Podcasts about CTO

Eno Reyes is the co-founder and CTO of Factory, the agent-native software development platform building autonomous "Droids" for enterprise engineering teams. Factory has raised $220 million, most recently a $150 million Series C at a $1.5 billion valuation, from investors including Khosla Ventures, Sequoia Capital, 20VC, NEA, Blackstone, Insight Partners and Nvidia. Before founding Factory, Eno worked as a machine-learning engineer at Hugging Face, training, optimizing and deploying large language models for enterprise customers. AGENDA: 00:00 Are We Underestimating AI by an Order of Magnitude?  06:35 Why Can the Smartest AI Model Be the Cheapest?  18:51 Is Anthropic's Coding Business Really Worth $2 Trillion?  33:41 Will Continuous-Learning Models Help or Hurt Factory?  40:43 Will 80–90% of Neo-Labs Die in the Next 18 Months?  44:33 Should American Enterprises Work With Open-Source Chinese Models?  55:42 Must AI Founders Radically Rethink What a Great Outcome Looks Like?  1:04:30 Do Pedigree and Credentials Still Matter in AI Hiring?  1:19:17 Which Is the Biggest Threat: Claude Code, Codex, Cognition or Cursor?  1:24:20 What Seems Crazy Today but Will Be Obvious in Five Years?  

Has enterprise AI finally reached the point where impressive demonstrations are no longer enough? In this episode, I speak with Murali Swaminathan, CTO at Freshworks, about the growing pressure on AI investments to deliver measurable business value. Murali has over 30 years of enterprise software experience, including roles at ServiceNow and CA, and now leads engineering and architecture teams at Freshworks. Murali believes the AI hype cycle is being replaced by an accountability cycle. Buyers want to understand reliability, governance, total cost of ownership, traceability, and the return generated by every deployment. They also want the ability to audit decisions, override outcomes, and use feedback to improve performance. Productivity alone provides an incomplete measure. Within service operations, companies can examine time to resolution, the volume of repetitive work automated, the number of issues completed without human intervention, and the quality of the employee's experience. Murali describes the difference between service-level agreements and experience-level agreements. Resolving a ticket within two minutes means very little if the employee's problem remains. The better question is whether AI completed the workflow and restored the person's ability to work. We also discuss why mid-market and agile enterprises provide a demanding test for AI. These companies have complex requirements but cannot absorb lengthy implementation programs, unclear pricing, or failed experiments. Murali recommends beginning with a limited process, measuring the result, establishing whether it can be repeated, and expanding only after it has proved reliable. Architecture plays an important role. Murali argues that ease of use begins beneath the interface. Configuration-led platforms can be upgraded as new capabilities arrive, while heavily customized systems can leave companies trapped on older releases. Autonomous service operations do not require removing people from every process. Murali uses the example of a printer incident. AI can read the ticket, classify the problem, route it to IT or facilities, and apply an automated fix when a trusted process exists. People retain responsibility for unusual, uncertain, or higher-risk decisions. Scaling this model requires cloud infrastructure that respects regional data residency, privacy, encryption, routing, and audit requirements. AI requests and diagnostic logs must remain within the correct geographic and regulatory boundaries. The conversation concludes with engineering skills. AI coding tools can generate software quickly, but engineers must understand architecture, usability, testing, and customer requirements. Companies also need rules determining which code can be reviewed by AI and which changes require human approval. Is your company measuring whether AI genuinely improves service operations, or is it counting deployments and calling that progress? Listen to the episode and share your thoughts with me.

In this solo episode of the Tech Leaders Playbook, Avetis Antaplyan explains why the right person in the wrong environment can still become the wrong hire. Avetis breaks down how leaders can evaluate candidates based on the problems they have actually solved, the environments where they perform best, and the stage of growth they have helped companies navigate. He explores common hiring mistakes, better executive interview questions, how to assess recruiting and executive search partners, and where AI belongs in modern talent acquisition. This episode is especially relevant for founders, CEOs, technology leaders, hiring managers, and executives building teams through periods of growth and change.What You'll Learn• Why impressive resumes and prestigious companies can create dangerous hiring bias.• How to match a candidate's experience with your company's current stage and next phase of growth.• What executives should ask to separate personal impact from simply being part of a successful company.• When an executive search partner can improve the quality and speed of a critical hire.• The role AI should play in sourcing and screening without replacing human judgment.Chapters00:00 Hiring for the Right Stage02:21 Start With Business Needs04:39 The Resume and Brand Trap06:53 Measuring a Candidate's Real Impact09:17 Hire for the Next Stage11:38 Be Honest About the Role16:08 Better Executive Interview Questions20:58 Choosing a Search Partner30:13 Protecting Your Employer Brand32:18 AI, Judgment, and Final TakeawaysFollow Avetis AntaplyanInstagram:https://www.instagram.com/avetisantaplyanSpotify:https://open.spotify.com/show/0rOkUXDSQb6SVFE6LttWDeApple Podcasts:https://podcasts.apple.com/us/podcast/the-tech-leaders-playbook/id1690263628HIRECLOUT:https://www.hireclout.comThe Tech Leader's Playbook:https://www.podcast.hireclout.comLinkedIn:https://www.linkedin.com/in/hirefasthirerighthiring strategy, executive recruiting, talent acquisition, executive search, hiring executives, recruiting strategy, leadership hiring, candidate assessment, hiring process, executive interview questions, startup hiring, technology leadership, business growth, company culture, talent strategy, hiring managers, founders, CEOs, CTO hiring, executive leadership, AI recruiting, AI hiring, candidate screening, employer branding, recruiting firms, search partners, Avetis Antaplyan, Tech Leaders Playbook#Hiring #ExecutiveRecruiting #TalentAcquisition #Leadership #ExecutiveSearch #HiringStrategy #TechLeadership #StartupHiring #AIRecruiting #BusinessLeadership #TechLeadersPlaybook

It's 0300 and you encounter a rapidly expanding zone 1 retroperitoneal haematoma. Time to enter “tiger country”. What can you do to make this a more familiar expedition?• Hosts: Bulleted list of host names, including title, institution, & social media handles if indicated1.     Mr Prashanth Ramaraj. ST5 General Surgery, George Hospital, Western Cape / Southeast Scotland Deanery. @LonTraumaSchool2.     Dr Roisin Kelly. Medical Officer, Emergency Medicine, Sydney, Australia. 3.     Mr Max Marsden. Consultant Trauma and UGI Surgeon, Royal London Hospital. @maxmarsden834.     Mr Christopher Johnston. Consultant Liver Transplant Surgeon and Transplant Surgery Fellowship Lead, Edinburgh Transplant Unit. @cjcjohnston• Learning objectives: Bulleted list of learning objectives.A)    To understand the rationale for thoracic aortic clamping in resuscitative trauma surgery and how this is performed.B)     To understand how to access the retroperitoneal structures by means of medial visceral rotation and how this is performed.C)     To understand the haemostatic ladder for liver trauma and considerations in hepatic exclusion.Please visit https://behindtheknife.org to access other high-yield surgical education podcasts, videos and more.  If you liked this episode, check out our recent episodes here: https://behindtheknife.org/listenBehind the Knife Premium: https://behindtheknife.org/premiumOral Board Review: https://behindtheknife.org/oral-boardOral Board Simulator: https://behindtheknife.org/oral-board/simulatorGeneral Surgery Oral Board Review Course: https://behindtheknife.org/premium/general-surgery-oral-board-reviewTrauma Surgery Video Atlas: https://behindtheknife.org/premium/trauma-surgery-video-atlasDominate Surgery: A High-Yield Guide to Your Surgery Clerkship: https://behindtheknife.org/premium/dominate-surgery-a-high-yield-guide-to-your-surgery-clerkshipDominate Surgery for APPs: A High-Yield Guide to Your Surgery Rotation: https://behindtheknife.org/premium/dominate-surgery-for-apps-a-high-yield-guide-to-your-surgery-rotationVascular Surgery Oral Board Review Course: https://behindtheknife.org/premium/vascular-surgery-oral-board-reviewColorectal Surgery Oral Board Review Course: https://behindtheknife.org/premium/colorectal-surgery-oral-board-reviewSurgical Oncology Oral Board Review Course: https://behindtheknife.org/premium/surgical-oncology-oral-board-reviewCardiothoracic Oral Board Review Course: https://behindtheknife.org/premium/cardiothoracic-surgery-oral-board-reviewOBGYN Oral Board Review Coures: https://behindtheknife.org/course/obgyn-oral-board-reviewEPA Playbook: https://behindtheknife.org/course/epa-playbookSurgical Instrument Flashcards: https://behindtheknife.org/course/surgical-instrument-flashcardsABSITE Review: https://behindtheknife.org/course/absite-2026-exam-reviewDownload our App:Apple App Store: https://apps.apple.com/us/app/behind-the-knife/id1672420049Android/Google Play: https://play.google.com/store/apps/details?id=com.btk.app&hl=en_US

Would you ever go into business with your family? In this week's episode, our hosts take on Sami's tale of becoming the CTO of his brother's business venture. After the trio get into some excellent running advice, Sami reminds us of the importance of validating the product to make sure the market will actually use what you've built. Will reflects on the importance of a Document of Expectations to weed out potential clients that aren't going to put effort into the development of their ideas (especially if you're doing the work for free), and Chad explains why an idea fizzling out before completion isn't necessarily a bad thing. And make sure to tune in next week, as the team brings in Sami's brother, Doron, to answer some of the questions brought up this episode. — You can find Chad all over social media as @cpytel and Sami through his website. You can also connect with the trio via their LinkedIn pages - Chad - Will - Sami. Don't forget you can now also watch the show over on our YouTube channel! If you would like to support the show, head over to our GitHub page, or check out our website. Got a question or comment about the show? Why not write to our hosts: hosts@giantrobots.fm This has been a thoughtbot podcast. Stay up to date by following us on social media - LinkedIn - Mastodon - Bluesky © 2026 Giant Robots Smashing Into Other Giant Robots Podcast

DHH is the creator of Ruby on Rails, Omarchy Linux, CTO of 37signals, and a racecar driver. Thank you for listening ❤ Check out our sponsors: https://lexfridman.com/sponsors/ep501-sc See below for timestamps, transcript, and to give feedback, submit questions, contact Lex, etc. Transcript: https://lexfridman.com/dhh-2-transcript CONTACT LEX: Feedback – give feedback to Lex: https://lexfridman.com/survey AMA – submit questions, videos or call-in: https://lexfridman.com/ama Hiring – join our team: https://lexfridman.com/hiring Other – other ways to get in touch: https://lexfridman.com/contact EPISODE LINKS: DHH’s X: https://x.com/dhh DHH’s Blog: https://world.hey.com/dhh Omarchy: https://omarchy.org Ruby on Rails: https://rubyonrails.org 37signals: https://37signals.com SPONSORS: To support this podcast, check out our sponsors & get discounts: Wispr Flow: AI-powered voice dictation app. Go to https://wisprflow.ai/lex Blitzy: AI agent for large enterprise codebases. Go to https://blitzy.com/lex NetSuite: Business management software. Go to http://netsuite.ai/lex Shopify: Sell stuff online. Go to https://shopify.com/lex LMNT: Zero-sugar electrolyte drink mix. Go to https://drinkLMNT.com/lex Plaud: AI-powered note-taking devices and software. Go to https://plaud.ai/lex Higgsfield AI: AI-based video generation, filmmaking, and creative studio. Go to https://higgsfield.ai Perplexity: AI-powered answer engine. Go to https://perplexity.ai/ OUTLINE: (00:00) – Introduction (01:14) – Sponsors, Comments, and Reflections (08:56) – Programming with AI agents (24:14) – How software will change (33:30) – AI impact on open source (43:21) – Building Omarchy Linux distro (53:05) – Vibe coding vs agentic engineering (1:06:06) – The end of manual programming (1:16:24) – Advice for programmers (1:28:31) – Surviving Internet Hate (1:37:46) – Programming setup for AI Agents (1:50:11) – Obsessing about speed (2:13:06) – Voice prompting vs typing (2:27:05) – Best AI coding models (2:43:55) – Best AI coding harnesses (2:56:57) – AI video generation and filmmaking (3:16:28) – Fatherhood (3:44:35) – Linux will win the desktop (3:55:51) – PewDiePie (4:05:25) – Future of programming (4:28:18) – Politics and immigration (4:59:55) – Longevity, over-optimization, and fear of death (5:11:38) – Eternal recurrence and future of human civization

On this week's show Patrick Gray and James Wilson are joined by guest co-host Ollie Whitehouse, the CTO of the UK's NCSC, to talk through the week's news, including: Iranian hackers take down a small-scale power generator in the UK Siemens PLCs in critical US sectors are also being targeted… We're stumped on who could be behind that one, too. Microsoft fixed a CVSS 10 deserialisation bug in Entra before someone else found it and owned the planet Prompt injection isn't going away LLMs are deceiving us meat sacks and it's a worry Much, much more… This week's show is brought to you by Okta. VP of Threat Intel Brett Winterford joins the show in this week's sponsor interview to talk James through how the company is turning its plethora of accumulated data into free alerting for its customers. They also chat about Okta's new threat intelligence product line. This episode is also available on YouTube Show notes Iran-linked hackers blamed for cyber-attack that shut down UK power plant | theguardian.com Hackers using AI to target Siemens PLCs in critical US sectors | securityweek.com Defending Against an Active Threat to Siemens S7 Series PLCs | IC3.gov Industry Alerts US charges Iranians for sprawling hacking campaign on government agencies, universities | therecord.media T-Mobile ‘chopped a cable' to expel Chinese hackers from its network | techcrunch.com The long tail of Clop's PTC hack is just beginning to emerge | cyberscoop.com CISA: Medusa ransomware hit over 500 critical infrastructure orgs | BleepingComputer Ransomware disproportionately targets medium-sized firms, straining customer relationships | Cybersecurity Dive Microsoft warns of max severity Entra ID flaw exploited in attacks | BleepingComputer Critical RCE flaw in Windows IKE Extension now actively exploited | BleepingComputer Rust supply chain attack linked to North Korean hackers | securityweek.com Grok exfiltrates user data when malicious instructions are encrypted | arstechnica.com New phishing toolkit uses passkeys to maintain access after password resets | securityweek.com Password spraying attacks surge 155x as hackers exploit MFA gaps | BleepingComputer Hackers compromise 14,500 Dahua web cameras in 35-day campaign | BleepingComputer Hackers infect Android car head units with proxy botnet malware | BleepingComputer ToxicPanda Android malware uses VPN permissions to block Google Play | BleepingComputer New Manic Android malware can exfiltrate data through nearby devices | BleepingComputer Citrix urges admins to patch new NetScaler flaws as soon as possible | BleepingComputer AliExpress caught fingerprinting visitors after sending inaudible sounds to browsers | arstechnica.com EXCLUSIVE: How a Texas student blew the whistle on a rogue AI hacking attempt | reuters.com Detections and customer notifications | Okta Threat Intelligence

Jordan Haines joins The Great Battlefield podcast to talk about his role as CTO at Run for Something, where they're building tools like CampSight, which allows candidates to track and improve how AI chatbots discuss their campaigns.

Carlos Corredor, Co-Founder and CEO of Condor Digital Marketing, is driven by a passion for interpreting data and helping marketing leaders Generate and Measure Your Pipeline with greater accuracy. ith a background in sports analytics and journalism, Carlos helps B2B companies identify which marketing activities generate qualified leads, clients, and revenue so they can invest confidently in what works.  In this conversation, Carlos introduces The Condor Pipeline Generation Framework—Understand Current Pipeline Generation, Map the Process, Move Budgets to Their Highest and Best Use, Fix Measurement Gaps, and Rinse and Repeat. He explains why marketers should begin with clients and revenue instead of clicks and impressions, how the Pipeline X-Ray exposes attribution gaps, and why budgets should move toward channels with proven returns. Carlos also discusses using BANT to diagnose conversion problems and why client champions, paid media, and events drive growth in high-ticket B2B markets. — Generate and Measure Your Pipeline with Carlos Corredor  Good day, dear listeners. Steve Preda here with the Management Blueprint, and today my guest is Carlos Corredor, Co-Founder and CEO of Condor Digital Marketing, a pipeline generation and measurement firm. Carlos, welcome to the show.  Hey, Steve. Hi, everybody. Thanks for having me. Great to be here.  It's exciting to have you and to learn about your secrets of how you generate a measurable pipeline. But before we get into it, I'm curious: What is your personal why, and how are you manifesting it through your company?  Yeah. So I've always been passionate about sports and the data behind sports, and I actually worked in sports data analysis and journalism. But ultimately, I've been passionate about interpreting data to have an advantage, whether that's playing tennis or doing analysis for baseball teams. And then I eventually started working in marketing, doing sports websites, and I saw the opportunity. In marketing in general, especially with digital, to use data to your advantage. So I would say that's really what I'm passionate about in terms of my professional life and why I enjoy what I do so much and why I get up in the morning and I really look forward to the day and even to Monday. Because obviously, it's not all fun. But ultimately, I think it comes from that passion of liking what you're doing, and the time flies when you work and you like what you do and you see that you're good at what you're doing and it's making an impact. So I would say that's why.  And have you always been a data person? Are you analytical and like to look at the numbers behind things?  Yeah, yeah. It started with sports. That's where I realized that I had, let's say, that passion at the beginning and ultimately that skill. With baseball at the beginning, it was reading the back of baseball cards and then fantasy baseball in high school, and then actually working in that. In kind of like sabermetrics and Moneyball-type analysis in college.  Because I saw, just like it happens in marketing, how back in the old days, even professionals, they were using the wrong type of data or a very antiquated way of looking at things. So it's like understanding really what has an impact and what is responsible for outcomes. That's, I think, the part that I've always thought was what's important and what I had a knack for, a talent to do that better than others. So that's why I went deep into that.  Okay. So how do you do that? So this podcast is a podcast of frameworks. So I wonder if you have a framework of how to create pipeline generation based on data, and perhaps you can share a simplified version of that with our listeners, something that can be explained in three to five steps.  Yeah, definitely. And I'll give you first the kind of like the philosophy or the mental model, and then I'll give you those steps because one comes from the other. So in marketing, with all of the data that's available, especially today, a lot of people start at the bottom. At clicks, impressions, and then they try to build a bottoms-up report to then prove what's generating leads and clients and revenue. But that is always inexact, takes forever.  What I propose is doing it the opposite: a top-down approach where you start with clients and revenue, and then start figuring out where those leads in your pipeline or clients and the closed revenue is coming from. And you will know all of that at the beginning. So that's, I think, how it starts, that framework. So the first step of the framework is to understand, which sounds really basic, but you'd be surprised today how many marketing leaders, marketing VPs, CMOs of especially mid-market, definitely smaller mid-market, and even some enterprise companies, don't have that data readily available to understand how much pipeline did we, as a marketing department, generate, let's say, last year. So that's, I think, the first step, is understanding that. It's asking your team for a report that says that. Now your team's going to come back and say they won't know the full picture. Maybe they know 10%, maybe they know 90%. But they're going to show you something. So then is the second step. You're going to start adjusting your investments to what you're seeing there, and at the same time, you're going to start fixing the dark holes or what you can't see.  And then simply step number three is rinse and repeat every, let's say, quarter at the beginning. And obviously, there's nuances of how exactly you should adjust and what exactly you can fix. But ultimately, that would be the three-step approach that you asked about.  That's fascinating. So the understand piece is understanding your pipeline or how you're generating the pipeline? What is it? Understanding what?  Yeah. So actually we have a name for that first step. We call it the Pipeline X-Ray. So let's say you start a new job as a CMO of a new company. Or simply you've been in the job for a while and you're listening to this and you say, “Okay, actually, I've never thought about it that way.  Let's sit tomorrow with my team and ask the question: How many qualified leads and closed clients have we, as marketing, generated so far this year and, let's say, last year?” That is understanding that. Now, I'll tell you, I'd be very surprised if the marketing person or the marketing team or the leader has that data in a way that they can say with 100% certainty what the answer is. In terms of, “We've closed these four clients, and we've had 72 qualified leads.  And out of the 72, 50 have come from our paid search campaigns, 10 have come from events, and then the others have come from organic.” In an ideal world, that's the type of answer that you want. But in the real world, again, very rarely do you have that clear understanding right then and there. So that's when step number two becomes, okay, let's close the gaps to be able to have an understanding.  Okay. So essentially, when you say adjust and fix, then are you talking about adjusting and fixing the process of generating clients, or actually mapping the gaps in the pipeline first?  Yeah, so that's a great question. The adjust, I mean move budget around. Not necessarily increase budget. You have to prove what's working. And obviously, if you don't have the full picture and understanding, you cannot just go to your CEO and say, “I need more budget.” So with the same budget that you have, what can you pause and move around towards the things that step number one told you with certainty are working. So if, let's say, out of the 50 qualified leads that you generated, you saw that half of them came from your paid search campaigns, then you say, “Oh, okay.” And then you don't see anything, let's say, for conferences, and now you're going to 10 conferences a year and you're spending a million dollars on conferences, and you're only spending $200,000 a year on your paid media spend. Then you say, “You know what? I'm going to stop. I'm going to pause. We're not going to go to these two conferences this year, and I'm going to move those $200,000, and we're going to double our spend in Google Ads,” for example. That's what I mean with the adjust piece. It could be the opposite. It could be pause paid search and then be more aggressive on our conference strategy. It could be, let's start a paid social campaign, whether that's LinkedIn or programmatic ads, or let's be more aggressive on our PR because right now our leads have come from interviews that our subject matter experts have done in certain types of podcasts or YouTube channels.  But that's what step number one is. But adjust is move budget around. Put your stocks where the returns are positive and where you can expect a better return almost immediately, or at least in the next upcoming months. And then the fix is particularly around the measurement gaps. The fix is what you can't see, right, on step number one. Step number one is understanding. And a report with all of that. When the person that does the reporting for you came back, or when you did it yourself or whatever, probably a lot of leads are like, “Ah, now it says direct traffic. What is that?” Obviously, they didn't just come and wake up one day and say, “Oh, I'm just going to go to condoragency.com.” No, they heard you somewhere, but you're still not sure. You won the client, you know you won the client, the client's paying you money, but you're not sure. So maybe, okay, what needs to improve in our measurement framework.  Usually, you can start with your CRM, your HubSpot, Salesforce, for instance, or whatever you use. There's some web analytics that might need to happen. You need to connect your advertising platforms. You're probably going to need to start talking to your sales team so they ask the right questions when they have discovery calls with prospects. I mean, there's a few things you can do, but I'm talking specifically about measurement gaps so you can have the full picture.  So when you talk to new prospects or clients, can they answer one most of the time?  They can partially answer one. I would go a step beyond because, I mean, that's not the sexiest answer. I would say it's usually, let's just say, around 50% of their leads and clients, they can know who was responsible. And then there's a couple of parts there. First and foremost, not only for your sake, but for the sake of your alignment with the C-suite and with the CEO and the CFO and even the sales team. You want to know, is marketing responsible for this? Number one. Because then that's very important.  Because that's what's going to justify the existence of the marketing team. Then later, if it came from a paid search campaign or a paid social or a conference, if those all are in the marketing budget, that's secondary. But most importantly, you want to make sure that, number one, you're bringing pipeline as a marketing department, and number two, you know exactly what pipeline you're bringing. Not only you, but then also your CEO and your CFO. So then it's like a luxury, let's say, to see if it comes from, the tough part is that you won't know that it comes from marketing unless you're tracking paid search and you're tracking conferences in the CRM the right way. So obviously, they are related in that way.  Okay. Love it. So understand your pipeline generation, and then adjust the budget to make sure you're supporting the ones that generate the most, and fix those that are not optimized. So maybe optimize them or replace them or come up with a new one. How else do you fix other than your measurement gaps?  Okay, you fixed the measurement gaps. Now you can measure it. You have a full picture. Then you have a slate of options, and how do you know what to choose if you're not doing enough?  Yeah. So I think there’s a couple of things there. One is understanding if you… Because, obviously, you always want to generate more pipeline. So you have to then say, “Okay, is my problem that I'm not generating any interest in the first place at all?” Like, there's nobody visiting my website. Or even downloading some pieces of content, what traditionally is called conversions or marketing-qualified leads. Obviously, that's not the goal.  The goal is that they turn into clients. But you have to know that if people are not visiting your website and you're not seeing marketing-qualified leads coming into your CRM, then you have to do certain things. Whereas if the problem is, “Okay, no, that's not the problem, Carlos,” and this is actually more common, which is a little counterintuitive, but the more and more that we work with mid-market clients, we realize this is the case.They are generating marketing-qualified leads. There is activity in the CRM. There are companies, new companies, that you see are visiting your website, downloading and consuming content. But then, for some reason, they are not becoming clients. So that's where we have to dig in and understand. Maybe they downloaded a white paper that was very educational in nature. And they're not ready to buy. Which is fine, and I'm not saying you have to not show that white paper, but you know that white paper is not going to bring you ready-to-buy customers.  So that's when we have the concept of what sales and marketing people call a BANT-type of lead, which is a lead that has the budget, the authority, the need, and the timing. You want, obviously, a lead that has the four things. Now you start, you measure. Okay, we had 10 leads, and they had, let's say, the budget and the authority. They were the CTO. The lead of the technology department in the company that we know has the budget. But they just downloaded this and didn't convert. They didn't have, let's say, the timing or the need.  Then maybe you rely more on, for example, paid search, which is a channel that, by searching the right keywords, the bottom-of-funnel keywords, for example, we are a pipeline generation firm. If somebody is looking for, “What is Google Ads?” That's educational. Now, if somebody's searching for “experienced agencies in B2B managing Google Ads.” Now, that's somebody that's ready to hire an agency to manage their Google Ads. So that's why, for example, in this case, if the component that's lacking is the need and the timing, paid search could be a way to do it. Or intent data, which is now something that is out there not only via paid search, but you identify certain signals and you can target them on programmatic ads or YouTube or whatever. That's another alternative. So that's something that you could do, for example, if you have a pain in moving leads down the funnel and closing clients, and you also realize that you're talking to the right people, but then they're simply not converting.  And the opposite. You get a lot of people that need your service. But they may be too small, or they may be just a manager and they don't have the authority to approve a high-ticket service. Then you go towards maybe LinkedIn targeting, or you do a campaign that is based more on account-based marketing, or ABM. Where you know you're talking to the right people. So again, that's another adjustment that you can make. So I don't know if I… Sorry if I deviated a little bit from the question, Steve, but hopefully that's still—  No, it makes sense. It makes sense. So first you want to measure, and then you diagnose. If you've got some activity but it's not converting, why is it not converting? Maybe it's not the right approach to build trust. Maybe there's another approach.  And then you look at the different elements: budget, authority, need, timing. That makes sense. So let me turn it back to you. So what drives growth in your business?  So for us, I would say if we do that, let's say, Pipeline X-Ray. And we actually did. We've been in business for almost 10 years now. And if you would do a Pipeline X-Ray, the number one driver of leads and new clients are, let's just call it, Condor champions that switch jobs. And not switch jobs that were working with us, but they were working with one of our clients.  And they worked with us, and they saw the work that we did, and they ended up moving to another agency within the same space, for example, or in B2B services, or even if it's something a little more niche like tech services, which is an area that we also specialize in. And then they say, “I already worked with Condor for either measurement or paid search campaigns or demand generation in general, and I like working with them, so they're going to call us.” And then some people, they switch multiple jobs. So embracing that and obviously using that to fuel and to focus even more on doing a great job and maintaining relationships with people, obviously most importantly while they're a client, but even if they switch, not forgetting about them. That has been the main driver. Obviously, we don't want to only rely on that. And then more recently, we've given more structure to our own sales and marketing department for that. And, for example, we closed a client that came via a paid search campaign. But that's still… We haven't scaled those yet.  We're still making sure. We're still in that measurement phase where, yeah, we're putting budget behind a few things and some of them seem to be working better, but not yet at the point of truly scaling that. We're ultimately also a relatively small firm, which obviously makes decisions differently than if you are, let's say, a mid-market or enterprise. But those, I would say, in order of importance, have been our three main drivers of growth: the champions that switch jobs, number one, and then I would say secondarily, paid media and events.  Yeah. So these are the three things. And what about the events? Why do you put events as a third? I'm just thinking that you're a B2B company and trust-based. Would events not be better than paid media?  I would say they're not mutually exclusive. Actually, they rely a lot on each other. And honestly, for us, I just put number two and three, but I would say they're tied for second, and then the other ones are four and below. And the reason why I think events are important, what we're seeing not only for us but for our clients, the outbound activity is really saturated.  I think cold email or cold outreach in general, because it used to be via email, now it's on LinkedIn as well, it's really, really saturated. It's really hard to be heard or to get a reply with cold outreach in general. Paid media, you can be a little bit more creative because you have visuals. Whether that's video that hopefully you can leverage. So I'm a believer in paid media more than the actual cold outreach via email or LinkedIn. But then the events are also great precisely because of that.  People are saturated and tired of being bombarded with messages from people they don't know. Whereas especially after COVID, people started going back to both the office and simply going out there. It doesn't have to be a big yearly conference. It can be just a dinner where you invite four or five people and talk about certain topics or any in-person activity. Well, I mean, a webinar can even be considered an event. Where you're educating your audience on certain things. And especially if your target audience is more on the manager side or below, or director and below, webinars can be an avenue.  But to answer your question, I think that personal connection is really, really powerful. And people forgot about it with, let's say, the boom of cold outreach and digital and now AI, and especially during COVID. But definitely in the last few years, we've seen not only that people are more willing or prefer to meet people in person, but we see that in the data as well, We see cold outreach campaigns that are bringing less and less results. And then when you connect in person.  Especially high-ticket. I also give this example. If you're selling B2B services, which are usually high-ticket. It's a project of either $50,000. It could be an engagement of $2 million over two years. Obviously, you want to know the company, but you also want to trust the human that is going to deliver on that promise. I always give the example: If you're selling an iPhone cover that costs $25, yeah, maybe you can get away with a pretty image on an Instagram ad. You click and you buy. Boom. Great. You can fully leverage digital for that.  But when you're selling a cloud migration project of a million dollars, you're going to want to talk to somebody, trust that person, dig in a little bit more, have a couple of meetings. So it's more complex. So in particular for those instances, that's why I think the personal connection, that it's even better if it starts at an event, or however you manage to do it, helps a lot.  So for Condor, do you make a distinction between B2B companies and B2C, and where you can help them the most?  Yeah. We have a couple of direct-to-consumer clients, but the majority of the work that we do is either for B2B or, if not B2B, it's lead generation. So e-commerce, for example, is a different world. E-commerce, as I mentioned, depending on what you buy, it's immediate. You track things. You have a platform like Shopify or something similar. It's a whole different world. Whereas that's immediate, and you can see everything, and it's all kind of automated and based on an inventory.  Whereas in either B2B services or lead generation, it's more about, okay, what happens after the initial action, after that initial either visit or conversion. Because a conversion is not a purchase. In e-commerce, in direct-to-consumer, in the example that I gave you, we made it. We sold the cover. That's our business. In here, it's like, okay, they downloaded a white paper. Or they signed up for a webinar, but that's only the first step of a long journey of closing, again, a $1 million service client.  So we specialize in that. In what needs to happen, not only to generate the initial raise of hand, but to make sure that the people that raise their hands are the right people, because otherwise they're not going to end up buying. And ultimately, the entire process of lead generated to client closed. Which is a big universe in itself. So that's where we want to focus.  So you basically help them not just to get the leads but to convert the leads and turn them into a client.  Right. Right.  So Carlos, if you had a magic wand and you could fix just one thing in your business in the next 12 months, what would you use the magic wand for?  I would say accelerate. I would accelerate by five or 10 years the structure and how mature our sales and marketing team is. I would love to wake up tomorrow morning and have a team of five people in the marketing department and five people dedicated to sales, with SDRs and a sales leader, that is already generating, that we're closing 10 clients a month. So I would say that's… But that obviously takes time.  And you want to go one step at a time, otherwise, to prove ROI and to grow without, let's say, wasting unproven budget or wasting money. But I think a lot of owners—I don't know if it's a cheap answer—but I think a lot of owners would probably answer the same thing.  Yeah. So essentially what you need to do is you need to have scalable sales and marketing so that you can just add people and it's going to—it's like a coin-operated system, right?  Yeah. Yeah.  So if the listeners would like to go through that process and they would like to understand, okay, how do we map our leads, where they come from, evaluate it, and then adjust and fix and scale, where can they learn more and how can they connect with you? Yeah.  So if they go to our website, it's condoragency.com. Condor, like the bird. There are some options there on how to work with us or even some information, even if they want to try and do it by themselves, right? Again, what I mentioned earlier, the Pipeline X-Ray. It's a quick project that we do to get to that, where you can start seeing some valuable information to take action on fairly quickly.  We can get that done in a couple of weeks, the exercise of the Pipeline X-Ray, so then you know what to start adjusting and fixing. And obviously, you can contact me directly also on LinkedIn or via our website. I'm glad to obviously have a subsequent conversation and see if and how we can help.  Awesome. So if you are out there and you want to improve your sales and marketing, then you have to start with the Pipeline X-Ray because you are getting leads, you just don't know where they are from and how effective they are, and then how you tweak the process so that you're putting energy behind the more effective ones and readjusting your budget, and then fix the gaps.  So Carlos can help you with that, right? So make sure you reach out to Condor and get the X-Ray. So Carlos, thanks for coming. And if you enjoyed this conversation, then make sure you subscribe and follow us on YouTube, Apple Podcasts, because every week I bring a couple of entrepreneurs who are sharing their frameworks with you. So Carlos, thanks for coming, and thanks for listening. Important Links: Carlos's LinkedIn Carlos's website

Recognizing failure patterns is the closest thing an innovator has to seeing the future.   If you can recognize the patterns, you can change the future, because most failures are not original. They repeat, and that repetition is the pattern: the same handful of patterns reappearing in one organization after another, decade after decade.   This one stings a little.   In 2011, Bill Geiser told me, almost word for word, how the project we had spent the past two years building was going to fail. He saw the pattern before I did; I heard him say it, and I never forgot it.   The failure still happened.   This is not a pre-mortem. A pre-mortem imagines new ways your plan could fail. Recognizing failure patterns means learning from failures that have already happened elsewhere and spotting the early signals before you repeat them, while there is still time to act.   By the end of this episode, you will have four patterns in your own library, a five-minute way to check any project against them, and the four steps to take when you find one.   Let's get into it. The Smartwatch We Killed In 2004, Fossil hired a watch-technology executive named Bill Geiser to help build innovative technology for their watches. A few years later, he and I started spending real time together, me as HP's CTO, him running watch technology at Fossil. Between us, we had an idea we both believed in: a connected wearable, years before anyone used that phrase, co-innovated by HP and Fossil, with each bringing its expertise.   Fossil named the resulting platform the MetaWatch. It ran an ultra-low-power processor with a 96 by 96 display, an accelerometer, and Bluetooth. It was designed to last a week on a charge, and it shipped with a full developer kit so anyone could build apps for it. We revealed the partnership in March 2011, at an HP event in China. And between us, we had the one thing Apple did not have in 2011: distribution. HP held roughly ten percent of consumer-electronics shelf space. Fossil sold through twenty thousand retail stores that carried its watches.   Bill saw the ending before anyone. He told me in 2011: "Phil, I wouldn't be shocked if Apple evolved the Nano to take advantage of this space. They'll legitimize it in consumers' minds worldwide."   So the man building the watch spotted the failure in advance, out loud. And naming it changed nothing.   The signs kept arriving in plain sight. HP went through three CEOs in thirteen months. In August 2011, Leo Apotheker killed HP's consumer mobile strategy and WebOS, which removed the platform that made a smartwatch matter to HP at all. The battery lasted three to four hours against the original target of a week. We ran month-long approval cycles for changes that startups could implement in days.   Then I went out on medical leave. When I came back six weeks later, HP had killed Palm, WebOS, and the connected wearable project.   Here is what the ignored warning turned into. The Apple Watch shipped in April 2015. It sold 4.2 million units in its first quarter, and by that fall Apple was selling three out of every four smartwatches on the planet. The market we walked away from grew from three hundred thousand units in 2012 to forty-five million by 2018, and Apple held fifty-one percent of the market share.   The idea was never the hard part. It never is. The hard part is committing. What Recognizing Failure Patterns Means Nothing that killed the MetaWatch was new, and none of the signals were faint. They were loud; they were ignored, and each one was a pattern that has killed projects for decades.   Recognizing failure patterns has two halves. The first is building a library of how failures repeat. The second is matching the situation in front of you against that library, and forcing what you find into an actual decision while the fix is still cheap. Bill did the first half. Neither of our companies did the second, and the gap between those halves is where the Apple Watch came from.   Here are four entries for your library, straight from this one failure. Each one ends with a test question. By the end, you will have a four-question checklist, and then I will show you what to do when a pattern shows up. Pattern 1: Success Protects Itself Fossil's traditional watch business grew from $950 million in 2004 to $3.25 billion by 2013. It was tripling while we were building the thing that might replace it, and that growth made cannibalizing it politically impossible. Fossil never had to kill the MetaWatch outright. Fossil positioned the watch as a two-hundred-dollar development platform, something no ordinary customer would ever be handed at a retail counter.   When we constrain what we're innovating so it doesn't risk the present, we've lost the future.   Test it: Is the new thing priced, staffed, or positioned so that it cannot hurt the current thing? If the answer is yes, this pattern is already running. Pattern 2: The Warning That Changes Nothing Bill's warning was specific, early, and exactly right, and it still changed nothing. I heard it directly, and hearing is not the same as deciding: nobody re-ran the plan with "Apple arrives and legitimizes the category" as an input, no roadmap changed, and no budget moved.   Test it: What decision changed after the warning? If the honest answer is none, the warning was never acted on, no matter how many people remember hearing it. Pattern 3: The Problem Nobody Owns A week of battery life was the MetaWatch's central promise, and it shipped at three to four hours. Both companies saw the gap. No one owned fixing it. The hardest problem on the project sat on the seam between two companies, and problems that sit on seams get reported, tracked, and carried forward without ever belonging to anyone who can be asked why the problem is still there. We ran that partnership for two years and never settled whose job it was to lose sleep over the one number that mattered most.   Test it: Who owns the hardest problem, by name? If the answer is a partnership, a committee, or a pause, then nobody owns it. Pattern 4: The Pace Mismatch Earlier, I shared that we ran month-long approval cycles for changes a startup could implement in days. That is a pacing problem: the organization's internal pace versus the market's. A smartwatch in 2011 was a fast-moving product running through slow-moving machinery, and no amount of talent inside the project could close that gap. The delay was structural, not personal.   Test it: How long does one small change take to approve, against how fast the market moves? Time a real one. Do not estimate it. Five Minutes on a Project That Died The four patterns are the start of your library. Before you use it on a live decision, test it on a dead one.   You have a dead project in your past. Everybody does. Pick the one that still stings and give it five minutes against the four test questions.   Was an existing success being protected while the project starved, in pricing, staffing, or positioning? Did people raise a warning, and what decision changed after it was said? Who owned the hardest problem, and can you name the person? And how long did a small change take to approve, against how fast the market was moving?   When I run the MetaWatch through those four questions, I find all four patterns. Your project will probably show fewer. Every pattern you find is one you will now recognize as it happens on the project you are working on right now. The Four Steps When You Spot a Failure Pattern Which brings up the harder half of the skill, because recognition alone did not save us. Suppose you had been standing next to me in 2011, holding all four of these patterns. It would not have been enough. Being right about the future means nothing without the organizational machinery to act on that insight.   So when a failure pattern appears on a live project, follow this sequence.   Step one: Say the failure pattern out loud, in the room where the decision lives. Not in the hallway afterward. Use the pattern's name.   Step two: Get it onto the decision memo. A warning that lives only in conversation changes nothing. Write the pattern and what it costs into a document that will drive a decision.   Step three: Attach an owner. If you identify a critical problem, assign it to one person. Not a team or an organization. Someone you can ask next sprint why the problem is still there.   Step four: Attach a date. Being early provides an advantage, and a failure pattern without a date on it fades unnoticed.   Bill was right for four years, and Apple was the one who acted on it. That could have been us if we'd had the organizational courage to back our vision with meaningful resources. Conclusion You now have what nobody handed me in 2011: four patterns of failure, a five-minute check, and the four steps to run when you spot one. What you do in the room where the decision lives is the part Bill's warning never got. Additional Resources How HP and Fossil Handed Apple the Smartwatch Market: The inside story of vision without execution: why being right about the future means nothing without the courage to act on breakthrough insights. https://www.philmckinney.com/how-hp-and-fossil-handed-apple-the-smartwatch-market/ The story of MetaWatch with its founder, Bill Geiser: https://www.philmckinney.com/the-difference-between-a-good-idea-and-a-great-idea-is-the-timing-s11-ep25/

Some crypto products work with multiple chains on different post-quantum paths. NEAR's Illia Polosukhin and Ledger's Charles Guillemet discuss how they manage that challenge. ======================================================== Thank you to our sponsor! ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Visit⁠⁠⁠ 1inch.com⁠⁠⁠ to swap tokenized securities, crypto and more. Simple. Secure. Self-custodial. Whatever asset you're buying - swap it at⁠⁠⁠ 1inch.com⁠⁠⁠ ======================================================== In March, a Google research team published a paper on breaking cryptographic keys with a quantum algorithm, so cautious about the finding that it released only a zero-knowledge proof the algorithm existed. Weeks later, an EigenLayer AI competition improved on that method in roughly 48 hours. Illia Polosukhin, co-founder of NEAR Protocol, and Charles Guillemet, CTO of Ledger, join Laura Shin for an update on the quantum threat whose deadline could be approaching fast. Both are creating products that deal with multiple chains that all have different post-quantum approaches.  They discuss why, of the three NIST-standardized, post-quantum algorithms, the crypto industry has splintered into different chains working with different ones, whereas most industries are converging on one, called lattice-based. They also debate what to do with Satoshi Nakamoto's bitcoins: do nothing, freeze them, or freeze and tail-emit new bitcoin, an option Guillemet favors even though Bitcoin's leaderless governance makes consensus hard to reach. Host: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Laura Shin⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, Host / Unchained Guests: ⁠Illia Polosukhin - Co-founder of NEAR Protocol ⁠Charles Guillemet - CTO of Ledger Timestamps

The conventional wisdom in AI is that the next breakthrough will come from more compute, more data, and larger models. But what if the next leap comes from somewhere else? In this episode, Max Welling—co-founder and CTO of CuspAI and professor at the University of Amsterdam—argues that physics may provide some of the ideas behind the next generation of AI systems. We begin with CuspAI's work using generative AI to design entirely new materials for semiconductors, batteries, carbon capture, and clean energy. Max explains how foundation models for chemistry, agentic workflows, simulation, and automated experimentation are dramatically accelerating the search for new materials and reshaping scientific discovery. The conversation then broadens into a deeper question. Beyond giving AI new scientific problems to solve, can physics also teach us how to build better AI? Max explores surprising connections between machine learning and thermodynamics, why waves may become a new computational primitive for neural networks, and how concepts like symmetry breaking and statistical physics could inspire AI architectures beyond today's scaling paradigm.

What happens when your autonomous coding agents need to navigate your core infrastructure? Do you hand them the keys and hope for the best? (gulp!) This week on Dev Interrupted, 1Password CTO Nancy Wang teaches the golden path for agentic security: just-in-time secrets that grants AI "access without custody." She also shares her CTO playbook for measuring true agentic ROI beyond raw PR volume, explains why 1Password has officially replaced traditional coding interviews with agent builder tests, and confesses she's shipping PRs again with her own fleet of agents between meetings. Like many CTOs we've had on the show, Nancy reminds us that code is cheap now, and review is what's expensive now. We get into tactics for addressing that bottleneck.Get the guide: The AI engineering productivity gap - how elite teams pull ahead in 2026Register: Dev Interrupted Presents: The Software Factory RoundtableFollow the show:Subscribe to our Substack Follow us on LinkedInSubscribe to our YouTube ChannelFollow the hosts:Follow AndrewFollow BenFollow DanFollow today's guest:1Password: Explore the enterprise password and identity platform at 1password.com1Password for Developers: Dive into the new developer tooling, credential brokering, and secure AI workflows at 1password.devOracle Red Bull Racing: Read more about the F1 team's systems engineering at redbullracing.comConnect with Nancy: LinkedIn OFFERSStart Free Trial: Get started with LinearB's AI productivity platform for free.Book a Demo: Learn how you can ship faster, improve DevEx, and lead with confidence in the AI era.LEARN ABOUT LINEARBAI Code Reviews: Automate reviews to catch bugs, security risks, and performance issues before they hit production.AI & Productivity Insights: Go beyond DORA with AI-powered recommendations and dashboards to measure and improve performance.AI-Powered Workflow Automations: Use AI-generated PR descriptions, smart routing, and other automations to reduce developer toil.MCP Server: Interact with your engineering data using natural language to build custom reports and get answers on the fly.

Este conteúdo é um trecho do nosso episódio: “#361 - Compra Agora: como a IA resolve 98% dos chamados na hora”.Nele, Thaise Hagge, COO & CTO do Compra Agora, explica por que a reconstrução completa da tecnologia da empresa não parou na parte técnica: exigiu revisar processos que todo mundo tratava como intocáveis e engajar cada pessoa envolvida na migração para entender por que aquele trabalho importava. Ela conta como isso ajudou a empresa a chegar a 25% de eficiência na jornada de compra. Ficou curioso? Então, dê o play!Assuntos abordados:Gestão de mudança;Processos "imutáveis";Eficiência operacional;Migração de tecnologia. Links importantes:NewsletterDúvidas? Nos mande pelo LinkedinContato:  osagilistas@dtidigital.com.brOs Agilistas é uma iniciativa da dti digital, uma empresa WPP #eficienciaoperacional

Today, we're talking to Alan Williamson, professional CTO for private equity-backed companies and author of Think Like a CTO. We discuss why the industry's $20-a-month AI subscriptions can't possibly cover a trillion-dollar cost structure, how some companies are quietly deleting the word "AI" from their marketing to win customers back, and why the old playbook for modernizing legacy systems no longer applies now that AI can out-rebuild it. All of this right here, right now, on the Modern CTO Podcast! To learn more about Alan Williamson, check out his website here

Richard Entrup is unusual in quantum circles: he's not a physicist, and he doesn't pretend to be. He spent decades as a CIO, CTO, CDO, and CISO at organizations including Verizon, Christie's, Disney/ABC, Time Warner, and Tiffany & Company before joining KPMG to lead its Emerging Solutions practice. That background — deep operational experience on the client side — shapes everything about how he thinks about quantum. He's not selling a hardware roadmap; he's thinking about what it actually takes to get a large, complex organization to change its cryptographic infrastructure before a threat materializes.The conversation matters now because the signals are accelerating. NIST has finalized its first post-quantum cryptography standards, executive orders in the US are pushing federal agencies toward PQC migration, and the algorithmic efficiency gains that reduce the qubit threshold for breaking RSA-2048 keep coming. Listeners who work in enterprise technology, cybersecurity, or quantum strategy — or who advise organizations that do — will find Entrup's practitioner perspective a useful counterweight to the more hardware-focused conversations that dominate the field.What We Get IntoWhy Q-Day's exact date is the wrong question — and why the more important issue is how long it will take enterprises to even inventory their cryptographic exposure, let alone remediate itThe scale of the cryptographic migration problem, including why a single laptop may contain hundreds of individual cryptographic components and why upstream/downstream API dependencies make this a supply-chain-wide challenge, not just an internal IT projectWhy "harvest now, decrypt later" creates urgency today, regardless of when fault-tolerant quantum computers arrive — and how compliance and regulatory timelines interact with that threat modelWhat crypto agility actually means in practice — moving from a "set it and forget it" cryptographic posture to a dynamic, continuously monitored framework, including the pressure SSL certificate renewal windows are already creatingHow KPMG built its PQC practice, incubated it within the firm, and handed it off to the cybersecurity advisory team as a core service offeringThe "good quantum" side of the ledger — how KPMG's emerging research function is approaching quantum computing as a source of competitive advantage, not just risk, and what sectors are furthest along in exploring itThe AI-quantum convergence, including Entrup's observation that AI is already being used to read and crack code — and what that means for the urgency of cryptographic modernizationWhy the enterprise quantum opportunity still has a long tail, and how the current moment compares to the early infrastructure phase of the internet — when everyone was talking about TCP/IP and DNS, not Uber or NetflixResources & LinksGuest & OrganizationRichard Entrup — Worth Magazine Profile — Career arc from CIO/CISO roles at major global brands to KPMG's Emerging Solutions practiceKPMG Quantum Dawn (2025) — KPMG's enterprise quantum readiness hub, introducing the Q-PREP framework and PQC implementation services, with Entrup as named leadReports & ResearchKPMG — "The Quantum Threat Is No Longer Theoretical" (2026) — The threat brief discussed in this episode, charting the rapid decline in qubits needed to crack RSA-2048 and urging immediate PQC migrationKPMG — "From Theory to Impact: Real-World Results in Quantum Machine Learning" (2026) — KPMG's joint report with IBM and Kipu Quantum on measurable quantum ML results on real hardwareKPMG — "Prepare Now for Quantum Cyber Risk" — Board Leadership Article (2026) — C-suite and board-level guidance on integrating quantum risk into enterprise oversightarXiv — "Quantum-enhanced satellite image classification" (2026) — The underlying research paper behind the KPMG/IBM/Kipu Quantum ML resultsEcosystem & EventsChicago Quantum Exchange — KPMG Joins CQE (October 2024) — Announcement of KPMG's formal CQE membership, referenced in the episode as part of the firm's ecosystem-building strategyKPMG 2026 Quantum Consortium — The inaugural KPMG Quantum Consortium event (March 2026, Orlando) discussed in the episodeIndependent CoverageQuantum Computing Report — KPMG joins Chicago Quantum Exchange (2024) — Independent coverage of KPMG's CQE partnership and enterprise quantum strategyQuantum Zeitgeist — Kipu Quantum satellite imagery coverage (Feb 2026) — Independent analysis of the KPMG/IBM/Kipu hybrid QML resultsKey Quotes & Insights> "It's not if but when. And it could be five years, could be three years, could be ten years. The fact is organizations are not gonna be ready. And that's the scary part." — Richard Entrup on Q-Day> "This is not just the CISO. This is gonna be the software engineering app dev guys. This is gonna be all your partners, upstream and downstream, who have to also be compliant — because if you change your crypto and they don't, that stuff's gonna break." — On why PQC migration is an enterprise-wide, supply-chain-wide problemInsight: Entrup draws a sharp distinction between the "bad quantum" (cryptographic risk requiring urgent defensive action) and the "good quantum" (competitive opportunity with a longer tail) — and argues that most organizations aren't adequately addressing either.Insight: The analogy to the early internet is deliberate: just as the 1990s were consumed with TCP/IP and DNS rather than the applications those protocols would eventually enable, the current quantum moment is still largely an infrastructure conversation — and that's normal, not a sign of failure.> "AI is expediting all of this. If AI is doing one thing, the use case is reading code and cracking it. That's pretty scary." — On the intersection of AI capability and cryptographic vulnerabilityRelated EpisodesEp. 81 — Quantum LDPC Error Correction with Larry Cohen and Paul Webster — Directly relevant: Cohen and Webster discuss how QLDPC error correction reduces the qubit overhead needed for RSA cryptanalysis, the technical underpinning of the threat timeline Entrup describesEp. 38 — Quantum Machine Learning with Jessic...

Quantas horas o seu time ainda perde resolvendo o que a tecnologia já deveria ter resolvido sozinha? Neste episódio, recebemos Thaise Hagge, COO & CTO do Compra Agora, plataforma B2B que nasceu dentro da Unilever e hoje conecta mais de 30 indústrias, 150 distribuidores e cerca de 530 mil lojistas em todo o Brasil. Ela conta como a reconstrução completa da tecnologia da empresa, migrada por regiões ao longo de um ano sem parar a operação, mudou a forma de decidir prioridades e permitiu que a inteligência artificial passasse a resolver 98% dos chamados no momento em que são abertos. Ficou curioso? Então, dê o play!Assuntos abordados:Migração de sistemas;Gestão de mudança;CTO e COO;Programa Conecta;IA em atendimento;Jornada de compra B2B;Expansão de segmento;Eficiência operacional.Links importantes:NewsletterDúvidas? Nos mande pelo LinkedinContato:  osagilistas@dtidigital.com.brOs Agilistas é uma iniciativa da dti digital, uma empresa WPP #eficienciaoperacional

Wie können DNA-Nanopartikel die medizinische Diagnostik radikal besser machen? Was hieße das für die Früherkennung von Krebs oder Demenz? Und wie können Biotech-Startups und Big Pharma gut zusammenarbeiten? Unser Host Thomas Ramge spricht mit Dr. Jonas Funke, Co-Gründer und CTO von Ulrabright Biotech.

As space infrastructure has continued to expand, developing secure space systems has become just as important as launching the spacecraft themselves. In this week's episode, host Maria Varmazis sits down with Filip Rezabek, co-founder and CTO of Space Computer, to talk about some of the technologies being created to secure space infrastructure in orbit. The two discuss the importance of establishing a chain of trust in space and the challenges of securing hardware against supply chain attacks. Like what you heard? Be sure to subscribe to our free Signals and Space Briefing⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, our Sunday newsletter covering the intersection of cybersecurity and space. Subscribe at: ⁠⁠⁠https://thecyberwire.com/newsletters/signals-and-space⁠⁠⁠ Is there a topic or person you'd like to hear on our show? You can send your questions and feedback to ⁠⁠⁠space@n2k.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. You can also fill our our audience survey: ⁠⁠⁠https://www.surveymonkey.com/r/NJYCN2P ⁠⁠⁠ T-Minus: Space-Cyber Briefing is a production of N2K CyberWire. ⁠⁠⁠N2K⁠⁠⁠ is your nexus for discovery and connection for people, technology, and ideas shaping the future of secure innovation. Learn how at ⁠⁠⁠n2k.com⁠⁠⁠.

As space infrastructure has continued to expand, developing secure space systems has become just as important as launching the spacecraft themselves. In this week's episode, host Maria Varmazis sits down with Filip Rezabek, co-founder and CTO of Space Computer, to talk about some of the technologies being created to secure space infrastructure in orbit. The two discuss the importance of establishing a chain of trust in space and the challenges of securing hardware against supply chain attacks. Like what you heard? Be sure to subscribe to our free Signals and Space Briefing⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, our Sunday newsletter covering the intersection of cybersecurity and space. Subscribe at: ⁠⁠⁠https://thecyberwire.com/newsletters/signals-and-space⁠⁠⁠ Is there a topic or person you'd like to hear on our show? You can send your questions and feedback to ⁠⁠⁠space@n2k.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. You can also fill our our audience survey: ⁠⁠⁠https://www.surveymonkey.com/r/NJYCN2P ⁠⁠⁠ T-Minus: Space-Cyber Briefing is a production of N2K CyberWire. ⁠⁠⁠N2K⁠⁠⁠ is your nexus for discovery and connection for people, technology, and ideas shaping the future of secure innovation. Learn how at ⁠⁠⁠n2k.com⁠⁠⁠.

Network to Code’s Jason Edelman, Founder and CTO; and Jeff Bradbury, VP of Marketing of Network, join host Scott Robohn for this sponsored episode to discuss open-core done right — community first, and creating a path to scalable automation results for enterprise success. They update Scott on Nautobot 3.1, which includes AI and AI agents... Read more »

Network to Code’s Jason Edelman, Founder and CTO; and Jeff Bradbury, VP of Marketing of Network, join host Scott Robohn for this sponsored episode to discuss open-core done right — community first, and creating a path to scalable automation results for enterprise success. They update Scott on Nautobot 3.1, which includes AI and AI agents... Read more »

Natalie Brunell sits down with Alex Leishman, Founder, CEO & CTO of River. Alex shares what River's own client data reveals about who is buying and selling Bitcoin right now — and why big institutions are quietly accumulating during this downturn while everyday investors sell. In this episode: Is Bitcoin still Bitcoin if Wall Street owns a growing share of it? Why most people never move their Bitcoin off an exchange How scammers actually steal Bitcoin, and the simple habits that stop them Whether quantum computing is a real threat to your Bitcoin, and how River is preparing Why Alex has no plans to take River public, even as competitors go the other way What Alex tells people when everyone around them has turned bearish Follow Alex Leishman on X: https://x.com/Leishman  and sign up for River at https://www.river.com/natalie  ---- Order Natalie's new book "Bitcoin is For Everyone," a simple introduction to Bitcoin and what's broken in our current financial system: https://amzn.to/3WzFzfU  ---- Borrow against your Bitcoin without selling it. Ledn offers Bitcoin-backed loans built for serious holders, with rates that get lower as your loan size increases. With Ledn's custodied loan product, your Bitcoin is held in custody and not lent out. Ledn has operated through multiple market cycles without a loss of client assets and publishes Proof of Reserves so you can verify what they hold. Get 0.25% off your first loan at ledn.io/natalie. Terms apply — see the site for details. ---- Bitdeer Technologies Group (NASDAQ: BTDR) powers AI and Bitcoin mining infrastructure with 3 GW of secured global energy — and owns the entire stack, from equipment manufacturing to data centers to proprietary orchestration software. Learn more at https://www.bitdeer.com. ---- Abundant Mines is a fully-managed Bitcoin mining in the U.S. You own the miners. You keep 100% of the Bitcoin. Voted #1 mining company by peers. Get 1 month of free hosting: AbundantMines.com/Natalie ---- Natalie's Bitcoin Product Partners & Sponsors: Speed is my go-to Bitcoin Lightning wallet! Send, receive, or swap stablecoins and digital gold into Bitcoin in one app. Run a business? Speed powers Bitcoin payments for Steak 'n Shake, and it can do the same for you. Download at https://speed.app/natalie  and use code COINSTORIES10 for 5,000 free sats after your first transaction. Download Bitkey Today and use my promo code STORIES to get 10% off the new Bitkey. This episode has been sponsored by Bitkey: https://bitkey.world/STORIES Master Bitcoin self-custody and gain peace of mind with 1-on-1 training: https://www.thebitcoinway.com/natalie?utm_source=partner-natalie&utm_medium=podcast With BitcoinIRA, you can invest in bitcoin 24/7 inside a tax-advantaged IRA. Choose a Traditional IRA to defer taxes, or a Roth IRA for tax-free withdrawals later. Take control of your future with BitcoinIRA: https://www.bitcoinira.com/natalie  Kalshi is the largest prediction market in the world. Use code HODL and get $25 when you trade $25: http://kalshi.com/r/HODL   Natalie's Upcoming Events: The best time to plan for Bitcoin 2027 is right now. Early bird tickets are live — grab the lowest pricing available and use code HODL for 10% off: https://tickets.b.tc/event/bitcoin-2027?promoCodeTask=apply&promoCodeInput=HODL  Extra Services to Consider: One of the best decisions I made for both my heath and my bank account was joining CrowdHealth years ago. I never spend more than $200 on health coverage through my CrowdHealth plan and all my health events have been crowd-funded. Get started with a discounted plan at my link. : www.joincrowdhealth.com/natalie  ---- Disclaimer: The News Block and Coin Stories are for educational and entertainment purposes only and do not constitute financial, investment, legal, or tax advice. Natalie Brunell is not a financial advisor. Some content may include sponsorships or paid partnerships, which are disclosed. Always do your own research and consult a licensed professional before making financial decisions. Bitcoin and digital assets are volatile — never invest more than you can afford to lose.  

Does AI increase or reduce technical debt? Join Johna Johnson and John Burke as they discuss how to make strategy in environments in which AI fuels untrammeled growth in enterprise complexity–but also points the way to automated optimization (and concomitant technical debt reduction). Episode Links: Watch this episode on YouTube The AI Technical Debt Crisis:... Read more »

Yasir Arafat is the co-founder and CTO of Aalo Atomics, a company developing factory-manufactured modular nuclear power plants designed for AI data centers. Before founding Aalo, Yasir led the MARVEL microreactor program at Idaho National Laboratory. In this episode of Inevitable, Yasir explains how Aalo became one of four U.S. nuclear startups to achieve criticality by the July 4, 2026 deadline. He breaks down what criticality means, why the milestone matters, and how the team went from a small startup to sustaining a nuclear fission chain reaction in less than a year. The conversation explores why Yasir believes nuclear's biggest challenges are speed and economics rather than safety or reliability, and how Aalo is trying to address both through factory-based manufacturing. Yasir also shares how the company built its own reactor building in 36 days, tested its full-scale reactor systems, developed scalable fuel assembly manufacturing, and partnered with Idaho National Laboratory to learn how to operate a real reactor. Finally, Yasir outlines Aalo's path from its zero-power Critical Test Reactor to Aalo-X, a full-powered reactor designed to generate electricity and power a co-located AI data center, and ultimately to the company's commercial Aalo Pod. The discussion also covers DOE demonstration pathways, future NRC licensing, the resurgence of nuclear innovation, and why Yasir believes multiple reactor technologies and companies will be needed to scale nuclear energy. Note: Aalo Atomics is an MCJ portfolio company. Episode recorded on August 6, 2026 (Published on August 18, 2026). In this episode, we cover:  (0:00) An overview of Aalo Atomics (2:00) What criticality means in a nuclear reactor (3:38) Why the July 4 deadline was set and why it mattered (7:07) The final 24 hours before Aalo reached criticality (9:24) How accurately Aalo's reactor matched its physics models (11:43) From the MARVEL microreactor to founding Aalo Atomics (13:56) Why Aalo is focused on nuclear speed and economics (17:05) Why Aalo built a zero-power critical test reactor first (19:01) Building a nuclear reactor building in 36 days (19:21) What Aalo tested beyond the reactor itself (20:53) Building fuel assemblies for the next 100 reactors (23:43) Why organizational readiness matters as much as reactor technology (24:05) Running the CTR and Aalo-X projects in parallel (24:56) Excavating through unexpectedly difficult basalt rock (26:03) The progression from CTR to Aalo-X to the Aalo Pod (29:29) Partnering with turbine suppliers and Crusoe (31:27) The timeline for powering a co-located AI data center (32:09) How DOE authorization supports first-of-a-kind reactor demonstrations (34:01) Moving from DOE demonstrations toward NRC commercial licensing (42:03) Why Aalo is betting on the next generation of sodium-cooled reactors Enjoyed this episode? Please leave us a review! Share feedback or suggest future topics and guests at info@mcj.vc.Connect with MCJ:Cody Simms on LinkedInVisit mcj.vcSubscribe to the MCJ Newsletter*Editing and post-production work for this episode was provided by The Podcast Consultant

Does AI increase or reduce technical debt? Join Johna Johnson and John Burke as they discuss how to make strategy in environments in which AI fuels untrammeled growth in enterprise complexity–but also points the way to automated optimization (and concomitant technical debt reduction). Episode Links: Watch this episode on YouTube The AI Technical Debt Crisis:... Read more »

Today we are talking with Vignesh Baskaran, the CTO and co-founder of Hexo Labs, about teaching AI agents to improve themselves. Vignesh has been training neural networks since 2012, back when he was still called a data scientist. Then he became an ML engineer and now an AI engineer, though he says the underlying work has never really changed. It's to figure out how to make a system behave the way you intend it to. He built the litigation search engine that Google itself became a customer of, and now he's chasing something new, agents that rewrite and retrain other agents without a human in the loop. We dig into Sia, the meta-agent at the center of Hexo's research, and why improving an agent means touching both its harness and its actual model weights, not just one or the other. We talk about proxy evals for when you don't have much to ground truth. The Darwin-Gödel machine and why formal verification is too strict a bar for anything commercial. How Hexo's work echoes DeepMind's Alpha lineage from AlphaGo to AlphaEvolve, and the spectrum from clearly verifiable to totally subjective tasks? Why VAE evals are quietly wrecking agent quality across the industry, and a great story about an agent that discovered a customer's own eval file was silently corrupted, something buried in hundreds of thousands of traces that no human would have caught.

Michael Barnard welcomes Cornelis Plet, CTO of Grid Systems Integration at GE Vernova, about the technologies reshaping modern power systems and the practical realities of building an electrified future.  High-voltage direct current (HVDC) transmission, once a specialist solution for narrow use cases, is now becoming a standard building block of the global grid. Increasingly standardised designs are enabling large-scale transfer of renewable power over long distances, yet the industry is still grappling with how to align control systems and operational standards across different vendors and regions.  A central theme of the conversation is the rise of grid-forming inverters. As traditional synchronous generation retires and is replaced by wind, solar, and batteries, the grid is shifting from mechanical inertia to power electronics. While technical progress is rapid and new grid codes are emerging, true interoperability between systems remains a work in progress, with different implementations still complicating integration at scale.  The discussion also touches on geopolitics and market dynamics. Investment patterns are evolving, regulatory environments are uneven across regions, and supply chains are adjusting after a period of rapid expansion. Yet across all of this, one constraint stands out more than any other: people. The shortage of experienced power engineers, particularly in system design, protection, and control, is becoming the defining bottleneck of the transition.  Ultimately, the episode is not only about HVDC or inverters, but about the broader system that surrounds them—standards, institutions, skills, and the accumulated expertise required to keep a highly complex, rapidly changing grid stable. It is a reminder that the energy transition is as much a human and organisational challenge as it is a technological one.  

Virtual cell models promise faster, cheaper early-stage drug discovery. However, the industry still lacks a shared way to judge which of these models can actually be trusted on a given problem.   In this episode, Kristóf Szalay, CTO and Co-Founder of Turbine, and Gerold Csendes, Scientist at Turbine, set out what virtual cell models can and can't do today, in conversation with host Marilie Fouché. They cover why benchmarking remains fragmented across the field, how pharma teams build confidence in a model before trusting it with real R&D decisions, and how compressing the feedback loop between experiments can cut months out of the discovery process.   This episode is sponsored by Turbine.   Emerj works with a select group of AI vendors to reach Fortune 500 decision makers through research, media, and direct access. If you want to be considered, download our media kit at emerj.com/AD1

Lightning Labs built Wavelength to deliver self-custodial Lightning payments without forcing users to run nodes, manage channels, or handle liquidity.Olaoluwa Osuntokun, CTO and co-founder of Lightning Labs, and Michael Levin, VP of Product, join me to detail the design choices behind their Ark implementation.They explain why Ark was selected, how hop hints let every payment use ordinary Lightning invoices, and why the four-endpoint SDK targets AI agents and vibe coders. The conversation covers sub-dust vouchers, unilateral exits, offline payment delivery, and one-basis-point alpha pricing.Wavelength shows that self-custodial Lightning can match the integration ease of custodial services while preserving Bitcoin sovereignty.Timestamps01:28 — Why Wavelength: Lightning Without Node Pain03:00 — Why Ark? 05:28 — No New Addresses: Just Lightning Invoices08:40 — Targeting Vibe Coders & AI Agents13:06 — Lightning Beats Credit for LLM APIs17:51 — Receive Sub-1k Sat Vouchers Seamlessly19:32 — Normal User Spins Up Ark Wallet Fast23:02 — Build Wallets with Just 4 Endpoints24:46 — Telegram Self-Custodial Wallets Already Live26:21 — Offline Payments Still Arrive Automatically29:17 — Drop-In SDK for iOS and Android31:26 — Can Servers Steal Your Funds?33:36 — Wavelength Alpha: Just 1 Bip Fees37:57 — AI Attacks Targeting Bitcoin Services?44:05 — Bug Bounties Shift to Token Spending48:36 — Self-Custody as Easy as CustodialLinks: https://x.com/roasbeehttps://x.com/MichaelLevinWavelength Announcement: https://x.com/lightning/status/2079620936567779707Stephan Livera links:Follow me on X: @stephanliveraSubscribe to the podcastSubscribe to Substack

This week on the Friday Deploy, Ben and Andrew explore Uber's strategy of "rearward deploying" engineers to spread agentic AI workflows into departments like legal and marketing. They also dive into Anthropic making Claude Code's Auto Mode the default, Meta's new on-device Muse Glimmer model, and Tim O'Reilly's case for an open source AI ecosystem. Finally, they break down context engineering for the SDLC and examine new research showing why generalized agent skills outperform personalized ones. Register: Dev Interrupted Presents: The Software Factory RoundtableFollow the show:Subscribe to our Substack Follow us on LinkedInSubscribe to our YouTube ChannelFollow the hosts:Follow AndrewFollow BenFollow DanFollow today's stories:After starting the tokenmaxxing panic, Uber's CTO is back with a very different AI storyAuto mode is now the default in Claude Code for Pro, Max, and Team plansIntroducing Muse Glimmer: An Open Agentic Model That Runs on Your DeviceWhy Open Source Matters for AIYour SDLC is your context engineeringDo personalized skills help coding agents? An empirical study of developer interaction historiesOFFERSStart Free Trial: Get started with LinearB's AI productivity platform for free.Book a Demo: Learn how you can ship faster, improve DevEx, and lead with confidence in the AI era.LEARN ABOUT LINEARBAI Code Reviews: Automate reviews to catch bugs, security risks, and performance issues before they hit production.AI & Productivity Insights: Go beyond DORA with AI-powered recommendations and dashboards to measure and improve performance.AI-Powered Workflow Automations: Use AI-generated PR descriptions, smart routing, and other automations to reduce developer toil.MCP Server: Interact with your engineering data using natural language to build custom reports and get answers on the fly.

Are you a senior tech leader, architect, or enterprise sales executive sitting on high-value technical acumen, wondering how to channel your skills into an independent venture without sacrificing your corporate career?   In this transparent guest conversation, host Billy Keels sits down with Diwas Timsina, a Customer Success Architect at a market leading enterprise software and services company, founder and CTO of Sarva, and former TEDx speaker. Born in a refugee camp in eastern Nepal, Diwas details his journey of arriving in the U.S. at age 14, changing high schools three times, and ultimately earning his MBA while navigating corporate consulting and enterprise software. Discover how Diwas uses the methodology of "building quietly" to prove concepts to himself before sharing them publicly, how he translates C-suite enterprise client conversations into grassroots multilingual AI tools for small vendors, and how to maintain total perspective during career challenges by remembering your ultimate starting point.  

Jarrette Schule is the Founder and CTO of TenFore Golf, a cloud-based, all-in-one management platform built for golf courses and recreational facilities. He founded the company in 2015 after recognizing the limitations of legacy golf management systems. As TenFore's lead architect, Jarrette directs its technology vision and product development, creating mobile-first tools that help single- and multi-course facilities streamline operations, increase revenue, and improve the golfer experience.  In this episode… Golf courses often juggle outdated systems for tee times, payments, food service, reporting, and customer engagement. What does it take to replace those fragmented systems with one platform designed around how modern facilities operate? Jarrette Schule, a lifelong software developer with decades of experience building technology, explains that successful golf management software must address the entire operation rather than solve one isolated problem. He highlights the importance of listening to course operators, validating recurring needs, and designing tools around real-world workflows. This customer-led approach helped transform an on-course beverage-ordering concept into a connected platform spanning tee sheets, point-of-sale, booking, payments, food and beverage, reporting, and self-service kiosks. By bringing an outside technology perspective to golf, Jarrette identified opportunities that legacy providers had overlooked. He also uses a "rule of three" to prioritize features that deliver value across multiple customers instead of reacting to every individual request. In this episode of the Inspired Insider Podcast, Dr. Jeremy Weisz speaks with Jarrette Schule, Founder and CTO of TenFore Golf, to discuss building an all-in-one platform for modern golf operations. They explore the product's evolution, customer-led development, and growth through multi-course operators. Jarrette also shares lessons from SaaS pricing, payment integrations, and moving from CEO to CTO.

Technology has made it easier to build a product. It has not made it easier to know what deserves to be built.Brett sits down with Josh Johnson, CTO of Card Ladder, at The National to discuss how Card Ladder grew from a problem its team faced as collectors.Josh shares why he spent three months preparing the app for The National, how Card Ladder earned trust through seven years of work, and why the team turns down revenue opportunities that pull the product away from collectors.They also discuss AI, product development, team health, brand building, and what people entering the sports card industry need to understand before trying to serve it.This is a conversation about staying close to collectors and building something that lasts.Sign up for Hobby Jobs and The Weekly Rip for freeGet exclusive content, promote your cards, and connect with other collectors who listen to the pod today by joining the Patreon: Join Stacking Slabs Podcast PatreonFollow Stacking Slabs: | Twitter | Instagram | Facebook | Tiktok ★ Support this podcast on Patreon ★

Michael Bervell is co-founder and CEO of TestParty, an AI-powered digital accessibility platform that automatically scans and fixes source code so websites meet WCAG and ADA standards, without slowing down engineering teams. Before TestParty, Michael worked in accessibility and product inclusion at Google and the United Nations, was a software engineer at Twitter, and held product and venture roles at Microsoft and M12. He holds a BA from Harvard and an MBA from Harvard Business School, is the author of Unlocking Unicorns, and was named to the Forbes Accessibility 100. TestParty raised a $4 million seed round led by Harlem Capital and the Urban Innovation Fund.Jason Tan is co-founder and CTO of TestParty and the technical architect behind its automated remediation engine. He came to the problem firsthand: while at Twitch, the company was sued for digital accessibility violations, and in researching fixes he discovered that accessibility lawsuits had become an industry norm. He co-founded TestParty in 2023 to give engineers a "spellcheck for accessible code." In This Conversation We Discuss:[00:00] Introduction[02:37] Why ADA lawsuits target ecommerce sites[04:36] Settling once doesn't protect you[07:01] ADA's outdated, vague legal language[11:16] Why "band-aid" solutions won't work[15:08] Callouts[16:44] How the brand fixes sites at the source[18:27] A former company's accessibility lawsuit story[21:31] Fixing sites fast after a demand letter[23:01] Defense packets against troll claims[24:24] Free tools to test site accessibilityResources:Subscribe to Honest Ecommerce on YoutubeAutomated WCAG Compliance testparty.ai/ Follow Jason Tan linkedin.com/in/jason-tan-75ab38191 Follow Michael Bervell linkedin.com/in/michaelbervell If you're enjoying the show, we'd love it if you left Honest Ecommerce a review on Apple Podcasts. It makes a huge impact on the success of the podcast, and we love reading every one of your reviews!

What do AI adoption, cyber resilience, and the great VM reset have in common? They're all trends which are colliding to reshape the world of enterprise technology. As organisations prepare for a future powered by intelligent systems, infrastructure, security and virtualisation are becoming increasingly connected strategic priorities. This week, Technology Now explores how these changes are reshaping enterprise technology, as Patrick Osborne, SVP Hybrid Cloud and Office of the CTO, joins the show to discuss:The economic and technological impacts of the great VM resetWhy hybrid systems are essential to succeed in the world of AIThe role of sovereignty and governance in AI adoptionWhat the agentic enterprise could mean for infrastructure and operations 

Sponsored by Blocks: Save at least 20% on your AWS costs with AI-powered optimization and enterprise discounts. Get your free Cloud Check at https://blocks.cloud/alphalist?utm_source=alphalist&utm_medium=podcast&utm_campaign=blocks-podcast-2026 Dana Lawson's path into tech started with backup tapes, not a keyboard-in-the-womb origin story. She joined the US Army in the late '90s, automated her way out of manual password resets, and went on to become VP of Product Engineering at GitHub before taking the CTO seat at Netlify. She joins Tobi to make the case that "writing code is no longer the job", an argument from her own New Stack article that lit up Hacker News, and one she doesn't back away from here. The conversation explores why trust in AI agents may eventually become automatic, the same way our trust in cars we can't repair ourselves already has. Dana explains why Netlify is designing for "agent experience" alongside developer experience, and why the engineer's role is shifting from writing every line of code to defining architecture, guardrails, reliability, and safe user experiences. CTOs will walk away with a sharper way to think about where human judgment still matters versus where it's already been commoditized, including the tension between speed and control, whether developers risk becoming the bottleneck, and why the real constraint may be moving from "can we build it?" to "does anyone actually want it?" What's covered: - Dana's path from the US Army to VP of Engineering at GitHub to CTO of Netlify - Why she argues "writing code is no longer the job" and the Hacker News backlash - The self-driving car analogy for trusting AI agents - What "agent experience" means and why Netlify designed for it - Craftsmanship, control, and the shift from writing code to defining guardrails - Whether developers risk becoming the bottleneck in the agentic era - Why the constraint is moving from "can we build it" to "does anyone want it"

Send us Fan MailWhat does it take to evolve from a hands-on technologist into the CEO of a global cybersecurity company?In this episode of Joey Pinz Conversations, Joey sits down with Joe Levy, CEO of Sophos, to discuss leadership, technology, entrepreneurship, cybersecurity, and personal growth. Joe shares his fascinating journey from writing software and running bulletin board systems as a teenager in Queens, New York, to becoming CTO and eventually CEO of one of the world's leading cybersecurity companies.The conversation explores the lessons learned from building technology businesses, transitioning into executive leadership, working with MSPs, and why the best products do not always win in the marketplace. Joe also shares insights on cybersecurity's leadership gap, the impact of AI, parenting in the digital age, and the importance of self-regulation in both business and life.From walking 12 miles a day on a treadmill desk to leading thousands of cybersecurity professionals worldwide, Joe offers practical wisdom on curiosity, learning, resilience, and long-term success.

Think about the last thing you almost bought and did not. You picked it up, you looked at it, you put it back down. You had a reason for choosing one item over its competitors, and you know exactly what it was. Did anybody ever ask you why you didn't choose the loser? Of course not. And somebody did the same thing to you this week. Something you made, or wrote, or suggested. An idea you put into a meeting that got a polite nod and then went nowhere. They considered it, decided against it, and you never found out the real reason. Almost everything that comes back to you comes from the people who said yes. Inside a business, the machinery makes that official. Satisfaction surveys go to people who have bought. Reviews come from people who have bought. The customer list is a list of people who have bought. The one who put it back down is invisible to all of it, and that person is holding the answer. So, where do you point a question to reach somebody who is not there? Last week, we took a question apart and rebuilt it. But a well-made question aimed at the wrong thing comes back empty. Where you point a question is the other half of the skill. Forty-two cards of Killer Questions A killer question is one that has been tested and proven to spark ideas beyond the obvious. The name comes from the old phrase "killer app," where "killer" meant standout, not lethal. I built this collection of questions the slow way. I designed structured tests into my innovation workshops, which I was running: specific questions put to specific groups, and a record of what each produced. The rule for keeping a question was that it had to trigger something in that room. Did somebody walk out seeing their customer, their product, or the way they work differently than when they walked in? If nothing moved, the question was cut. If there was a good idea underneath one and I had simply worded it badly, I rewrote it and ran it again in another workshop. There were hundreds of questions, and most did not survive. Forty-two did. When I sorted the survivors, they fell into three groups. Not by subject. By where they aim your thinking.  Three places to aim Every question in the deck points to one of three things. Who, what, and how. WHO is the person or organization who will benefit from what you make. Usually, your customer, though the gap between "usually" and "always" is where a lot of new business hides. WHAT is the product, the service, the solution that creates the value for the WHO. HOW is the way your organization builds, delivers, and supports the WHAT for the WHO. Three places an idea can come from, and the questions exist to send you into each one on purpose rather than by accident. The cards all say "product." Read that as whatever you make for somebody else. A service counts. So does a proposal you hand to your boss. Thirteen of my cards aim at WHO. Thirteen at WHAT. Sixteen at HOW. That split was never a plan. It is where the questions that kept surviving pointed, and eventually, I stopped arguing with it. WHO What are your unshakable beliefs about what your customers want? The phone companies believed their customers wanted reliability above all else, and they were right. For a century, they built toward 99.999 percent uptime. A dial tone that worked in a storm, in a power failure, always. Then somebody turned that belief over and looked at it with no assumptions about what the customer wanted. Where were there people who would give up call quality for something else? That is the question that led to voice over IP, a phone call carried over the internet. In the early days, it sounded terrible. Calls dropped. By the standard the old industry had spent a century perfecting, VoIP was not a serious product. But underneath it sat an idea nobody in that industry had allowed themselves to consider: that many people would trade call quality for price and mobility, and would do so happily. They did. That market opportunity existed before anyone built it, waiting for someone willing to challenge the old standard on its head.  WHAT What is surprisingly inconvenient about my product? It does not ask whether the product is good. Your team will defend that all day, and they will be partly right, which will only make the conversation worse. Surprisingly inconvenient means some part of using your product that nobody inside your company has ever seen a real person struggle with. The fifteen minutes with the instructions. The step everyone on your team skips automatically because they built the thing. On the back of that card sits the shortest useful question I own: "Do you use your own product yourself?" Hold on to this one. In a few minutes, it turns up at a Best Buy, and the strange part is that I wasn't aiming at it when I found it. HOW What do people not like about the buying experience for my product? For the whole time I was CTO at HP, I spent nearly every Saturday in a Best Buy. While traveling, I found a local electronics store in whatever country I was in. I was not shopping. I was standing in the aisle watching strangers choose, because this question has no other answer. You cannot survey somebody who did not buy.  My family called it my "digital stalking". My kids would have done almost anything else rather than be seen with me in a Best Buy on a Saturday. When somebody picked up a competitor's product and headed for the checkout, I would walk over, introduce myself, and ask what made them choose that one. I did it long enough that the sales staff around Silicon Valley knew me, and would change how they talked to a customer if they saw me standing there. Stay somewhere long enough, and you stop being an observer. You influence what you are measuring. Then came the Saturday that changed a product. A customer set down an HP laptop and bought a competitor's. I asked him why. He told me he could not see the keys. This was during the stretch when every laptop was going aluminum, and somebody in our laptop group had given ours a chrome-looking keyboard. High gloss. On a store shelf, it looked expensive, which is exactly what it was designed to do. It also meant that anyone whose eyesight had started to go could not read the letters on it. Sales on that product had been running under plan, and nothing in the data said why. We changed the keyboard back to matte black with high contrast white lettering. Sales went up on that one change. No survey would have revealed the issue. By the time he told me, he was already somebody else's customer. Notice what that question actually turned up. I went into the store carrying a HOW question about the buying experience. What came back was a WHAT answer, something surprisingly. Inconvenient about the product itself. You choose where to aim. You do not choose where the answer comes from. Testing for Great Questions How do you find and test great questions? Ask the question, then watch what happens in the next four seconds. If the room goes quiet, and then somebody says, "Hang on," you are holding a good one. That pause is the sound of a person arriving somewhere they have not been. You just unleashed a great question. If someone answers immediately and confidently, the question isn't that great. A fast answer means you aimed where the team has already been, and they are reciting. I threw away hundreds that way and got down to the questions that caused impact. Practice Exercise  Take a decision you are facing this month and give it ninety minutes. Start with whichever of the three you are least comfortable with, which for most people is HOW. Take a question from it at random. Do not hunt for the one you like, because the one you like is the one you have already answered. Set a timer for thirty minutes and write down every idea that question produces. No judging, no editing, just quantity. Then do the same thing with a question aimed at your customer, and again with one aimed at the product. When you have worked through all three, read back over everything and pick the best three ideas to start on. That is how you run it on your own. If you would rather do it with a team, there is a second version designed for groups of 4 to 6 people. Both are written out step by step on killerquestions.com, so you are not working from memory. You can buy the deck at innovation.tools, either as printed cards or as a digital download for your phone, tablet, or PC.  Send me the question that worked best for you. I am also still on the search for new questions for volume 2 of the card deck. Send your suggestions, and they might just be included. That closes out this three-part series on questions. If you came in at the end, part one is about why you cannot stop yourself from answering a question, and part two is about how a single word inside a question steers the answer you get back. The next episode is about abductive thinking. Deduction hands you a conclusion you can prove. Induction hands you a pattern you can bet on. Abduction is what you reach for when you have neither and still have to decide, which is most of the time. It is how a doctor arrives at a diagnosis, and it is how most real innovation actually happens. Subscribe wherever you watch or listen, and you will get that one when it lands.

What if the real risk in your AI adoption plan isn't that the pilot fails — it's that it succeeds, and you still can't get it into production?Agility isn't how fast you can launch a pilot. It's whether the organization can absorb what works and still behave like one company while it does.Today, we're going to talk about moving enterprise AI from theory to practice in customer experience. Specifically, we'll cover:- What separates an AI pilot that scales from one that quietly stalls.- How to govern AI agents proportionately — enough accountability to be defensible, not so much that nothing ships.- How to tell a program that's creating business value from one that's simply handling volume.To help me discuss this topic, I'd like to welcome, Kevin Lee, CTO at NiCE.About Kevin LeeKevin Lee serves as Chief Technology Officer and Key Pursuits Leader at NiCE, where he leads the company's technology vision and its most strategic customer engagements by aligning platform capabilities, AI strategy, and architectural vision to deliver differentiated outcomes.Kevin joined NiCE in 2021 and has held multiple leadership roles across the company's digital and go-to-market organizations. He founded and scaled the Customer Service Automation team, transforming it into a cornerstone of NiCE's growth strategy. He has played a pivotal role in many of NiCE's most competitive and highimpact pursuits, shaping both technical and commercial strategy across global opportunities. Prior to his current role, Kevin served as Global Head of Digital Sales & Strategy, where he led the growth of NiCE's digital portfolio and helped customers transition into the self-service era. With more than 15 years of experience in cloud and software sales, Kevin brings a comprehensive approach to account strategy, technical storytelling, and executive engagement. Kevin Lee on LinkedIn: https://www.linkedin.com/in/thekevinlee/---------- Resources ----------Coca-Cola FEMSA, NiCE: https://www.nice.comThe Agile Brand podcast is brought to you by TEKsystems. Learn more here: https://aglbrnd.co/r/2868abd8085a9703We're proud to be a media partner for #MAICON26 - Oct. 13-15! Learn how AI can power your marketing and business and help you grow smarter. Use code AGILE150 to save! https://aglbrnd.co/r/7fe458ced0f04658Reach your customers with Reddit. Spend $500 in ad spend, get $500 back in ad credit! Learn more: https://advertalize.com/r/491818c79fb1873fChaser is the only Slack-native project management platform that helps teams turn messages into tracked tasks, automate follow-ups, and maintain team-wide visibility, without adopting another tool. Now integrated with Claude and other GenAI tools. Learn more at trychaser.com and use code AGILEBRAND for a 3-month free trial (normal trial is 14 days).The most influential minds in software, AI, and engineering leadership will be at WeAreDevelopers World Congress North America, September 23-25 in San Jose. Learn more: https://aglbrnd.co/r/60a7299222a7bcf1Start building your own apps with Replit and get $20 off. Learn more: https://aglbrnd.co/r/93531742a7625a20Enjoyed the show? Tell us more at and give us a rating so others can find the show at: https://aglbrnd.co/r/faaed112fc9887f3Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregkihlstromDon't miss a thing: get the latest episodes, sign up for our newsletter and more: https://aglbrnd.co/r/35ded3ccfb6716baCheck out The Agile Brand Guide website with articles, insights, and Martechipedia, the wiki for marketing technology: https://www.agilebrandguide.comThe Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. Hosted on Acast. See acast.com/privacy for more information.

Follow me @samirkaji for my thoughts on the venture market, with a focus on the continued evolution of the VC landscape.Welcome back to another episode of Venture Unlocked, the podcast that takes you behind the scenes of the business of venture capital.In this episode, I sit down with Aditya Agarwal of South Park Commons (SPC) to trace his journey from being one of the earliest employees at Facebook, becoming CTO at Dropbox, and then the inspiration of creating South Park Commons from his living room. The firm just announced a $575MM IV, it's largest fund to date. We discuss his decision-making at key career forks including his learnings working with Mark Zuckerberg, the power of surrounding yourself with exceptional people, and the five founder traits SPC relentlessly optimizes for. We also covered what it means to invest at the -1 to zero stage, and his view on the current state of venture capital.Thanks for listening to another episode of Venture Unlocked. I hope you enjoyed this conversation with Aditya. If you'd like to get Venture Unlocked content straight to your inbox, go to ventureunlocked.substack.com and sign up, or head over to Apple Podcasts or Spotify and subscribe. Thanks again for listening.Aditya Agarwal is a General Partner at South Park Commons and a longtime technology leader and entrepreneur. He previously served as CTO and VP of Engineering at Dropbox, where he scaled the engineering organization from 25 to more than 1,000 people. Before Dropbox, Aditya was one of Facebook's earliest engineers, helping build foundational products including News Feed, Search, and Messenger before becoming the company's first Director of Product Engineering. Today, he invests in and advises early-stage startups, drawing on decades of experience building some of Silicon Valley's most influential technology companies.Topics in this conversation include:* Choosing Oracle Over Bridgewater (2:31)* First Impressions of Mark Zuckerberg and Early Facebook (6:02)* Lessons From Oracle on Talent Density and Bureaucracy (9:38)* Five Founder Traits SPC Looks For (13:14)* Growing the SPC Community and Early Angel Checks (22:33)* AI, ChatGPT, and Rethinking Fund Size (35:15)* Investing Ahead of the Curve in AI and Robotics (39:11)* Aiming for 5x Net Per Fund (41:04)* AI Compared to Railroads and Heavy Capex (46:07)* AI's High Usefulness Floor and Mass Adoption (49:10)* Concerns Around Hyperscaler Capex and Hiccups (52:01)* Closing Reflections and Takeaways (54:38)Follow me @SamirKaji and give me your insights and questions with the hashtag #ventureunlocked. If you'd like to be considered as a guest or have someone you'd like to hear from (GP or LP), drop me a direct message on X. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit ventureunlocked.substack.com

If AI can produce the code, what becomes more valuable for engineers?John Kuhn, CTO and cofounder of Integral, joins The Tech Trek to discuss how agentic development is changing engineering work, product ownership, experimentation, and hiring. Integral helps companies de identify and anonymize data for model training, including unstructured data.John argues that the value of an engineer is shifting away from simply writing code. As AI handles more implementation work, engineers need stronger product judgment, better systems thinking, and the ability to make decisions when requirements are incomplete. That means asking better questions, understanding customer problems more directly, and taking greater ownership of the outcome.The conversation also looks at what happens when software becomes cheaper to produce. Teams can prototype and experiment faster, but lower development costs do not eliminate the cost of building something customers do not want. Good product discovery still matters, especially when engineers are expected to operate with more autonomy.What You'll Take Away• Why engineers increasingly need to think like product managers• How agentic tools are changing the economics of prototyping and product experimentation• Why good product discovery requires questions that seek information instead of confirming an existing idea• Why engineering interviews may need to focus more on assumptions, constraints, systems thinking, and decision quality than manual coding speedA Moment Worth Pulling Out“Engineers are not meant to write code anymore. They're meant to solve problems.”John also raises an interesting idea for the future of technical hiring: instead of giving candidates only a time limit, give them a fixed AI compute budget and evaluate how efficiently they use it to reach a solution.Follow The Tech Trek for more conversations about AI, engineering, product, data, and technical leadership.

More than 50 cats have been rescued from an abandoned boat in Tacoma as police try to figure out who owns the vessel, A META employee asked for more time off and the CTO of the compnay called the question 'very dumb', Headline of the Week contender #2: Council apologizes aftyer 'Dead End' sign was placed next to cemetery

Will sat down with Minal and Brijraj from Spry live at APTA CSM to talk about the part of the physical therapy industry most clinicians never see: the technology quietly reshaping how clinics run.Brijraj was the CTO of Ola, the ride-share company often called the Uber of India, at its $6 billion peak. He left that world to build Spry because the same problem kept showing up: people need to move, and mobility gives them purpose. Minal treated patients for 15 years in outpatient ortho before she and her husband moved to Portugal. She wasn't looking for a new job. Spry found her on LinkedIn, and three years later she's the clinical voice inside a tech company, pushing back when the product team drifts too far from what actually happens on a clinic floor.The conversation gets into the real tension of building healthcare technology: a founder who thinks in outcomes and a clinician who thinks in patients, and what happens when those two things pull in different directions. They talk through Spry's insurance verification engine (95% accurate, down to the NPI level), the AI agent that now handles prior authorization and removes 80% of the manual work behind it, and why EMRs were never supposed to become billing tools in the first place.In this episode:Why Brijraj left a $6 billion ride-share company to build an EMR for physical therapistsThe difference between "work" and "toil," and why toil is what's driving burnout in PTHow Spry's insurance verification hits 95% accuracy at the NPI levelInside the AI agent that cuts prior authorization work by 80%Why most EMRs turned into billing tools when they were built for interoperabilityWhat's next for Spry: multi-specialty workflows, waitlist agents, and clinical decision supportMinal and Brijraj also get into what's next: a shared workflow for multi-specialty clinics where PT, OT, speech, and MD care actually talk to each other, an agent for canceling and waitlist management, and a clinical decision support tool built specifically for physical therapy.Follow the Will Power Podcast for more conversations with the people building the future of physical therapy. Connect with Spry: www.sprypt.com Send us Fan MailRockstars specialize in helping support or replace all non-clinical roles.Learn how a Rockstar can help scale your physical therapy practice.Subscribe here to our completely free Stress-Free PT Newsletter for your weekly dose of joy. 

In this podcast episode, Trent and Matt interview Cody Rich, founder of Bridger Watch, about why he built a hunting-focused smartwatch and how it evolved from wanting usable offline maps and hunting features on a watch. Rich shares his background from Perrydale, Oregon, moving to Montana, early work in Marine Corps training using Hollywood-style special effects, then entrepreneurship through Powder River Cartridge and learning marketing/SEO before starting The Rich Outdoors podcast and building Backcountry Fuel Box. Seeking a larger legacy business, he pursued a Garmin-adjacent niche, raised money, and assembled teams including former Fossil talent and connections to Google leadership and a CTO with Garmin dog-collar experience, ultimately building custom hardware and a new operating system. He describes key features: offline topo maps with panning/zooming, onX waypoint/track/markup syncing, integrated ballistics via Sierra True Data, redshift mode, frequent over-the-air updates, and ongoing battery-life improvements, with purchasing available at bridgerwatch.com, GuideFitter, GovX, and via HSA through TrueMed.

Welcome to this episode of The New Warehouse Podcast, recorded at Traba's Manhattan office. Kevin is joined by Akshay Buddiga, co-founder and CTO of Traba, and engineering director Jeff Chen. Traba began by using technology and operational support to improve industrial staffing. Its next evolution is Neo, an AI operating system built for the industrial supply chain. Buddiga and Chen explain how AI agents differ from chatbots, connect fragmented warehouse systems, and reshape the relationship between people, automation, and warehouse intelligence.Learn more about Pallite here.Learn more about Big Joe's AP44 here. Follow us on LinkedIn and YouTube.Support the show

Philosopher Stefan Molyneux shows how to get things done by facing conflict head-on and telling the truth instead of avoiding it. He talks with a sister about her brother's separation from a controlling wife and with a software developer who wants to lead as a CTO but keeps putting approval ahead of his own needs and mission.JOIN ME IN NASHVILLE SEPTEMBER 12! https://wordwardebate.com/Use code STEFAN for 10% off!GET FREEDOMAIN MERCH! https://shop.freedomain.com/SUBSCRIBE TO ME ON X! https://x.com/StefanMolyneuxFollow me on Youtube! https://www.youtube.com/@freedomain1GET MY NEW BOOK 'PEACEFUL PARENTING', THE INTERACTIVE PEACEFUL PARENTING AI, AND THE FULL AUDIOBOOK!https://peacefulparenting.com/Join the PREMIUM philosophy community on the web for free!Subscribers get 12 HOURS on the "Truth About the French Revolution," multiple interactive multi-lingual philosophy AIs trained on thousands of hours of my material - as well as AIs for Real-Time Relationships, Bitcoin, Peaceful Parenting, and Call-In Shows!You also receive private livestreams, HUNDREDS of exclusive premium shows, early release podcasts, the 22 Part History of Philosophers series and much more!See you soon!https://freedomain.locals.com/support/promo/FREEDOMAIN2026

In this episode, host Bidemi Ologunde speaks with Jacqueline De Lora, PhD, the CEO/CTO and cofounder of SURFACtoBioTech, a Max Planck spin-off developing surfactant and droplet-based technologies for more efficient, sustainable and data-rich biotechnology experiments. How can microscopic droplets function as individual test tubes? What separates useful AI-enabled laboratory automation from hype? And what does it take to transform frontier research into technology that scientists can reliably adopt? Jacqueline discusses her transition from biomedical researcher to founder, the often-overlooked role of surfactants, and the scientific and commercial challenges of building practical tools for real laboratory workflows.