Built This Week

This week we sat down with Jennifer Dulski, CEO and founder of Rising Team, to demo the AI leadership platform that acts as a personal trainer for your effectiveness at work. Jen spent 10 years at Yahoo, then Google, then Facebook, ran Change.org for five years, and sold her first AI company to Google in 2009. That company now powers the review insights inside Google Maps. She also teaches at Stanford GSB.Rising Team's AI coach RT does not give generic leadership advice. It knows your team. It knows that Tom likes direct feedback and Debbie needs encouragement first. And it helps you practice the conversation before you have it.We also got into why Apple Intelligence took too long, why AI memory still feels creepy to some people, and why the best AI features are the ones you never notice.We cover:What Rising Team is and how the AI coach RT worksWhy 70 percent of AI transformations fail because of people not technologyHow RT learns your team individually and personalizes every conversationWhy every executive gets a coach and every frontline manager gets nothingWhy the engagement survey is dying and what is replacing it in real timeThe privacy guardrails built into RT and EU AI Act complianceJen's first AI company in 2009 — DealMap, sold to Google, now inside Google MapsWhy Apple Intelligence took so long and whether it matters anymoreThe AI memory debate — helpful or creepyWhy the best AI features are the ones you never have to turn onIf you are building with AI, managing a team, or want to understand where workplace AI is heading, this episode is for you.Find Jen and Rising Team:Website: risingteam.comLinkedIn: linkedin.com/in/jdulskiNew episodes every Friday at BuiltThisWeek.comTIMESTAMPS[00:00] Intro[01:11] Meet Jen — CEO and founder of Rising Team[01:44] From high school teacher to Yahoo, Google, Facebook, and Stanford GSB[02:27] What Rising Team is at the highest level[02:47] Why coaching never scaled past the executive level[03:40] How Rising Team started in 2020[04:03] DealMap — her first AI company, sold to Google, now inside Google Maps[05:18] How Rising Team evolved from team building software to AI coach[05:55] How RT knows your team individually[06:31] Live demo — RT in action[07:00] Why 70 percent of AI transformations fail because of people[07:24] The science of high performing teams has not changed[08:12] What a session with RT actually looks like[10:00] Real-time anonymized insights for executives[14:21] Why the engagement survey is dying[14:48] Real insights from enterprise customers[15:36] Privacy guardrails and EU AI Act compliance[16:43] News — Apple Intelligence, Siri, and why it took too long[18:28] The AI memory debate[20:06] The best AI features are the ones you never notice[21:00] Where to find Jen and Rising Team[21:42] Wrap up#AI #Leadership #RisingTeam #FutureOfWork #BuildWithAI #BuiltThisWeek #TeamManagement #AICoach #Apple #HR

This week we sat down with David Petrou, CEO of Continua, to demo Wheely — an agent development operating system built for developers running multiple AI coding agents who are hitting the wall of mental overhead. David spent 18 years at Google, was on the founding teams of Google Glass and Google Goggles, and left when ChatGPT launched. We also covered the foldable iPhone, Android vs Apple for AI agents, Fable 5.1, Anthropic vs OpenAI on developer experience, and whether new programming languages designed for agents are coming.We cover:What Wheely is and why David calls it an agent development operating system18 years at Google, Google Glass, Google Goggles, and why he left to start a companyThe pivot from social AI to building the OS layer for multi-agent codingWhy token costs dropping does not solve the human attention problemHow Wheely decomposes problems, allocates agents, and knows when to interrupt youWhy Git and GitHub were designed for humans and need to be rethought for agentsHow agent coding can modernize legacy code and rebuild bloated React frontendsWho Wheely is actually built for and why the middle space is the opportunityWhy new programming languages designed specifically for agents could unlock major efficiency gainsApple vs Android for AI — best hardware vs best OS for agent use casesHow Android can disintermediate apps by running them simultaneously off screenFable 5.1, Gemini 3.8 Flash, and the honest developer take on Anthropic vs OpenAIThe coevolution of models, harnesses, and programming languagesWhether the foldable iPhone matters if agent coding eliminates the need for extra screen real estateIf you are building with AI agents, working in dev tools, or want to understand where the agent coding stack is heading, this episode is for you.Find David and Wheely:Website: wheelie.devTwitter: x.com/dpetrouNew episodes every Friday at BuiltThisWeek.comTIMESTAMPS[00:00] Intro[01:07] Meet David — CEO of Continua and creator of Wheely[01:56] Google Glass, Google Goggles, 18 years at Google[02:40] Why he left Big Tech when ChatGPT launched[05:18] The previous product — social AI for group chats[06:36] When coding agents changed everything[08:03] How building for agents internally became the real opportunity[08:56] Who Wheely is built for[09:46] What happens when you run 4 agents at once[10:17] Human attention is the scarcest resource in agent coding[11:16] How Wheely works — decompose, allocate, optimize, interrupt only when needed[13:05] The space between Claude Code and Lovable[14:05] Modernizing legacy code and greenfield agent projects[15:18] Why React is bloated and agents can rebuild frontends better[16:11] News — Apple foldable iPhone coming Q3[17:29] Apple unified memory vs Android open OS for AI agents[18:27] Android disintermediating apps with off-screen agent execution[20:24] Will the foldable iPhone matter if agents take over development[20:48] Fable 5.1 launch — honest developer take[22:10] Anthropic vs OpenAI on developer experience and harness access[23:17] New programming languages designed for agents[25:19] The coevolution of models, harnesses, and programming languages[25:40] Where to find David and Wheely[25:55] Wrap up#AI #AIAgents #Wheely #DevTools #GoogleGlass #BuildWithAI #BuiltThisWeek #Anthropic #Fable #Apple #iPhone

This week we sat down with Hardik Kabaria, co-founder and CEO of Vinci, to demo the AI platform making physics simulation accessible to any engineer building hardware. A chip tape-out used to cost millions of dollars and take months. Thermal analysis that should take seconds was waiting days for a specialist with a PhD. Vinci is compressing all of that into minutes — and making it accessible to anyone on the design team, not just the simulation expert.We also got into why AI image and video generation still has not produced a Netflix movie, what has to change before it does, and how AI getting into hardware design raises the stakes around IP and watermarking in ways nobody is talking about yet.We cover:What Vinci does — making physics simulation accessible to anyone building hardwareWhy a chip tape-out costs millions and takes months and how AI is compressing that cycleHow Vinci lets engineers get thermal and physics answers in seconds instead of daysThe existing workflow — designers, performance evaluators, and manufacturers rarely even work in the same teamHow simulation software went from requiring PhDs to something any engineer can accessThe digital twin concept — running physics experiments in software before touching physical prototypesWhy the semiconductor and data center cooling market is the starting pointNews — AI image and video generation still has not crossed the quality schismWhy there are no AI-generated movies on Netflix yet even though the models existHow AI getting into hardware design changes the stakes around IP and watermarkingThe parallel between language models democratizing reasoning and physics models democratizing simulationIf you are building hardware, working in semiconductors, or want to understand where AI is going beyond software, this episode is for you.Find Hardik:LinkedIn: linkedin.com/in/hardikkabariaTwitter: x.com/hardikk13Find Vinci:Website: getvinci.aiLinkedIn: linkedin.com/company/vinciphysicsCompany Twitter: x.com/VinciPhysicsNew episodes every Friday at BuiltThisWeek.comTIMESTAMPS[00:00] Intro[01:14] Meet Hardik — co-founder and CEO of Vinci[02:06] What Vinci does — making physics accessible for hardware builders[03:24] How simulation has worked in hardware for decades[04:33] The digital and physical world of experiments[05:47] Getting physics answers in seconds instead of days[06:28] How Vinci fits into the existing hardware design workflow[08:10] The tape-out problem — millions of dollars and months per iteration[10:00] Live demo — thermal simulation for semiconductor design[13:00] Who is using Vinci and what problems they are solving[15:30] The language model analogy — democratizing physics reasoning[17:00] News — AI image generation and the quality schism[19:30] Why there are no AI movies on Netflix yet[21:00] AI getting into hardware and the IP watermarking problem[23:50] The regulations and guardrails that will follow[26:05] Where to find Hardik and Vinci[26:43] Wrap up#AI #Physics #Semiconductors #HardwareDesign #Vinci #ChipDesign #BuildWithAI #BuiltThisWeek #AIHardware #Simulation

This week we sit down with Zach Rattner, CTO and co-founder of Yembo, to demo the computer vision platform that turns a ten minute phone walkthrough into a full home inventory, 3D model, and floor plan. Deployed in 35 countries, running thousands of inspections every day for moving companies and property insurers — and the end user never even knows AI is involved. We also dig into Claude Fable 5 being pulled without coding access, the 25,000 Chinese accounts exploiting the model, and whether AI has finally entered its regulatory adolescence.We cover:What Yembo does — computer vision that deeply understands the interior of homesHow a ten minute phone video replaces a 60 to 90 minute in-home inspectionThe visual inventory — color coded, numbered, time stamped photos of every itemWhy the real AI opportunity is doing what was previously impossible, not just fasterHow Yembo embedded AI in a workflow where the end user never knows it existsThe insurance use case — 3D model and floor plan from a single video walkthroughWhy 30 percent of their patents are on guiding the camera capture without any trainingClaude Fable 5 pulled and reinstated without coding access — what it means for developersAI reaching regulatory adolescence and whether the framework arrives in time25,000 Chinese accounts exploiting the model and the KYC failure behind itIf you are building with AI, working in insurance or logistics, or want an honest take on what happens when regulators start touching frontier models, this episode is for you.Find Zach and Yembo:Website: yembo.aiLinkedIn: search Zach RattnerNew episodes every Friday at BuiltThisWeek.comTIMESTAMPS[00:00] Intro[01:15] Meet Zach — CTO and co-founder of Yembo[02:05] What Yembo does — computer vision for home interiors[03:30] How a ten minute phone video replaces 90 minutes of in-home inspection[05:10] Live demo — the visual inventory report[07:00] The real AI opportunity — doing what was previously impossible[09:30] Embedding AI so the end user never knows it exists[11:00] Insurance use case — 3D model and floor plan from video[13:00] 30 percent of patents on guiding camera capture without a tutorial[14:30] News — Claude Fable 5 pulled and reinstated without coding[16:20] AI adolescence — the regulation debate[18:30] 25,000 Chinese accounts and the KYC problem[20:30] Where to find Zach and Yembo[21:00] Wrap up#AI #ComputerVision #Yembo #Insurance #MovingIndustry #ClaudeFable #BuildWithAI #BuiltThisWeek #PropTech #AIRegulation

This week we sit down with Ryan Aytay, President and COO of Code Metal, to dig into one of the most underestimated problems in tech — the legacy code running mission critical infrastructure across aerospace, defense, automotive, and medical devices. Code Metal translates that code to any hardware with mathematical proof it will behave identically. Provably correct. We also dig into Meta glasses, Jony Ive at OpenAI, and where AI hardware interfaces are really heading.We cover:What Code Metal does and why provably correct code mattersThe legacy code problem running mission critical infrastructure right nowWhy testing is not enough and what formal methods actually proveHow AI finally made formal verification scalable after 50 yearsThe Tesla over-the-air update analogy for code-to-hardware deploymentWhich industries Code Metal is built for and whyWhy vibe coding works for apps but terrifies Ryan for aerospace and defenseWhat brought Ryan from running Tableau at Salesforce to a code verification startupMeta Ray-Ban glasses — price drop, Kylie Jenner, and the veteran use caseJony Ive at OpenAI and what the mystery hardware device might beWhy every AI interface is converging on the same form factorIf you build software, work in hardware, or want to understand the infrastructure layer AI is about to touch, this episode is for you.Find Ryan and Code Metal:Website: codemetal.aiLinkedIn: linkedin.com/in/ryanaytayCompany LinkedIn: linkedin.com/company/code-metalTwitter: x.com/Code_Metal_AITIMESTAMPS[00:00] Intro[01:04] Meet Ryan — President and COO of Code Metal[02:00] What Code Metal does in one sentence[03:30] The legacy code problem in mission critical systems[05:32] What provably correct means and why testing is not enough[07:10] Formal methods — mathematical proof not just testing[08:45] How AI made formal verification scalable[10:20] Tesla over-the-air updates analogy[11:40] ICP — aerospace, defense, automotive, medical[13:05] Why vibe coding terrifies Ryan for mission critical systems[15:10] From Salesforce and Tableau to Code Metal — the origin story[17:30] News — Meta Ray-Ban glasses price drop and Kylie Jenner[19:45] Meta glasses given to veterans — the real use case[20:50] Jony Ive at OpenAI and the mystery hardware device[22:30] Why all AI interfaces are converging on glasses[23:05] Where to find Ryan and Code Metal[23:45] Wrap upNew episodes every Friday at BuiltThisWeek.com#AI #CodeMetal #FormalMethods #LegacyCode #Engineering #Defense #Aerospace #BuildWithAI #BuiltThisWeek #AIHardware