank box and you're like, what do I do with it? I think this is great. More of these things, it would be good for them to exist. I want them to exist in ways that we can actually make sure that they're done correctly. I don't want to just have them be pushed into more and more things just blindly. I feel like lots of people, there are far too many X plus AI, where X is like arbitrary thing in the world that has nothing to do with it and could not be benefited at all. And they're just doing it because they want to use the word. And I don't want that to happen.Swyx [00:26:58]: You don't want an AI fridge?Nicholas [00:27:00]: No. Yes. I do not want my fridge on the internet.Swyx [00:27:03]: I do not want... Okay.Nicholas [00:27:05]: Anyway, let's not go down that rabbit hole. I understand why some of that happens, because people want to sell things or whatever. But I feel like a lot of people see that and then they write off everything as a result of it. And I just want to say, there are allowed to be people who are trying to do things that don't make any sense. Just ignore them. Do the things that make sense.Alessio [00:27:22]: Another chunk of use cases was learning. So both explaining code, being an API reference, all of these different things. Any suggestions on how to go at it? I feel like one thing is generate code and then explain to me. One way is just tell me about this technology. Another thing is like, hey, I read this online, kind of help me understand it. Any best practices on getting the most out of it?Swyx [00:27:47]: Yeah.Nicholas [00:27:47]: I don't know if I have best practices. I have how I use them.Swyx [00:27:51]: Yeah.Nicholas [00:27:51]: I find it very useful for cases where I understand the underlying ideas, but I have never usedSwyx [00:27:59]: them in this way before.Nicholas [00:28:00]: I know what I'm looking for, but I just don't know how to get there. And so yeah, as an API reference is a great example. The tool everyone always picks on is like FFmpeg. No one in the world knows the command line arguments to do what they want. They're like, make the thing faster. I want lower bitrate, like dash V. Once you tell me what the answer is, I can check. This is one of these things where it's great for these kinds of things. Or in other cases, things where I don't really care that the answer is 100% correct. So for example, I do a lot of security work. Most of security work is reading some code you've never seen before and finding out which pieces of the code are actually important. Because, you know, most of the program isn't actually do anything to do with security. It has, you know, the display piece or the other piece or whatever. And like, you just, you would only ignore all of that. So one very fun use of models is to like, just have it describe all the functions and just skim it and be like, wait, which ones look like approximately the right things to look at? Because otherwise, what are you going to do? You're going to have to read them all manually. And when you're reading them manually, you're going to skim the function anyway, and not just figure out what's going on perfectly. Like you already know that when you're going to read these things, what you're going to try and do is figure out roughly what's going on. Then you'll delve into the details. This is a great way of just doing that, but faster, because it will abstract most of whatSwyx [00:29:21]: is right.Nicholas [00:29:21]: It's going to be wrong some of the time. I don't care.Swyx [00:29:23]: I would have been wrong too.Nicholas [00:29:24]: And as long as you treat it with this way, I think it's great. And so like one of the particular use cases I have in the thing is decompiling binaries, where oftentimes people will release a binary. They won't give you the source code. And you want to figure out how to attack it. And so one thing you could do is you could try and run some kind of decompiler. It turns out for the thing that I wanted, none existed. And so I spent too many hours doing it by hand. Before I first thought, why am I doing this? I should just check if the model could do it for me. And it turns out that it can. And it can turn the compiled source code, which is impossible for any human to understand, into the Python code that is entirely reasonable to understand. And it doesn't run. It has a bunch of problems. But it's so much nicer that it's immediately a win for me. I can just figure out approximately where I should be looking, and then spend all of my time doing that by hand. And again, you get a big win there.Swyx [00:30:12]: So I fully agree with all those use cases, especially for you as a security researcher and having to dive into multiple things. I imagine that's super helpful. I do think we want to move to your other blog post. But you ended your post with a little bit of a teaser about your next post and your speculations. What are you thinking about?Nicholas [00:30:34]: So I want to write something. And I will do that at some point when I have time, maybe after I'm done writing my current papers for ICLR or something, where I want to talk about some thoughts I have for where language models are going in the near-term future. The reason why I want to talk about this is because, again, I feel like the discussion tends to be people who are either very much AGI by 2027, orSwyx [00:30:55]: always five years away, or are going to make statements of the form,Nicholas [00:31:00]: you know, LLMs are the wrong path, and we should be abandoning this, and we should be doing something else instead. And again, I feel like people tend to look at this and see these two polarizing options and go, well, those obviously are both very far extremes. Like, how do I actually, like, what's a more nuanced take here? And so I have some opinions about this that I want to put down, just saying, you know, I have wide margins of error. I think you should too. If you would say there's a 0% chance that something, you know, the models will get very, very good in the next five years, you're probably wrong. If you're going to say there's a 100% chance that in the next five years, then you're probably wrong. And like, to be fair, most of the people, if you read behind the headlines, actually say something like this. But it's very hard to get clicks on the internet of like, some things may be good in the future. Like, everyone wants like, you know, a very, like, nothing is going to be good. This is entirely wrong. It's going to be amazing. You know, like, they want to see this. I want people who have negative reactions to these kinds of extreme views to be able to at least say, like, to tell them, there is something real here. It may not solve all of our problems, but it's probably going to get better. I don't know by how much. And that's basically what I want to say. And then at some point, I'll talk about the safety and security things as a result of this. Because the way in which security intersects with these things depends a lot in exactly how people use these tools. You know, if it turns out to be the case that these models get to be truly amazing and can solve, you know, tasks completely autonomously, that's a very different security world to be living in than if there's always a human in the loop. And the types of security questions I would want to ask would be very different. And so I think, you know, in some very large part, understanding what the future will look like a couple of years ahead of time is helpful for figuring out which problems, as a security person, I want to solve now. You mentioned getting clicks on the internet,Alessio [00:32:50]: but you don't even have, like, an ex-account or anything. How do you get people to read your stuff? What's your distribution strategy? Because this post was popping up everywhere. And then people on Twitter were like, Nicholas Garlini wrote this. Like, what's his handle? It's like, he doesn't have it. It's like, how did you find it? What's the story?Nicholas [00:33:07]: So I have an RSS feed and an email list. And that's it. I don't like most social media things. On principle, I feel like they have some harms. As a person, I have a problem when people say things that are wrong on the internet. And I would get nothing done if I would have a Twitter. I would spend all of my time correcting people and getting into fights. And so I feel like it is just useful for me for this not to be an option. I tend to just post things online. Yeah, it's a very good question. I don't know how people find it. I feel like for some things that I write, other people think it resonates with them. And then they put it on Twitter. And...Swyx [00:33:43]: Hacker News as well.Nicholas [00:33:44]: Sure, yeah. I am... Because my day job is doing research, I get no value for having this be picked up. There's no whatever. I don't need to be someone who has to have this other thing to give talks. And so I feel like I can just say what I want to say. And if people find it useful, then they'll share it widely. You know, this one went pretty wide. I wrote a thing, whatever, sometime late last year, about how to recover data off of an Apple profile drive from 1980. This probably got, I think, like 1000x less views than this. But I don't care. Like, that's not why I'm doing this. Like, this is the benefit of having a thing that I actually care about, which is my research. I would care much more if that didn't get seen. This is like a thing that I write because I have some thoughts that I just want to put down.Swyx [00:34:32]: Yeah. I think it's the long form thoughtfulness and authenticity that is sadly lacking sometimes in modern discourse that makes it attractive. And I think now you have a little bit of a brand of you are an independent thinker, writer, person, that people are tuned in to pay attention to whatever is next coming.Nicholas [00:34:52]: Yeah, I mean, this kind of worries me a little bit. I don't like whenever I have a popular thing that like, and then I write another thing, which is like entirely unrelated. Like, I don't, I don't... You should actually just throw people off right now.Swyx [00:35:01]: Exactly.Nicholas [00:35:02]: I'm trying to figure out, like, I need to put something else online. So, like, the last two or three things I've done in a row have been, like, actually, like, things that people should care about.Swyx [00:35:10]: Yes. So, I have a couple of things.Nicholas [00:35:11]: I'm trying to figure out which one do I put online to just, like, cull the list of people who have subscribed to my email.Swyx [00:35:16]: And so, like, tell them, like,Nicholas [00:35:16]: no, like, what you're here for is not informed, well-thought-through takes. Like, what you're here for is whatever I want to talk about. And if you're not up for that, then, like, you know, go away. Like, this is not what I want out of my personal website.Swyx [00:35:27]: So, like, here's, like, top 10 enemies or something.Alessio [00:35:30]: What's the next project you're going to work on that is completely unrelated to research LLMs? Or what games do you want to port into the browser next?Swyx [00:35:39]: Okay. Yeah.Nicholas [00:35:39]: So, maybe.Swyx [00:35:41]: Okay.Nicholas [00:35:41]: Here's a fun question. How much data do you think you can put on a single piece of paper?Swyx [00:35:47]: I mean, you can think about bits and atoms. Yeah.Nicholas [00:35:49]: No, like, normal printer. Like, I gave you an office printer. How much data can you put on a piece of paper?Alessio [00:35:54]: Can you re-decode it? So, like, you know, base 64A or whatever. Yeah, whatever you want.Nicholas [00:35:59]: Like, you get normal off-the-shelf printer, off-the-shelf scanner. How much data?Swyx [00:36:03]: I'll just throw out there. Like, 10 megabytes. That's enormous. I know.Nicholas [00:36:07]: Yeah, that's a lot.Swyx [00:36:10]: Really small fonts. That's my question.Nicholas [00:36:12]: So, I have a thing. It does about a megabyte.Swyx [00:36:14]: Yeah, okay.Nicholas [00:36:14]: There you go. I was off by an order of magnitude.Swyx [00:36:16]: Yeah, okay.Nicholas [00:36:16]: So, in particular, it's about 1.44 megabytes. A floppy disk.Swyx [00:36:21]: Yeah, exactly.Nicholas [00:36:21]: So, this is supposed to be the title at some point. It's a floppy disk.Swyx [00:36:24]: A paper is a floppy disk. Yeah.Nicholas [00:36:25]: So, this is a little hard because, you know. So, you can do the math and you get 8.5 by 11. You can print at 300 by 300 DPI. And this gives you 2 megabytes. And so, every single pixel, you need to be able to recover up to like 90 plus percent. Like, 95 percent. Like, 99 point something percent accuracy. In order to be able to actually decode this off the paper. This is one of the things that I'm considering. I need to get a couple more things working for this. Where, you know, again, I'm running into some random problems. But this is probably, this will be one thing that I'm going to talk about. There's this contest called the International Obfuscated C-Code Contest, which is amazing. People try and write the most obfuscated C code that they can. Which is great. And I have a submission for that whenever they open up the next one for it. And I'll write about that submission. I have a very fun gate level emulation of an old CPU that runs like fully precisely. And it's a fun kind of thing. Yeah.Swyx [00:37:20]: Interesting. Your comment about the piece of paper reminds me of when I was in college. And you would have like one cheat sheet that you could write. So, you have a formula, a theoretical limit for bits per inch. And, you know, that's how much I would squeeze in really, really small. Yeah, definitely.Nicholas [00:37:36]: Okay.Swyx [00:37:37]: We are also going to talk about your benchmarking. Because you released your own benchmark that got some attention, thanks to some friends on the internet. What's the story behind your own benchmark? Do you not trust the open source benchmarks? What's going on there?Nicholas [00:37:51]: Okay. Benchmarks tell you how well the model solves the task the benchmark is designed to solve. For a long time, models were not useful. And so, the benchmark that you tracked was just something someone came up with, because you need to track something. All of deep learning exists because people tried to make models classify digits and classify images into a thousand classes. There is no one in the world who cares specifically about the problem of distinguishing between 300 breeds of dog for an image that's 224 or 224 pixels. And yet, like, this is what drove a lot of progress. And people did this not because they cared about this problem, because they wanted to just measure progress in some way. And a lot of benchmarks are of this flavor. You want to construct a task that is hard, and we will measure progress on this benchmark, not because we care about the problem per se, but because we know that progress on this is in some way correlated with making better models. And this is fine when you don't want to actually use the models that you have. But when you want to actually make use of them, it's important to find benchmarks that track with whether or not they're useful to you. And the thing that I was finding is that there would be model after model after model that was being released that would find some benchmark that they could claim state-of-the-art on and then say, therefore, ours is the best. And that wouldn't be helpful to me to know whether or not I should then switch to it. So the argument that I tried to lay out in this post is that more people should make benchmarks that are tailored to them. And so what I did is I wrote a domain-specific language that anyone can write for and say, you can take tasks that you have wanted models to solve for you, and you can put them into your benchmark that's the thing that you care about. And then when a new model comes out, you benchmark the model on the things that you care about. And you know that you care about them because you've actually asked for those answers before. And if the model scores well, then you know that for the kinds of things that you have asked models for in the past, it can solve these things well for you. This has been useful for me because when another model comes out, I can run it. I can see, does this solve the kinds of things that I care about? And sometimes the answer is yes, and sometimes the answer is no. And then I can decide whether or not I want to use that model or not. I don't want to say that existing benchmarks are not useful. They're very good at measuring the thing that they're designed to measure. But in many cases, what that's designed to measure is not actually the thing that I want to use it for. And I expect that the way that I want to use it is different the way that you want to use it. And I would just like more people to have these things out there in the world. And the final reason for this is, it is very easy. If you want to make a model good at some benchmark, to make it good at that benchmark, you can find the distribution of data that you need and train the model to be good on the distribution of data. And then you have your model that can solve this benchmark well. And by having a benchmark that is not very popular, you can be relatively certain that no one has tried to optimize their model for your benchmark.Swyx [00:40:40]: And I would like this to be-Nicholas [00:40:40]: So publishing your benchmark is a little bit-Swyx [00:40:43]: Okay, sure.Nicholas [00:40:43]: Contextualized. So my hope in doing this was not that people would use mine as theirs. My hope in doing this was that- You should make yours. Yes, you should make your benchmark. And if, for example, there were even a very small fraction of people, 0.1% of people who made a benchmark that was useful for them, this would still be hundreds of new benchmarks that- not want to make one myself, but I might want to- I might know the kinds of work that I do is a little bit like this person, a little bit like that person. I'll go check how it is on their benchmarks. And I'll see, roughly, I'll get a good sense of what's going on. Because the alternative is people just do this vibes-based evaluation thing, where you interact with the model five times, and you see if it worked on the kinds of things that you just like your toy questions. But five questions is a very low bit output from whether or not it works for this thing. And if you could just automate running it 100 questions for you, it's a much better evaluation. So that's why I did this.Swyx [00:41:37]: Yeah, I like the idea of going through your chat history and actually pulling out real-life examples. I regret to say that I don't think my chat history is used as much these days, because I'm using Cursor, the native AI IDE. So your examples are all coding related. And the immediate question is, now that you've written the How I Use AI post, which is a little bit broader, are you able to translate all these things to evals? Are some things unevaluable?Nicholas [00:42:03]: Right. A number of things that I do are harder to evaluate. So this is the problem with a benchmark, is you need some way to check whether or not the output was correct. And so all of the kinds of things that I can put into the benchmark are the kinds of things that you can check. You can check more things than you might have thought would be possible if you do a little bit of work on the back end. So for example, all of the code that I have the model write, it runs the code and sees whether the answer is the correct answer. Or in some cases, it runs the code, feeds the output to another language model, and the language model judges was the output correct. And again, is using a language model to judge here perfect? No. But like, what's the alternative? The alternative is to not do it. And what I care about is just, is this thing broadly useful for the kinds of questions that I have? And so as long as the accuracy is better than roughly random, like, I'm okay with this. I've inspected the outputs of these, and like, they're almost always correct. If you ask the model to judge these things in the right way, they're very good at being able to tell this. And so, yeah, I probably think this is a useful thing for people to do.Alessio [00:43:04]: You complain about prompting and being lazy and how you do not want to tip your model and you do not want to murder a kitten just to get the right answer. How do you see the evolution of like prompt engineering? Even like 18 months ago, maybe, you know, it was kind of like really hot and people wanted to like build companies around it. Today, it's like the models are getting good. Do you think it's going to be less and less relevant going forward? Or what's the minimum valuable prompt? Yeah, I don't know.Nicholas [00:43:29]: I feel like a big part of making an agent is just like a fancy prompt that like, you know, calls back to the model again. I have no opinion. It seems like maybe it turns out that this is really important. Maybe it turns out that this isn't. I guess the only comment I was making here is just to say, oftentimes when I use a model and I find it's not useful, I talk to people who help make it. The answer they usually give me is like, you're using it wrong. Which like reminds me very much of like that you're holding it wrong from like the iPhone kind of thing, right? Like, you know, like I don't care that I'm holding it wrong. I'm holding it that way. If the thing is not working with me, then like it's not useful for me. Like it may be the case that there exists a way to ask the model such that it gives me the answer that's correct, but that's not the way I'm doing it. If I have to spend so much time thinking about how I want to frame the question, that it would have been faster for me just to get the answer. It didn't save me any time. And so oftentimes, you know, what I do is like, I just dump in whatever current thought that I have in whatever ill-formed way it is. And I expect the answer to be correct. And if the answer is not correct, like in some sense, maybe the model was right to give me the wrong answer. Like I may have asked the wrong question, but I want the right answer still. And so like, I just want to sort of get this as a thing. And maybe the way to fix this is you have some default prompt that always goes into all the models or something, or you do something like clever like this. It would be great if someone had a way to package this up and make a thing I think that's entirely reasonable. Maybe it turns out that as models get better, you don't need to prompt them as much in this way. I just want to use the things that are in front of me.Alessio [00:44:55]: Do you think that's like a limitation of just how models work? Like, you know, at the end of the day, you're using the prompt to kind of like steer it in the latent space. Like, do you think there's a way to actually not make the prompt really relevant and have the model figure it out? Or like, what's the... I mean, you could fine tune itNicholas [00:45:10]: into the model, for example, that like it's supposed to... I mean, it seems like some models have done this, for example, like some recent model, many recent models. If you ask them a question, computing an integral of this thing, they'll say, let's think through this step by step. And then they'll go through the step by step answer. I didn't tell it. Two years ago, I would have had to have prompted it. Think step by step on solving the following thing. Now you ask them the question and the model says, here's how I'm going to do it. I'm going to take the following approach and then like sort of self-prompt itself.Swyx [00:45:34]: Is this the right way?Nicholas [00:45:35]: Seems reasonable. Maybe you don't have to do it. I don't know. This is for the people whose job is to make these things better. And yeah, I just want to use these things. Yeah.Swyx [00:45:43]: For listeners, that would be Orca and Agent Instruct. It's the soda on this stuff. Great. Yeah.Alessio [00:45:49]: That's a few shot. It's included in the lazy prompting. Like, do you do a few shot prompting? Like, do you collect some examples when you want to put them in? Or...Nicholas [00:45:57]: I don't because usually when I want the answer, I just want to get the answer. Brutal.Swyx [00:46:03]: This is hard mode. Yeah, exactly.Nicholas [00:46:04]: But this is fine.Swyx [00:46:06]: I want to be clear.Nicholas [00:46:06]: There's a difference between testing the ultimate capability level of the model and testing the thing that I'm doing with it. What I'm doing is I'm not exercising its full capability level because there are almost certainly better ways to ask the questions and sort of really see how good the model is. And if you're evaluating a model for being state of the art, this is ultimately what I care about. And so I'm entirely fine with people doing fancy prompting to show me what the true capability level could be because it's really useful to know what the ultimate level of the model could be. But I think it's also important just to have available to you how good the model is if you don't do fancy things.Swyx [00:46:39]: Yeah, I would say that here's a divergence between how models are marketed these days versus how people use it, which is when they test MMLU, they'll do like five shots, 25 shots, 50 shots. And no one's providing 50 examples. I completely agree.Nicholas [00:46:54]: You know, for these numbers, the problem is everyone wants to get state of the art on the benchmark. And so you find the way that you can ask the model the questions so that you get state of the art on the benchmark. And it's good. It's legitimately good to know. It's good to know the model can do this thing if only you try hard enough. Because it means that if I have some task that I want to be solved, I know what the capability level is. And I could get there if I was willing to work hard enough. And the question then is, should I work harder and figure out how to ask the model the question? Or do I just do the thing myself? And for me, I have programmed for many, many, many years. It's often just faster for me just to do the thing than to figure out the incantation to ask the model. But I can imagine someone who has never programmed before might be fine writing five paragraphs in English describing exactly the thing that they want and have the model build it for them if the alternative is not. But again, this goes to all these questions of how are they going to validate? Should they be trusting the output? These kinds of things.Swyx [00:47:49]: One problem with your eval paradigm and most eval paradigms, I'm not picking on you, is that we're actually training these things for chat, for interactive back and forth. And you actually obviously reveal much more information in the same way that asking 20 questions reveals more information in sort of a tree search branching sort of way. Then this is also by the way the problem with LMSYS arena, right? Where the vast majority of prompts are single question, single answer, eval, done. But actually the way that we use chat things, in the way, even in the stuff that you posted in your how I use AI stuff, you have maybe 20 turns of back and forth. How do you eval that?Nicholas [00:48:25]: Yeah. Okay. Very good question. This is the thing that I think many people should be doing more of. I would like more multi-turn evals. I might be writing a paper on this at some point if I get around to it. A couple of the evals in the benchmark thing I have are already multi-turn. I mentioned 20 questions. I have a 20 question eval there just for fun. But I have a couple others that are like, I just tell the model, here's my get thing, figure out how to cherry pick off this other branch and move it over there. And so what I do is I just, I basically build a tiny little agency thing. I just ask the model how I do it. I run the thing on Linux. This is what I want a Docker for. I spin up a Docker container. I run whatever the model told me the output to do is. I feed the output back into the model. I repeat this many rounds. And then I check at the very end, does the git commit history show that it is correctly cherry picked in
Wir kennen es alle: die Aufgaben stapeln sich auf unserem Schreibtisch und der Kopf raucht. Wie man dem entgegenwirken kann und welche Rolle Timeboxing dabei spielt, besprechen wir in dieser Folge. Viel Spaß! Literatur: https://hbr.org/2018/12/how-timeboxing-works-and-why-it-will-make-you-more-productive Marc Zao-Sanders: Timeboxing Impressum (gewert-consulting.de) Kontakt: leadershipleichtgelernt@gmx.de
In dieser Folge gehe ich auf die 3 Begriffe Timeblocking, Timeboxing und Timebatching ein und wie du diese unterschiedlich anwenden kannst. Kannst du die Unterschiede? --- Send in a voice message: https://podcasters.spotify.com/pod/show/sandra-balje/message
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In this episode of The Brainy Business podcast, host Melina Palmer and guest Marc Zao-Sanders reveal how the technique of timeboxing transformed not just his productivity but his life. In this episode, you'll hear a genuine transformation story from chaos to structured success, and how intentional living can lead to profound personal and professional growth. Marc and Melina dissect the practicalities of digital organization, intentional decisions, and share personal experiences that bring the concept to life. Learn why timeboxing is more than just a productivity hack – it's a path to a more purposeful life. If you're looking to make meaningful changes to your daily routine, this episode offers wisdom and actionable steps without the hype. Join us for a dose of reality about the power of scheduling and prioritizing that could truly reshape your outlook on work and life. In this episode: Maximize Productivity: Unlock the benefits of timeboxing to supercharge your daily output and efficiency. Harness Time Management: Learn the art of implementing timeboxing, a powerful technique to take control of your schedule and accomplish more. Optimize Productivity: Explore the nuances between timeboxing and time blocking to revolutionize your approach to time management. Prioritize Effectively: Discover strategies for prioritizing tasks using timeboxing, ensuring maximum impact in minimal time. Foster Collaboration: Strengthen team collaboration with shared calendars, enhancing efficiency and synergy within your organization. Show Notes: 00:00:00 - Introduction Melina introduces Marc Zhao-Sanders, author of Timeboxing, and sets the stage for the conversation about the psychology of time management and productivity. 00:03:32 - Marc's Background and the Origin of Timeboxing Marc shares his journey from being disorganized at the start of his career to creating his system of personal productivity and stumbling upon the concept of timeboxing through an article in Harvard Business Review. 00:08:42 - Success of Timeboxing Marc discusses the popularity of timeboxing, the TikTok video that led to a book deal, and the widespread reach of the concept with translations in 33 languages. 00:11:35 - The Power of Timeboxing for Everyone Marc emphasizes that timeboxing is not just for naturally organized individuals. Still, it can benefit anyone, especially in terms of mental health and feeling in control of one's time and productivity. 00:14:07 - Differentiating Timeboxing and Time Blocking Marc provides a four-part definition of timeboxing, highlighting the intentional decision-making, scheduling, and flexibility of the practice, and distinguishes it from time blocking as a more comprehensive approach to managing time. 00:15:05 - The Importance of Timeboxing Marc discusses the importance of timeboxing in making decisions and spending time intentionally, free from distractions. This allows for prioritizing tasks and committing to single-tasking. 00:16:17 - Defining Timeboxing Marc defines time boxing as scheduling specific blocks of time to work on tasks, committing to single-tasking, and ensuring task completion to an acceptable standard within the allocated time. 00:17:36 - Parkinson's Law and Timeboxing Marc talks about Parkinson's Law and how time expands to fill the time allowed. He emphasizes the importance of setting deadlines and timeboxing to avoid endless, frustrating tasks. 00:20:01 - Overcoming Timeboxing Challenges Marc addresses the challenges of timeboxing, especially for new tasks. He recommends starting small with time boxes and gradually building confidence in the process. 00:24:51 - The Power of One Thing at a Time Marc emphasizes the productivity of focusing on one thing at a time and the mantra "one thing at a time" to avoid multitasking and increase efficiency. He also discusses the satisfaction of completing tasks according to one's plan. 00:29:58 - Efficient To-Do List Management Marc explains how to efficiently manage a to-do list using timeboxing and spreadsheet functionality. He emphasizes the 80/20 rule and the importance of prioritizing tasks. 00:31:41 - Ranking and Sorting Tasks Marc discusses the importance of ranking and sorting tasks based on urgency and importance. He also addresses the issue of prioritizing tasks and provides advice on how to handle items with high rankings. 00:32:53 - Calibrating Priorities Marc shares his approach to collapsing urgency and importance, and emphasizes the need for calibration when dealing with tasks that are ranked highly. He also discusses the value of retaining tasks for future reference. 00:36:56 - Data-Driven Time Management Marc highlights the value of using hashtags and search terms in digital calendars for time management insights. He emphasizes the importance of quantifying and prioritizing activities, such as learning and reading, through intentional time boxing. 00:43:42 - Living an Intentional Life Marc discusses the concept of living an intentional life and emphasizes the importance of setting milestones and time boxing for aspirational activities, such as travel planning. He encourages planning to achieve desired outcomes. 00:44:24 - The Importance of Timeboxing and Planning Marc discusses the significance of planning and timeboxing to achieve goals. He emphasizes the need for setting specific milestones rather than vague timelines like "soon" or "next week." 00:46:33 - Accountability and Collaboration Marc and Melina talk about accountability and collaboration in the context of timeboxing. They explore the positive effects of timeboxing on reassurance and realistic task allocation within a team. 00:47:29 - Digital Calendar Sharing and Transparency Marc delves into the benefits of sharing digital calendars within a team, highlighting the positive impact on task dependencies and realistic time allocation. He also touches on the potential positive pressure created by the Hawthorne effect. 00:49:11 - Using Emojis in Timeboxing The conversation shifts to the use of emojis in timeboxing and calendar management. Marc explains the light-hearted and visually pleasant aspect of incorporating emojis into time management, adding a touch of fun to the process. 00:51:48 - Conclusion What stuck with you while listening to the episode? What are you going to try? Come share it with Melina on social media -- you'll find her as @thebrainybiz everywhere and as Melina Palmer on LinkedIn. Thanks for listening. Don't forget to subscribe on Apple Podcasts or Android. If you like what you heard, please leave a review on iTunes and share what you liked about the show. I hope you love everything recommended via The Brainy Business! Everything was independently reviewed and selected by me, Melina Palmer. So you know, as an Amazon Associate I earn from qualifying purchases. That means if you decide to shop from the links on this page (via Amazon or others), The Brainy Business may collect a share of sales or other compensation. Let's connect: Melina@TheBrainyBusiness.com The Brainy Business® on Facebook The Brainy Business on Twitter The Brainy Business on Instagram The Brainy Business on LinkedIn Melina on LinkedIn The Brainy Business on Youtube Connect with Marc: Filtered Blog Marc's Website LinkedIn Learn and Support The Brainy Business: Check out and get your copies of Melina's Books. Get the Books Mentioned on (or related to) this Episode: Timeboxing, by Marc Zao-Sanders Indistractable, by Nir Eyal The Life Changing Magic of Tidying Up, by Marie Kondo Work Well, Play More, by Marcey Rader Come Up For Air, by Nick Sonnenberg Top Recommended Next Episode: Precommitment (ep 120) Already Heard That One? Try These: Time Pressure (ep 74) Bikeshedding (ep 99) Habits (ep 256) Nir Eyal Interview (ep 290) Unmasking the Hawthorne Effect (ep 364) Other Important Links: Brainy Bites - Melina's LinkedIn Newsletter How Timeboxing Works and Why It Will Make You More Productive To Do Lists Don't Work TEDx Portland
Second City Works presents "Getting to Yes, And" on WGN Plus
Want a productivity hack that will change your life? Kelly connects with Marc Zao-Sanders, the co-founder and CEO of filtered.com to discuss his new book “Timeboxing: The Power of Doing One Thing at a Time.” “Timeboxing is the flexible friend of any and all other time management techniques.” “Disconcertingly organized people weren't born that way.” “Time […]
Timeboxing means dividing your day into 15-60 minute slots, based on your priorities, and then sticking to those slots as you dive into the business of work. If that sounds great, it is. If it sounds easy, it isn't. In this week's episode of The Mind Tools L&D Podcast, author Marc Zao-Sanders joins Ross G to give him advice on timeboxing his life. We discuss: · The benefits of timeboxing; · How email is the ‘killer', and what to do about it; · The difficulties that Ross had implementing timeboxing, and what he could do differently. The article Marc wrote for HBR was ‘How timeboxing works and why it will make you more productive'. Find out more about timeboxing from Mind Tools. The book, Timeboxing, is available from Penguin. Marc's substack is One Thing at a Time. The company Marc runs is Filtered. In ‘What I Learned This Week', Ross discussed the rising popularity of the ‘dumbphone'. For more from us, including access to our back catalogue of podcasts, visit mindtools.com/business. There, you'll also find details of our award-winning performance support toolkit, our off-the-shelf e-learning, and our custom work. Connect with our speakers If you'd like to share your thoughts on this episode, connect with our speakers: · Ross Garner · Marc Zao-Sanders
Bienvenue dans Pro-Pulse ! Dans ce deuxième épisode, on inaugure la série "Mot du jour » en décryptant le timeboxing, une méthode de gestion du temps qui peut transformer votre façon d'aborder votre emploi du temps...Comment cette approche peut-elle vous aider à mieux organiser vos journées, à rester concentré sur vos objectifs et à éviter la procrastination ? Quelles astuces concrètes et rapides pouvez-vous mettre en place pour bien « timeboxer » ?Bonne écoute !→ Pour aller plus loin, l'Institut vous propose des formations sur ce thème. Découvrez les en cliquant ICI.———Crédits Auteur de ce podcast : Marie-Laure CuzacqRéalisation et montage : Chloé Lefèvre pour l'institut François BocquetVoix : Emma Bouchet et Mathis H.Hébergé par Ausha. Visitez ausha.co/politique-de-confidentialite pour plus d'informations.
Bereit für deine 8 Wochen Transformation? In dieser inspirierenden Episode über Flow, Lebensgestaltung und persönlicher Entwicklung teile ich meine wertvollsten Einsichten aus meinen Coaching-Erfahrungen mit dir, wenn es darum geht, den Körper, Geist, das Leben und auch den Beruf so zu transformieren, dass es deine kühnsten Träume und Wünsche übersteigt. Dazu teile ich die wichtigsten Erkenntnisse aus meinem flowX-Programm, mit dem ich gesundheitsbewusste Unternehmerinnen und Unternehmer dabei unterstütze, innerhalb von nur acht kurzen Wochen in die Person zu schlüpfen, die sie schon immer sein wollten. Wenn du nach dem Ansehen der Folge selbst Lust hast, dich mit den besten Methoden und Strategien der Biohacker zu transformieren und Teil der wachsenden flowX Community zu werden, dann bewerbe dich für die nächste Runde (beginnt im Mai 2024). ► Bewirb dich jetzt: http://www.flowgrade.de/flowx Kurz zum Inhalt dieser Folge: Ich teile mit dir meine eigenen Erfahrungen und die lebensverändernden Einsichten, die ich als Coach des flowX-Programms gewonnen habe. Wir sprechen über die Kraft der Entscheidung, den Mut, den ersten Schritt zu wagen, und wie die Unterstützung einer Gemeinschaft den Unterschied machen kann auf dem Weg zu persönlichem Wachstum und Erfüllung. Ich führe dich durch die verschiedenen Aspekte des Programms – von Zeitmanagement und Time-Boxing über die Steigerung von Selbstwert und Einkommen bis hin zu einem ganzheitlichen Ansatz für eine umfassende Transformation. Dazu teile ich einige Erfahrungen meiner Teilnehmer, den physischen und biologischen Veränderungen, die sie durchgemacht haben, und wie Fokus, Ausdauer und der Zustand des Flows ihr Leben zum Besseren verändert haben. Zudem werfen wir einen Blick auf die Anwendung und individuelle Anpassung des Programms, diskutieren Preis und Inhalt und tauchen ein in den flowX Alumni Club und meine Vision für die Zukunft. Höre dir diese Episode an und entdecke, was es bedeutet, in 8 Wochen ein neues Ich zu werden. Wer weiss, vielleicht wird sie sogar den Funken für deine eigene Transformation in dir entzünden. Go for Flow! ► Zum Programm: http://www.flowgrade.de/flowx ► Kontakt: • YouTube Kanal abonnieren https://www.youtube.com/@flowgrade/?sub_confirmation=1 • Website https://www.flowgrade.de • Flowgrade Instagram https://www.instagram.com/flowgrade • FlowTribe https://flowtribe.community • Max Gotzler's Instagram https://www.instagram.com/max_gotzler • Facebook https://www.facebook.com/biotrakr • Twitter https://www.twitter.com/flowgrade • LinkedIn https://www.linkedin.com/company/biotrakr • Mail info@flowgrade.de ► Kapitel: 00:00 Die 8 Wochen Transformation 01:46 Die Idee hinter dem Programm 06:26 Glaubenssätze und Krisen 07:51 Die richtigen Entscheidungen treffen 10:42 Die Bedeutung von Flow 14:40 Module und der Austausch in der Gruppe 19:23 Die Bedeutung von Zeit und Glück 19:53 Zeitmanagement und Timeboxing 23:08 Was Gehalt mit Selbstwert zu tun hat 26:01 Ganzheitliches Denken und Transformation 28:26 Erfahrungen der Teilnehmer 29:50 Physische Erfahrung und biologische Veränderungen 31:44 Bewerbe dich für das FlowX Programm 34:09 Programmdetails und Preispunkt 38:49 FlowX Alumni-Club #flowgrade #biohacking #podcast #transformation
From work to chores to entertaining distractions, there are many options for what you can be doing at any moment in the modern world. We often endlessly toggle between these options and, as a result, feel frazzled and frustratingly unproductive. We feel ever haunted by the question, "What should I be doing right now?" (Or "What am I even doing right now?")My guest will share a simple but effective productivity method that will quash this feeling of overwhelm, answer that question, and help you make much better use of your time. Marc Zao-Sanders is the CEO and co-founder of filtered.com, a learning tech company, and the author of Timeboxing: The Power of Doing One Thing at a Time. In the first half of our conversation, we unpack what timeboxing — which brings your calendar and to-do list together — is all about and its benefits as a time management system, including how it can help you get more done, live with greater intention and freedom, and even create a log of memories. In the second half of our conversation, we get into the practicalities of timeboxing, from how to capture the to-dos that will go on your calendar to how to deal with things that might pull you away from it. We end our conversation with how you can get started with timeboxing right now and have a more focused, productive, and satisfying day tomorrow.Resources Related to the PodcastAoM Podcast #543: Learn the System for Getting Things Done With David AllenAoM Podcast #972: Down With Pseudo-Productivity — Why We Need to Transform the Way We Work With Cal NewportAoM Article: The Eisenhower Decision Matrix — How to Distinguish Between Urgent and Important Tasks and Make Real Progress in Your LifeAoM Podcast #768: Become a Focused MonotaskerAoM Article: The Productivity Tool I Use to Get Things DoneAoM Article: A Formula for Success — The Power of Implementation IntentionsConnect With Marc Zao-SandersMarc's websiteMarc on LinkedIn
Are you living an intentional life? On this Live Greatly podcast episode, Kristel Bauer sits down with Marc Zao-Sanders, author of, 'TIMEBOXING: The Power of Doing One Thing At a Time.' Kristel and Marc discuss how timeboxing can help you avoid regret, minimize overwhelm and fill your work and life with the things that matter most to you. Tune in now! Key Takeaways From This Episode What timeboxing is A look into Marc's popular Harvard Business Review article on Timeboxing and how it led to a book deal How to start Timeboxing How to use Timeboxing in your life, not just work How Timeboxing can help you live an intentional life Why you should be focusing on one task at a time How Timeboxing can help you avoid living a life of regret Why you shouldn't be striving for perfection About Marc Zao-Sanders: MARC ZAO-SANDERS is the CEO and co-founder of filtered.com, a learning tech company. He regularly writes about algorithms, learning and productivity in Scientific American, Harvard Business Review and MIT Sloan Management Review. Marc is the author of 'TIMEBOXING: The Power of Doing One Thing At a Time. TIMEBOXING is a comprehensive guide to carefully and intentionally selecting what to do, specifying start and finish times, focusing solely on that single activity, and getting it done to an acceptable standard within that timeframe. Connect with Marc Website: https://marczaosanders.com/ Buy Marc's Book: https://marczaosanders.com/book/ Instagram: https://www.instagram.com/marczaosanders/ LinkedIn: https://www.linkedin.com/in/marczs/ About the Host of the Live Greatly podcast, Kristel Bauer: Kristel Bauer is a corporate wellness expert, popular keynote and TEDx speaker, and the host of top-rated podcast, “Live Greatly,” a show frequently ranked in the top 1% for self-improvement. Kristel is an Integrative Medicine Fellow & Physician Assistant with clinical experience in Integrative Psychiatry, giving her a unique perspective into optimizing mental well-being and attaining a mindset for more happiness and success in the workplace and beyond. Kristel decided to leave clinical practice in 2019 when she founded her wellness platform “Live Greatly” to share her message around well-being and success on a larger scale. With a mission to support companies and individuals on their journeys for more happiness, success, and well-being, Kristel taps into her unique background in healthcare, business, and media, to provide invaluable insights into high power habits, leadership development, mental well-being, peak performance, resilience, sales, success, wellness at work, and a modern approach to work/life balance. Kristel is a contributing writer for Entrepreneur and she is an influencer in the business and wellness space having been recognized as a Top 10 Social Media Influencer of 2021 in Forbes. A popular speaker on a variety of topics, Kristel has presented to groups at APMP, Bank of America, Commercial Metals Company, General Mills, Northwestern University, Mazda, Santander Bank and many more. She has been featured in Forbes, Forest & Bluff Magazine, Authority Magazine & Podcast Magazine, has contributed to CEOWORLD Magazine & Real Leaders Magazine, and has appeared on ABC 7 Chicago, WGN Daytime Chicago, Fox 4's WDAF-TV's Great Day KC and Ticker News. Kristel lives in the Chicago area with her husband and their 2 children. She can be booked for speaking engagements worldwide. To Book Kristel as a speaker for your next event, click here. Website: www.livegreatly.co Follow Kristel Bauer on: Instagram: @livegreatly_co LinkedIn: Kristel Bauer Twitter: @livegreatly_co Facebook: @livegreatly.co Youtube: Live Greatly, Kristel Bauer To Watch Kristel Bauer's TEDx talk of Redefining Work/Life Balance in a COVID-19 World click here. Click HERE to check out Kristel's corporate wellness and leadership blog Click HERE to check out Kristel's Travel and Wellness Blog Disclaimer: The contents of this podcast are intended for informational and educational purposes only. Always seek the guidance of your physician for any recommendations specific to you or for any questions regarding your specific health, your sleep patterns changes to diet and exercise, or any medical conditions. Always consult your physician before starting any supplements or new lifestyle programs. All information, views and statements shared on the Live Greatly podcast are purely the opinions of the authors, and are not medical advice or treatment recommendations. They have not been evaluated by the food and drug administration. Opinions of guests are their own and Kristel Bauer & this podcast does not endorse or accept responsibility for statements made by guests. Neither Kristel Bauer nor this podcast takes responsibility for possible health consequences of a person or persons following the information in this educational content. Always consult your physician for recommendations specific to you.
Discover all of the podcasts in our network, search for specific episodes, get the Optimal Living Daily workbook, and learn more at: OLDPodcast.com. Episode 1246: Discover the transformative power of timeboxing through Nir Eyal's insightful exploration. Eyal demystifies this highly effective time management technique, showcasing its superiority over traditional to-do lists and revealing practical strategies to overcome common pitfalls. Embrace timeboxing to master your schedule, enhance productivity, and live with intention. Read along with the original article(s) here: https://www.nirandfar.com/timeboxing/ Quotes to ponder: "You can't call something a distraction unless you know what it is distracting you from." "Timeboxing is among the most well-studied and powerful methods we know for getting things done." "Discipline equals freedom. We all know we do our best work when we have constraints, and timeboxing gives us just that in the form of time on our schedules." Learn more about your ad choices. Visit megaphone.fm/adchoices
Discover all of the podcasts in our network, search for specific episodes, get the Optimal Living Daily workbook, and learn more at: OLDPodcast.com. Episode 1246: Discover the transformative power of timeboxing through Nir Eyal's insightful exploration. Eyal demystifies this highly effective time management technique, showcasing its superiority over traditional to-do lists and revealing practical strategies to overcome common pitfalls. Embrace timeboxing to master your schedule, enhance productivity, and live with intention. Read along with the original article(s) here: https://www.nirandfar.com/timeboxing/ Quotes to ponder: "You can't call something a distraction unless you know what it is distracting you from." "Timeboxing is among the most well-studied and powerful methods we know for getting things done." "Discipline equals freedom. We all know we do our best work when we have constraints, and timeboxing gives us just that in the form of time on our schedules." Learn more about your ad choices. Visit megaphone.fm/adchoices
In this episode, we're joined by best-selling author and behavioral design expert Nir Eyal, as we delve into strategies for empowering children to thrive in a world saturated with digital distractions. Discover the essential psychological nutrients of competency, autonomy, and relatedness from Self-Determination Theory, and learn how to integrate them into parenting and educational practices to develop focused, resilient minds. Key Points from the Episode: - The profound impact of Self-Determination Theory on understanding human motivation and its relevance in child development.- Exploring the balance between structured schedules and the autonomy children need for emotional health and resilience.- The role of family interactions in managing screen time and the establishment of no-phone zones.- Techniques and strategies to help children navigate digital distractions and make intentional choices about technology use.- The importance of natural consequences in parenting and how to involve kids in setting rules and understanding outcomes.- The Super Mario effect and how failure can be a learning tool to adjust approaches to challenges.- Time boxing as a method for setting priorities and intentionally using time for both adults and children. Chapter Summaries: - (0:00:03) The Impact of Self-Determination Theory - Discussion on competency, autonomy, and relatedness as psychological nutrients and their role in combating technology overuse.- (0:08:12) Autonomy and Over-Scheduling's Impact on Children's Development - How modern society's over-scheduling can limit children's autonomy and the benefits of unstructured playtime.- (0:19:26) Technology's Impact on Family and Interactions - The importance of shared family meals, parental engagement, and creating new social antibodies to maintain core values amidst digital distractions.- (0:26:35) Managing Screen Time and Distraction - Understanding 'traction' versus 'distraction,' and how intent defines our engagement with technology.- (0:36:18) Parenting, Technology, and Natural Consequences - Addressing the language around technology use and promoting autonomy through understanding and natural consequences.- (0:40:35) Help Kids Manage Digital Distractions - Strategies for helping kids cope with digital distractions, including the Super Mario effect and environmental shaping.- (0:51:19) Time Boxing and Setting Priorities Power - The benefits of time boxing over to-do lists and modeling healthy tech habits for children.- (1:02:20) The Power of Being Indistractable - Embracing forethought as the antidote to impulsiveness and sharing the message of becoming indistractable. About Nir:Nir Eyal, a writer, consultant, and teacher, specializes in the intersection of psychology, technology, and business. He has taught at the Stanford Graduate School of Business and is the author of two bestselling books: "Hooked: How to Build Habit-Forming Products" and "Indistractable: How to Control Your Attention and Choose Your Life." Get in touch with Nir:www.nirandfar.comThe book, it's: http://geni.us/indistractableIndistractable bonus content: http://www.nirandfar.com/indistractable/Indistractable summary article: https://www.nirandfar.com/skill-of-the-future/Timeboxing article: https://www.nirandfar.com/timeboxing/His free habit tracker tool: https://www.nirandfar.com/habit-tracker/His free schedule maker tool: https://www.nirandfar.com/schedule-maker/His list of my top articles: https://www.nirandfar.com/best-articles/ #IndistractableKids #DigitalAge #SelfDeterminationTheory #ParentingTips #ScreenTimeManagement #NirEyal #FamilyDynamics #ResilientYouth #FocusedMinds Thank you for tuning in to this enlightening conversation. We hope you leave this episode with actionable insights and a new perspective on parenting and technology. Don't forget to subscribe for more episodes like this and share with anyone who could benefit from these powerful discussions. THE FOUNDATION - Virtual Community for Young MenBuilding Men InstagramBuilding Men WebsiteBuilding Men YouTubeBuilding Men FacebookWork with Dennis as your 1 on 1 coach If our podcast resonates with you, please consider rating, reviewing and sharing it with anyone who you believe would benefit from the message.Visit our sponsors - Finish The Race – Home of the official Building Men gear
Fat-Burning Man by Abel James (Video Podcast): The Future of Health & Performance
Do you find that you're more easily distracted than ever? You're in good company. In the age of nonstop notifications, painfully short attention spans, and endless fear mongering and doom scrolling, sometimes it feels difficult to get things done. So are you ready to master your time, attention and productivity? Imagine what you could accomplish if you could stay focused and follow through on your goals, despite all the distractions of modern life. Now is the perfect time to harness science-backed strategies to break bad habits for good. I'm pleased to be here today with Nir Eyal, a business consultant and award-winning author, including his latest bestseller, “Indistractable: How to Control Your Attention and Choose Your Life.” On this episode with Nir, we're chatting about: How to break bad habits and reduce wasted time How to use discomfort to your advantage How to master your time and attention Why that long to-do list could actually be hurting your productivity (and what to do instead) And tons more… Read the show notes: https://fatburningman.com/nir-eyal-how-to-break-bad-habits-and-use-discomfort-to-your-advantage/ For more from Nir Eyal, including his award-winning book "Indistractable," articles and more, go to NirAndFar.com. Join The Wild Guild and get freebies on Patreon: https://www.patreon.com/abeljames Watch on YouTube: https://www.youtube.com/fatburningman Like the show on Facebook: http://www.facebook.com/fatburningman Follow on Twitter: http://www.twitter.com/fatburnman Click here for your free Fat-Burning Kit: http://fatburningman.com/bonus
Passar någon titel på ett avsnitt som ska sätta tonen för ett nytt år bättre än ”Attack the day”? Frågar du oss är svaret nej. I avsnittet delar vi med oss gällande kraftfulla tankesätt och smarta strategier för att ta kontroll över ditt liv och din framtid. Vi diskuterar vikten att tro på rätt saker och fokusera på möjligheter snarare än hinder. Vi bryter också ner vanliga invändningar mot det som nämns ovan och lär oss anpassa oss till verkligheten utan att förlora positiviteten. "Just Do It" är ett mantra som alla borde ta till sig och vi går igenom varför det passar så bra och speciellt tillsammans med konceptet Timeboxing. Är du säljare ska du definitivt inte missa avsnittet då Oliver levererar tre konkreta tips för att göra en enorm skillnad under 2024. Genom att fokusera på namngivna konton (ICP), definiera säljprocesser och främja ett samarbete mellan olika avdelningar kommer förutsättningarna för succé att öka. , Sist, men inte minst viktigt pratar vi om vikten av återhämtning och att skapa tid för pauser. Vi belyser värdet av att tillåta sig själv att koppla av och ladda om för att verkligen orka upprätthålla ett ”Attack the day” mindset! Trevligt lyssnande! Michael & Oliver ————————————————————————————————————————————————————————————————————— Podcasten drivs av sälj- och marknadsexperten Oliver Lopez samt ledarskap- och effektivitetsexperten Michael Alphov. Oliver driver till vardags Structsales AB och Michael driver Effektiva Metoder AB. Kolla gärna in www.structsales.se och www.michaelalphov.se
Some days, the world seems intent on sabotaging your timeboxed calendar. A meeting goes longer than expected. The daycare center calls to say that your child is ill and has to be picked up ASAP. A project you thought would take an hour to complete instead took three. Before you know it, the end of the day arrives, and you've barely given time to the tasks you had wanted to do. You can read the Nir And Far blog post on: Scheduling for Life's Surprises: When Timeboxing is Toast: https://www.nirandfar.com/scheduling-for-surprises/ Nir And Far, a podcast about business, behaviour and the brain by Nir Eyal. If you enjoy this podcast, please subscribe on iTunes and leave an iTunes review. It will greatly help new listeners discover the show. Please visit my website Nir and Far for other info about my writing, books and teaching: http://www.nirandfar.com/ --- Support this podcast: https://podcasters.spotify.com/pod/show/nirandfar/support
Nir Eyal writes, consults, and teaches about the intersection of psychology, technology, and business. Nir previously taught as a Lecturer in Marketing at the Stanford Graduate School of Business and the Hasso Plattner Institute of Design at Stanford. Nir co-founded and sold two tech companies since 2003 and was dubbed by The M.I.T. Technology Review as, “The Prophet of Habit-Forming Technology.” Bloomberg Businessweek wrote, “Nir Eyal is the habits guy. Want to understand how to get app users to come back again and again? Then Eyal is your man.” He is the author of two bestselling books, Hooked: How to Build Habit-Forming Products and Indistractable: How to Control Your Attention and Choose Your Life. His books have resonated with readers worldwide, selling over 1 million copies in over 30 languages. Indistractable received critical acclaim, winning the Outstanding Works of Literature Award as well as being named one of the Best Business and Leadership Books of the Year by Amazon and one of the Best Personal Development Books of the Year by Audible. The Globe and Mail called Indistractable, “the best business book of 2019.” In addition to blogging at NirAndFar.com, Nir's writing has been featured in The New York Times, The Harvard Business Review, Time Magazine, and Psychology Today. Nir invests in habit-forming products that improve users' lives. Some of his past investments include Eventbrite (NYSE:EB), Anchor.fm (acquired by Spotify), Kahoot! (KAHOOT-ME.OL), Canva, Homelight, Product Hunt, Marco Polo, Byte Foods, FocusMate, Dynamicare, Wise App, and Sunnyside. Nir attended The Stanford Graduate School of Business and Emory University. Free Tools and Resources from Nir Eyal: Indistractable the book: http://geni.us/indistractable Indistractable bonus content is here: http://www.nirandfar.com/indistractable/ Indistractable summary article: https://www.nirandfar.com/skill-of-the-future/ Timeboxing article: https://www.nirandfar.com/timeboxing/ Values article: https://www.nirandfar.com/common-values/ Free habit tracker tool: https://www.nirandfar.com/habit-tracker/ Free schedule maker tool: https://www.nirandfar.com/schedule-maker/ List of top articles: https://www.nirandfar.com/best-articles/ Anders Varner on Instagram Doug Larson on Instagram
The battle against digital distractions is real. In this enlightening episode, we're joined by Nir Eyal, dubbed “The Prophet of Habit-Forming Technology” by The M.I.T. Technology Review. With a rich background in psychology, technology, and business, Nir sheds light on the techniques used by tech giants to create habit-forming products. He's the bestselling author of "Hooked" and "Indistractable," two books that delve deep into the world of digital habits. Dive in to discover: The interplay between building good habits and avoiding bad ones. How to make conscious decisions to pursue what truly matters. The real impact of ADHD diagnoses and digital distractions. The importance of time boxing and planning your day. Turning your values into time to combat distractions. Join us for a transformative conversation that will empower you to reclaim your time and attention in the digital age. Get my weekly newsletter - Adaptation. Start AIM7 for Free for 7 Days & then it's just $1 for your 1st month. Use the code: BLUEPRINT at checkout on our site Purchase Indistractable Follow Nir on LinkedIn, Instagram, YouTube, & Twitter My free schedule maker tool: https://www.nirandfar.com/schedule-maker/ Timeboxing article: https://www.nirandfar.com/timeboxing/ Quotable moments: "Hooked and indistractable are not negations. They're compliments." - Nir Eyal "Pills don't teach skills." - Nir Eyal "You cannot call something a distraction unless you know what it distracted you from." - Nir Eyal "The life changing practice of simply planning your day is so under appreciated." - Nir Eyal ABOUT THE BLUEPRINT PODCAST: The BluePrint Podcast is for busy professionals and Household CEOs who care deeply about their families, career, and health. Host Dr. Erik Korem distills cutting edge-science, leadership, and life skills into simple tactics optimized for your busy lifestyle and goals. Dr. Korem interviews scientists, coaches, elite athletes, entrepreneurs, entertainers, and exceptional people to discuss science and practical skills you can implement to become the most healthy, resilient, and impactful version of yourself. On a mission to equip people to pursue audacious goals, thrive in uncertainty, and live a healthy and fulfilled life, Dr. Erik Korem is a High-Performance pioneer. He introduced sports science and athlete-tracking technologies to collegiate and professional (NFL) football over a decade ago. He has worked with the National Football League, Power-5 NCAA programs, gold-medal Olympians, Nike, and the United States Department of Defense. Erik is an expert in sleep and stress resilience. He is the Founder and CEO of AIM7, a health and fitness app that unlocks the power of wearables by providing you with daily personalized recommendations to enhance your mind, body, and recovery. SUPPORT & CONNECT Instagram - https://www.instagram.com/erikkorem/ Twitter - https://twitter.com/ErikKorem LinkedIn - https://www.linkedin.com/in/erik-korem-phd-19991734/ Facebook - https://www.facebook.com/erikkorem Website - https://www.erikkorem.com/ Newsletter - https://erikkoremhpcoach.activehosted.com/fSee omnystudio.com/listener for privacy information.
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Episode Summary: I'm thrilled to introduce you to my guest, Nir Eyal, the esteemed author of the renowned book, Indistractable. In today's conversation, Nir provides a profound insight into mastering attention and sustaining focus. We delve into topics such as effective time management, prioritization, and decision-making strategies. Additionally, we explore how to seize control of your attention's direction, the drawbacks of traditional to-do lists, and Nir's insightful alternatives. His infectious energy and engaging demeanor made for a great conversation.-------------------------------Links Discussed in This EpisodeOrder a Copy of Minimalist Moms: Living and Parenting with SimplicitySubstack: Minimalist Moms PodcastDiane's Resource: Building a Non-Anxious Life by John DelonyConnect with Nir:WebsiteInstagramBook: Indistractable: How to Control Your Attention and Choose Your Life by Nir EyalBonus content: http://www.nirandfar.com/indistractable/Timeboxing article: https://www.nirandfar.com/timeboxing/Values article: https://www.nirandfar.com/common-values/Fomo article: https://www.nirandfar.com/fomo/Wage slavery article: https://www.nirandfar.com/wage-slaves/Nir's Free Habit Tracker Tool: https://www.nirandfar.com/habit-tracker/Free Schedule Maker Tool: https://www.nirandfar.com/schedule-maker/Nir's Top Articles: https://www.nirandfar.com/best-articles/Enjoy this Podcast?Post a review and share it! If you enjoyed tuning into this podcast, then do not hesitate to write a review. You can also share this with your fellow mothers so that they can be inspired to think more and do with less. Order (or review) my recent book, Minimalist Moms: Living & Parenting With SimplicityQuestions? You can contact me through my website, find me on Instagram, or like The Minimalist Moms Page on Facebook.Thanks for listening! For more updates and episodes, visit the website. You may also tune in on Apple Podcasts, Spotify, Google Podcasts, or Stitcher.Checkout the Minimalist Moms Podcast storefront for recommendations from Diane.If you enjoyed today's episode of the Minimalist Moms Podcast, then hit subscribe and share it with your friends!Episode Sponsors |The Minimalist Moms Podcast would not be possible without the support of weekly sponsors. Choosing brands that I believe in is important to me. I only want to recommend brands that I believe may help you in your daily life. As always, never feel pressured into buying anything. Remember: if you don't need it, it's not a good deal!Check out Greenlight and use my code minimalist for a great deal: https://greenlight.com/Our Sponsors:* Check out Armoire and use my code MINIMALIST for a great deal: http://www.armoire.style* Check out Armoire and use my code MINIMALIST for a great deal: http://www.armoire.styleSupport this podcast at — https://redcircle.com/minimalist-moms-podcast2093/exclusive-contentAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy
Nir Eyal | is my favorite focus author. He preaches and teaches after spending 5 years of his life studying ways to break distracted habits. It has been a dream of mine to have a podcast episode with Nir... today that wish has come true. We spend time talking about; Why Distraction is a Bad Thing Why Humans get distracted in the first place Best Practices to Avoid Distraction Does Nir actually live an indistractable life? Advice to Authors from Alex's point of view SO MUCH MORE Make sure to check Nir out on social media, and pick up a copy of his incredible book. LinkedIn - https://www.linkedin.com/in/nireyal/ Youtube - https://www.youtube.com/user/nirandfar Twitter - https://twitter.com/nireyal Facebook - https://www.facebook.com/nirandfar/ Instagram - http://instagram.com/neyal99 More from Nir: link to the book, it's: http://geni.us/indistractable Indistractable bonus content is here: http://www.nirandfar.com/indistractable/ Indistractable summary article: https://www.nirandfar.com/skill-of-the-future/ Timeboxing article: https://www.nirandfar.com/timeboxing/ Values article: https://www.nirandfar.com/common-values/ Fomo article: https://www.nirandfar.com/fomo/ Wage slavery article: https://www.nirandfar.com/wage-slaves/ My free habit tracker tool: https://www.nirandfar.com/habit-tracker/ My free schedule maker tool: https://www.nirandfar.com/schedule-maker/ List of my top articles: https://www.nirandfar.com/best-articles/ I love you all!!! ~A. --- Send in a voice message: https://podcasters.spotify.com/pod/show/alexander-davis9/message
Episode 369 welcomes back Nir Eyal, who writes, consults, and teaches about the intersection of psychology, technology, and business.Find Nir Online:Link to the book, it's: http://geni.us/indistractableIndistractable bonus content is here: http://www.nirandfar.com/indistractable/Indistractable summary article: https://www.nirandfar.com/skill-of-the-future/Timeboxing article: https://www.nirandfar.com/timeboxing/Values article: https://www.nirandfar.com/common-values/Fomo article: https://www.nirandfar.com/fomo/Wage slavery article: https://www.nirandfar.com/wage-slaves/My free habit tracker tool: https://www.nirandfar.com/habit-tracker/My free schedule maker tool: https://www.nirandfar.com/schedule-maker/List of my top articles: https://www.nirandfar.com/best-articles/=============================Connect with the host, Brian Ondrako:=============================Website: https://brianondrako.com/Youtube: https://www.youtube.com/@brianondrakoTwitter: https://twitter.com/brianondrakoInstagram: https://www.instagram.com/brianondrako/Linkedin: https://www.linkedin.com/in/brianondrako/Substack: https://brianondrako.substack.com/=============================This episode is brought to you by LMNT, the delicious, sugar-free electrolyte drink mix. As someone who is active with CrossFit and other activities, I take LMNT 1–2 times per day. LMNT is formulated to help anyone with their electrolyte needs as electrolytes are vital to helping relieve hunger, cramps, headaches, tiredness, and dizziness.For a limited time, listeners of the Just Get Started Podcast can get a free LMNT Sample Pack with any purchase. This special offer is available here: DrinkLMNT.com/justgetstarted Hosted on Acast. See acast.com/privacy for more information.
Agile Timeboxing - Gain The Focus You Need! In the dynamic world of Agile project management, the concept of “timeboxing” has emerged as a crucial technique for fostering efficiency, maintaining focus, and enabling iterative development. Timeboxing is a disciplined approach that sets specific time limits for tasks, activities, or phases within an Agile project. This technique empowers teams to manage their work effectively and deliver valuable results within defined timeframes. Understanding Timeboxing in Agile Timeboxing is a practice that derives from the Agile principle of time management and continuous improvement. It involves breaking down work into manageable chunks, each with a predefined duration. The timeboxes, which can range from hours to weeks, create a sense of urgency and commitment, driving teams to complete tasks within the allotted time. In Agile methodologies like Scrum, timeboxing is utilized in various aspects of the project, including: Sprints: In Scrum, each sprint is a timeboxed iteration typically lasting 1 to 4 weeks. This time constraint encourages teams to focus on delivering a potentially shippable product increment by the end of the sprint. Daily Standup Meetings: Daily standup meetings, also known as daily scrums, are timeboxed to a brief 15 minutes. Team members provide updates on their progress, discuss obstacles, and plan their work for the day. Backlog Refinement: Backlog refinement sessions, where the team reviews and refines the product backlog, are timeboxed to ensure that they don't become lengthy meetings. Retrospectives: Retrospectives, as discussed in a previous article, are timeboxed meetings where the team reflects on the iteration and identifies areas for improvement. Benefits of Timeboxing Enhanced Focus: Timeboxing creates a sense of urgency and encourages the team to concentrate on the most critical tasks. By setting clear time limits, teams avoid getting sidetracked and ensure that they deliver valuable increments of work. Predictability: Timeboxing improves predictability in project planning. Since tasks and iterations have defined durations, the team can better estimate the amount of work that can be accomplished within a given timeframe. Improved Collaboration: Timeboxing encourages collaboration and helps manage expectations. Knowing that a timebox is limited, team members are more likely to communicate, prioritize, and work together efficiently. Reduced Waste: Timeboxing reduces the likelihood of gold-plating (overengineering) and scope creep (adding features mid-iteration). Teams focus on delivering what's necessary, reducing waste and optimizing the use of resources. Continuous Improvement: The timeboxing practice feeds into the Agile principle of continuous improvement. By analyzing results at the end of each timebox, teams can identify areas for optimization and implement changes in subsequent iterations. How to connect with AgileDad: - [website] https://www.agiledad.com/ - [instagram] https://www.instagram.com/agile_coach/ - [facebook] https://www.facebook.com/RealAgileDad/ - [Linkedin] https://www.linkedin.com/in/leehenson/
If you don't invest the necessary time into learning Chinese, it doesn't matter how good your method is. Timeboxing is a wonderful way to get more done in less time. Link to article: Timeboxing Chinese: Get more done in less time: https://www.hackingchinese.com/timeboxing-chinese/ #learnchinese #timemanagement #timeboxing #gettingthingsdone Three factors that decide how much Chinese you learn: https://www.hackingchinese.com/three-factors-decide-much-chinese-learn/ Learning Chinese is more like walking a thousand miles than running 100-metre dash: https://www.hackingchinese.com/learning-chinese-is-more-like-walking-a-thousand-miles-than-running-100-metre-dash/ The 10 best free Chinese listening resources for beginner, intermediate and advanced learners: https://www.hackingchinese.com/the-10-best-free-chinese-listening-resources-for-beginner-intermediate-and-advanced-learners/ An introduction to extensive reading for Chinese learners: https://www.hackingchinese.com/introduction-extensive-reading-chinese-learners/ 7 mistakes I made when writing Chinese characters and what I learnt from them: https://www.hackingchinese.com/7-mistakes-i-made-when-writing-chinese-characters-and-what-i-learnt-from-them/ The forking path: A human approach to learning Chinese: https://www.hackingchinese.com/the-forking-path-a-human-approach-to-learning-chinese/ The time barrel: How to find more time to study Chinese: https://www.hackingchinese.com/the-time-barrel-you-have-more-time-than-you-think/How long have you studied Chinese? https://www.hackingchinese.com/how-long-have-you-studied-chinese/ Listen to this and other episodes on your favourite podcasting platform, including Apple Podcasts, Breaker, Google Podcast, Overcast, Pocket Casts, RadioPublic, Spotify and YouTube: https://www.hackingchinese.com/podcast More information and inspiration about learning and teaching Chinese can be found over at https://www.hackingchinese.com Music: "Traxis 1 ~ F. Benjamin" by Traxis, 2020 - Licensed under Creative Commons Attribution (3.0)
You've probably heard this one before: When you change your habits, you change your life. But before we can change our habits, we need to learn how to master our attention and focus, and do the things you say you're going to do that'll direct us towards living the life we desire, and being the person we want to become. This week, I am beyond thrilled to be sharing with you my chat with Nir Eyal, who's going to make you think — and re-think — how you're spending your time and attention every day. Are you actively choosing your life with each action you take? Why do we do things that we did not intend against our better interest? Why do we go off track? Through his work, Nir wants to make sure we don't look back on our lives with regret for all the things we said we were going to do, but didn't because we got “distracted”. Nir is the author of two bestselling books, Hooked: How to Build Habit-Forming Products and the critically acclaimed Indistractable: How to Control Your Attention and Choose Your Life. He has taught at the Stanford Graduate School of Business and the Hasso Plattner Institute of Design at Stanford, and his writings have been featured in The New York Times, The Harvard Business Review, Time Magazine, and Psychology Today. We had so much to talk about that this conversation will be shared with you in two parts. In this first half, Nir redefines for us what “distraction” means: It is not what's on the outside that is distracting us — not social media, not the children, not the laundry. What is distracting us 90% of the time is our desire to escape uncomfortable emotional states such as boredom and loneliness — also known as “internal triggers”. How do we manage them instead of letting them manage us? Do you know what you really want to do with your time? How can we turn our values into time and action with intention by the simple act of scheduling them in our calendar, whether that's an hour for exercise and mediation, weekly date night with your spouse, or house chores? Let's dive in. (Stay tuned for Part Two of the conversation where we get into what it means to raise indistractable kids in today's world.) Chapters 00:00 Introduction 00:29 Nir's introduction 04:05 Inspiration for the book “Indistractable” 07:44 The impact of technology on attention span 09:29 What are internal triggers 10:15 Carrots and Sticks 14:30 How to manage Distraction 15:45 Traction vs Distraction 18:43 Busyness vs Productivity 23:54 Reactive Work Vs Reflective work 25:28 Being intentional yet spontaneous 29:21 Productivity tool: Timeboxing 32:04 Timeboxing for social media 34:33 Outro Find RachReflects on : http://rachreflects.com http://instagram.com/ms_rach
Join Coach JVB for an insightful and helpful one-on-one chat about how to get more done in less time. Are you familiar with Parkinson's Law? This one is all about how the more time you give yourself to accomplish something, the longer it will take you to get it done. Jenny shares examples from her own business and life to demonstrate how to set realistic yet challenging goals, having spent years building good habits through trial and error when it comes to productivity. Learn all about how to eliminate distractions, the importance of time-blocking, and how breaking down large projects into smaller and manageable tasks can be a gamechanger for you too! Get Your Perfect Sports 20% Discount here by using coupon code JVBSave $100 off Your MAXPRO Fitness hereApply for the STRONG Formula Certification Program WORK WITH A TEAM STRONG GIRLS COACHSTRONG Fitness Magazine Subscription Use discount code STRONGGIRL If you enjoyed this episode, make sure and give us a five star rating and leave us a review on iTunes, Podcast Addict, Podchaser and Castbox. Resources:STRONG Fitness MagazineSTRONG Fitness Magazine on IGTeam Strong GirlsCoach JVB Follow Jenny on social media:InstagramFacebookYouTube
In dieser Folge geht es um Zeitmanagement. Ganz genau geht es um eine Methode bzw. ein Tool im Zeitmanagement, die ich sehr gern anwende: das Timeboxing. Ich erkläre in dieser Folge, was genau Timeboxing ist und welche drei Gründe es aus meiner Sicht gibt, wieso du das unbedingt mal ausprobieren solltest und damit deine Ziele leichter erreichst!
Today my conversation partner is Matt LeMay! Matt is an internationally recognized product leader, author, and consultant. He is the author of Agile for Everybody (O'Reilly Media, 2018) and Product Management in Practice (Second Edition O'Reilly Media, 2022), and has helped build and scale product management practices at companies ranging from early-stage startups to Fortune 500 enterprises. Matt and I met at UX Lisbon last year where he gave a talk that included him describing his extremely actionable recipe for team agility: the One Page / One Hour Pledge, a powerful commitment to minimize busywork and maximize collaboration that has been adopted by individuals and teams at Amazon, Walmart, CNN, and more. I was excited to bring Matt into a conversation about this pledge, because I know how easy it is to get caught in a rabbit-hole of perfectionism before sharing my work with others. Teams can work more fluidly if we reduce the cycle time between solo work and team work. Matt is an advocate for the power of focus, subtraction and feedback loops over perfection - I mean, would you rather ride a bike you can only aim once or one that you get to steer continuously? I never dreamed I'd get to have a podcast conversation that includes references to Alan Watts and the power of Ego Death to accelerate your team's success and ultimately, one's own success…but glad that we are! Matt and unpack how TIMEBOXING (ie, Tight-and-almost-thoughtless constraints ) helps shift the relationship between thought and action in teams and organizations…and can help move the conversation forward. Head over to theconversationfactory.com/listen for full episode transcripts, links, show notes and more key quotes and ideas. You can also head over there and become a monthly supporter of the show for as little as $8 a month. You'll get complimentary access to exclusive workshops and resources that I only share with this circle of facilitators and leaders. Links Matt's website Product Management in Practice https://www.onepageonehour.com/ Matt's talk at UX Brighton on “You Don't Get anyone to do Anything” “When we attempt to exercise power or control over someone else, we cannot avoid giving that person the very same power or control over us” Alan Watts Alan Watts “The wisdom of Insecurity
Kicking off a focus on founder mental health, my first suggestion is Timebox. You'll hear me say this all the time: time is our most precious asset. Maybe a corollary to that is focus. I found that I can create focus by time boxing. About SpringTime VenturesSpringTime Ventures seeds high-growth startups in healthcare, fintech, logistics, and marketplace businesses. We look for founders with domain expertise, forging a path with a truly transformative technology. We only invest in software-based businesses in the USA. We bring a people-focused approach, work quickly, and reach conviction independently. Our initial check size is $400k to $600k. You can learn more about us and our approach. About Rich MaloyRich's mission is to rebuild the American dream through entrepreneurship. He works with early stage startups transforming the world, giving all people the opportunity to grow, learn and earn. With prior careers in finance and sales, he's now focused on startups investing through SpringTime Ventures where he is a Managing Partner. He's a father of two young children and loves sci-fi, skiing, and video games.
Timeboxing and to-do lists are two popular productivity methods, and each has its own unique benefits. To illustrate these benefits, let's consider a scenario: Imagine you're a software developer working on a new project. You have a long list of tasks to complete and only a limited amount of time each day to work on them.On one hand, you have timeboxing, where you allocate a specific amount of time for each task. With this method, you set a timer for a set amount of time, usually 25 to 50 minutes, and work on a single task until the timer goes off. The idea behind this approach is to use time constraints to increase focus and prevent distractions. By using timeboxing, you'll be able to complete more tasks in a shorter amount of time since you're not allowing yourself to get sidetracked.This is the topic we're discussing in this week's episode.Listen & Enjoy!
¿Te cuesta encontrar el tiempo, el espacio o la motivación para avanzar en las cosas importantes?Ese es el tema principal del programa de esta semana, donde aprenderás cómo priorizar lo prioritario con la técnica del timeboxing.Notas de programaLas notas del programa están disponibles en https://kenso.es/episodio/242-timeboxingÍndice del programa(01:07) ¿Qué son las cajas de tiempo?(07:39) ¿Qué necesitas para comenzar con timeboxing?(11:05) Un entorno físico adecuado(18:28) Recomendación: recurso(20:29) Cómo crear una caja de tiempo(27:05) El tamaño de las cajas de tiempo(35:15) Recomendación: herramienta(37:26) Cronometra sobre la marcha(39:17) Ritmo y carrera(43:48) ¿Por qué no hacer timeboxing?(46:25) Timeboxing y tu perfil productivo(48:43) Resumen(50:59) Tu plan de acción(51:57) ¡Nos escuchamos muy pronto!Recursos mencionadosEpisodio 240: Tu método personalizado para decidir qué hacer con tu tiempo y tu vidaVídeo: Crea tu propio sistema pomodoroLibro: El ejecutivo eficaz de Peter F. DruckerEpisodio 107: Cómo crear hábitos productivosEpisodio 35: Descubre tu cronotipo y mejora tu energía y descansoEpisodio 179: 11 leyes para mejorar tu productividadVideo: Haz descansos productivos en tu jornadaGestor de tareas: Sunsama (consigue 30 días de prueba gratis)Episodio : Hábitos atómicos de James ClearLa página web de KENSOEl canal de Telegram: Efectividad KENSONuestros cursos onlineSuscríbete al boletín electrónico de KENSOÚnete a KENSO CírculoKENSO Círculo es el club para personas centradas en mejorar su efectividad y vivir más felices.Un club a tu alcance porque a partir de 1€ al mes tendrás acceso prioritario a los episodios del podcast, podrás descargar un plan de acción para cada episodio, recibirás cada mes un episodio especial donde haremos una reseña sobre un libro de efectividad, disfrutarás de descuentos en los servicios de KENSO y de nuestra eterna gratitud por ayudarnos a mejorar.Esta semana queremos dar las gracias a Gustavo, Montserrat Moreno Boronat, Paula y Alejandra por su apoyo a nuestro proyecto.Más información & InscripciónComparte tus sugerencias¿Qué te gustaría escuchar en futuros episodios del podcast?Déjanos tus sugerencias de personas a entrevistar o temas a tratar en los comentarios de las notas del progra Hosted on Acast. See acast.com/privacy for more information.
Founders love a good stretch target. The only problem is this can often put them under massive pressure. This is exactly what happened to my guest today. Ken Babcock's wife Judy was set to give birth in a month and Ken used that deadline to place a somewhat self-imposed timeframe on his fundraising round. Find out what happened in this session. Want to know how Future Fit you are? Take 3 mins to benchmark yourself with our Peer Score test on peer-effect.com. You might discover some surprising gaps! Or just follow James on LinkedIn for more thoughts around coaching and being future fit.
You’ve heard of “Timeboxing” to be more productive, but “Spaceboxing” is just as important. We talk about being more productive with your space, iPhone gimmicks, and discuss: why is America so much LESS productive this year? Go to Shopify.com/tps for a FREE trial. You can find links to everything that we share in the show […]
We're facing a burnout epidemic that goes beyond work. Understanding its causes can help us fix it. A 2021 Indeed survey shows 52% of 1,500 American respondents say they feel burned out, compared with 43% the year prior; 67% believe that burnout worsened during the COVID-19 pandemic. That's not surprising. You can read the Nir And Far blog post on How to Prevent Burnout Using Timeboxing https://www.nirandfar.com/how-to-prevent-burnout/ Nir And Far, a podcast about business, behaviour and the brain by Nir Eyal. If you enjoy this podcast, please subscribe on iTunes and leave an iTunes review. It will greatly help new listeners discover the show. Please visit my website Nir and Far for other info about my writing, books and teaching: http://www.nirandfar.com/ --- Support this podcast: https://anchor.fm/nirandfar/support
So you've done your part in creating content online and making your website come alive with videos to showcase your brand, services and product. But so far, the numbers have stalled, and there's no progress to your video engagements. Is there another way for you to attract prospects? Two words: Video Prospecting. Break through the noise with a video strategy that doesn't need to be entertaining or production-heavy, but is highly more enticing and helpful. In this episode, Chris Schwager (Co-founder and Video Marketer of Ridge Films) is joined by Chet Lovegren (Director of Sales Development at Pavillion, and the Host of The Sales RX Podcast) to discuss everything about video prospecting. Chet takes us back to his roots as a full-circle sales representative and how it shaped his expertise on cold calling, sales outreach and prospecting to now lead a team of Sales Development Representatives or SDR's, who perform inbound and outbound prospecting to generate leads. Chet gives insight on how he discovered the sales video's potential to get higher engagement and conversion rates, and how he's able to produce a sales playbook by his own learning process of creating an ideal outreach. Chet also sheds light on unresponsive subscriber behavior, maximising LinkedIn voicemails for prospecting, which platform best serves friction-based headlining, and optimising Timeboxing for proper cold calling. FOLLOW CHET LOVEGREN or check out The Sales Doctor Website and Pavillion. DIY VIDEO PROGRAM Create your own videos with a push of a button. ASK YOUR QUESTION What has you feeling overwhelmed? Let us help you solve the mystery of video marketing. CONVINCE YOUR BOSS Download our guide to help decision makers understand the importance of video marketing their business. THE POWER OF VIDEO MARKETING View on demand in 60-minutes. 7 lessons to kickstart your video marketing journey. RIDGE FILMS YOUTUBE Catch new episodes of the Video Made Simple podcast on our Youtube channel. Let us know what you think and feel free to like, comment, and subscribe.
►► Finde in unter drei Minuten heraus, ob du dich effektiv auf deine Prüfungen vorbereitest, indem du nur einige wenige Fragen beantwortest: https://mailchi.mp/endlichjura/lernen Ganz egal, ob du dich aktuell auf das Jura-Examen vorbereitest, also schon in der Examensvorbereitung bist, dein Jura-Studium gerade erst begonnen hast oder mitten im Referendariat steckst: Der Stoff ist enorm, und die verfügbare Zeit scheint nicht auszureichen. In diesem Quick Win möchte ich dir eine Lerntechnik namens »Timeboxing« zeigen, die dir ermöglichen wird, effizienter zu lernen und so deine Lernzeit sofort zu reduzieren – damit du die gewonnene Zeit für die anderen schönen Dinge im Leben nutzen kannst.
6 weeks ago, I made a commitment to myself that I was going to become Indistractable. That I would take back my control over my time, rather than being a slave to the schedule. This episode explores how it's working out, and how it's changing my life.
Some of what Christian covers: Horizontal service teams enable and collaborate The balancing point between innovation and confidence in roadmaps Timeboxing approach to provide capped flexibility to explore Rotational engineering programs grow cross-functional relationships Integrating the learned knowledge from the rotational engineering program Creating a feedback loop via a service-oriented mindset Using the Focused Innovation pillar Meet: Christian Yang is an engineering manager at Zoox for two software infrastructure teams: High-Performance Compute and 3D Vehicle Run Visualization Platform If you have any questions for Christian, please feel free to reach out via: https://www.linkedin.com/in/yang-christian/ I hope you enjoyed the episode, the best place to connect with me is on Linkedin - https://www.linkedin.com/in/amirbormand (Amir Bormand). Please send me a message if you would like me to cover certain topics with future guests.
Nir Eyal is a behavioural designer who has taught at the Stanford Graduate School of Business and Hasso Plattner Institute of Design. He is the bestselling author of "Hooked: How to Build Habit-Forming Products" and "Indistractable: How to Control Your Attention and Choose Your Life."His writing on technology, psychology, and business, appears in the Harvard Business Review, The Atlantic, TechCrunch, and Psychology Today and he blogs regularly at NirAndFar.com Today we discuss how you can use his principles to powerfully influence your own behaviour and you'll probably need to listen twice, as there are heaps of valuable nuggets.Here are some links to Nir's work:Indistractable book: http://geni.us/IndistractableIndistractable summary article: https://www.nirandfar.com/skill-of-the-future/Distraction guide here: https://www.nirandfar.com/distractions/Habits vs routines article here: https://www.nirandfar.com/habits/Why schedules are better than to-do lists: https://www.nirandfar.com/todo-vs-schedule-builder/Timeboxing article: https://www.nirandfar.com/timeboxingSchedule maker tool: https://nirandfar.com/schedule-maker/Indistractable Model graphic: https://www.dropbox.com/s/uip4bifw7fll6p4/How%20to%20be%20Indistractable%20%20by%20Nir%20Eyal.png?dl=0
Links related to this episode: https://amzn.to/3enDQof (Indistractable by Nir Eyal) https://amzn.to/3rdAEAS (Hooked by Nir Eyal) https://amzn.to/3ikL79E (No B.S. Time Management by Dan Kennedy) https://www.nirandfar.com/timeboxing (Nir's article on Timeboxing) https://www.btmsinsiders.com/bundles/btmsinsiders-all-access-pass?utm_source=btms-daily&utm_medium=email&utm_campaign=20210716 (BTMSinsiders is like Netflix for Copywriting & Marketing Training — Stream all of Roy's training for one low monthly fee) https://www.youtube.com/user/royfurr?sub_confirmation=1 (Subscribe to Roy's YouTube channel) https://breakthroughmarketingsecrets.captivate.fm/listen (Subscribe to the Breakthrough Marketing Secrets podcast) https://www.breakthroughmarketingsecrets.com/work-with-roy/ (Work With Roy ) https://www.breakthroughmarketingsecrets.com (Get Roy's Daily Emails) I hate this stupid productivity tip... I hate it because it works. But it's a little more complex than that. I keep coming back to it over and over again, because people keep recommending it to me. And it always happens the same way. First, I resist it, because I hate the idea of it. Then I try it, because I have things I need to get done. Then I love it, because it works. Then even though it works, I eventually stop using it. Until I feel the drive to be more productive and I'm reminded of this powerful productivity tip yet again. https://youtu.be/HwM0HTxtE8I (Is this the world's most-powerful stupid productivity tip? You decide...) Yours for bigger breakthroughs, Roy Furr
Kyle Kowalski of Sloww teaches you the best productivity hack for actually doing what you need to get done. Episode 1930: Timeboxing: The #1 Productivity Hack for Actually Doing Your To-Do List by Kyle Kowalski of Sloww.co Kyle Kowalski, the human behind Sloww, is a corporate dropout turned solopreneur who found and created his life purpose after an existential crisis―synthesizing the world's wisdom to awaken and actualize the art of living. His crisis was the beginning of the end of my glorification of busy and unconscious consumption—and the beginning of his awakening to intentional living The original post is located here: https://www.sloww.co/timeboxing/ Gusto is making payroll, benefits, and HR easy for small businesses. Get 3 months free once you run your first payroll with our link: Gusto.com/OLD Please Rate & Review the Show! Visit Me Online at OLDPodcast.com and in The O.L.D. Facebook Group Join the Ol' Family to get your Free Gifts and join our online community: OLDPodcast.com/group Interested in advertising on the show? Visit https://www.advertisecast.com/OptimalLivingDaily Learn more about your ad choices. Visit megaphone.fm/adchoices
Kyle Kowalski of Sloww teaches you the best productivity hack for actually doing what you need to get done. Episode 1930: Timeboxing: The #1 Productivity Hack for Actually Doing Your To-Do List by Kyle Kowalski of Sloww.co Kyle Kowalski, the human behind Sloww, is a corporate dropout turned solopreneur who found and created his life purpose after an existential crisis―synthesizing the world's wisdom to awaken and actualize the art of living. His crisis was the beginning of the end of my glorification of busy and unconscious consumption—and the beginning of his awakening to intentional living The original post is located here: https://www.sloww.co/timeboxing/ Gusto is making payroll, benefits, and HR easy for small businesses. Get 3 months free once you run your first payroll with our link: Gusto.com/OLD Please Rate & Review the Show! Visit Me Online at OLDPodcast.com and in The O.L.D. Facebook Group Join the Ol' Family to get your Free Gifts and join our online community: OLDPodcast.com/group Interested in advertising on the show? Visit https://www.advertisecast.com/OptimalLivingDaily Learn more about your ad choices. Visit megaphone.fm/adchoices
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