Built This Week

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• AI Agents Doing Commercial Real Estate Due Diligence in Minutes. We Demo It Live. 19.06.2026 24dk

  This week on Built This Week we sit down with Jackson, co-founder of Realm AI, to demo the platform replacing months of manual due diligence with AI agents that find, compile, and cite every piece of data on any commercial property in the US in minutes. We also go deep on the SpaceX IPO, what the Cursor acquisition means for the Elon portfolio, and whether the finance textbooks are just wrong.We cover:What Realm AI is and how it works for commercial real estate due diligenceA live demo of the self-serve platform — any property in the US in minutesHow dozens of AI agents communicate and delegate to find property dataWhy Realm deliberately refuses to make investment recommendationsThe before and after — printed spreadsheets and button calculators vs AI agentsHow small firms with three analysts are beating 100-analyst firms to dealsWho is actually using Realm AI and what surprised them about the ICPSpaceX IPO — is the valuation frothy or are the finance textbooks just wrong167 launches in 2025, one every 2.2 days, and no real competitionThe Cursor acquisition confirmed and what it means for the SpaceX portfolioHow Tesla, SpaceX, xAI, and Cursor all connect into one bigger visionWhat it actually feels like to watch a SpaceX launch in personIf you are in real estate, building with AI agents, or want a fresh take on the SpaceX IPO from people who actually use the product, this episode is for you.New episodes every Friday at BuiltThisWeek.comTIMESTAMPS[00:00] Intro[01:04] Meet Jackson — co-founder of Realm AI[02:03] What Realm AI does and the problem it solves[03:19] Live demo — researching any US property in minutes[05:10] How the waterfall of data agents works[07:20] Why Realm refuses to make property recommendations[09:08] Before vs after — the printed spreadsheet era[11:27] Who is getting the most value — small firms vs big funds[14:43] ICP and asset type diversity[15:40] News — SpaceX IPO valuation above Amazon[16:41] Jackson's take — throw away the finance textbooks[17:40] The SpaceX monopoly on launches — 167 trips in 2025[19:55] Jordan's bull case for the full Elon portfolio[21:12] Cursor acquisition confirmed[22:11] Watching a SpaceX launch in person[23:15] Where to find Jackson and Realm AI[23:46] Wrap up#AI #RealEstate #PropTech #AIAgents #SpaceX #Cursor #BuildWithAI #BuiltThisWeek #CommercialRealEstate
• We Tested Claude 4 Fable and Deployed Enterprise Agents Without a Single Data Migration 15.06.2026 23dk

  This week on Built This Week we sit down with Emanuele Melis, who leads Field Engineering at AI One, to demo how enterprises are deploying AI agents right now without needing a massive data transformation first. We also go deep on Claude 4 Fable — first impressions, token spend chaos, the '100x the design' prompt, and what the Jevons paradox means for AI consumption.We cover:Emmanuel builds a physics puzzle game from memory using Claude in 10 minutesJordan's first 36 hours with Claude 4 Fable — slow, expensive, and world classWhat happens when you type '100x the design' into FableWhy nobody knows how many tokens they are burning and why that needs to changeWhat AI One and Context One actually do for enterpriseThe autonomous ladder — how to deploy agents safely without giving them full controlThe sweet spot for AI agents: high complexity, low judgment workHow a financial firm cut a week-long investigation down to hours using agentsWhy 150,000 brittle rules are being replaced by a single agentMaking custom coloring books for kids with AI every dayJevons paradox — cheaper tokens, more consumption, no ceilingA PM had Claude Code listen to a live engineering meeting and build in real timeSpaceX IPO — the bull case, the wait and see case, and who is rightIf you are building with AI, deploying agents in enterprise, or just want an honest take on Claude 4 Fable, this episode is for you.Find Emanuele and AI One:Website: ai.oneLinkedIn: linkedin.com/in/emanuele-melisCompany LinkedIn: linkedin.com/company/ai-one-1TIMESTAMPS[00:00] Intro[01:33] Emmanuel builds a physics game with Claude in 10 minutes[03:30] Jordan's first take on Claude 4 Fable[04:35] Token spend confusion and the slider nobody understands[05:17] '100x the design' — what happened[06:37] Fable in five — Jordan's verdict[07:32] What AI One actually does — the context control layer[09:03] The autonomous ladder — starting agents at zero[10:12] High complexity low judgment — where agents win[11:40] Financial investigation use case — from one week to hours[13:25] 150,000 rules replaced by one agent[14:03] Coloring books for kids — the fun use case[15:07] News — Claude 4 Fable launch and what it means[15:55] Jevons paradox — cheaper tokens, more consumption[16:42] How fast AI has evolved in 18 months[17:17] Claude Code listening to live engineering meetings[18:49] SpaceX IPO — bull case vs wait and see[22:17] Where to find Emmanuel and AI One[22:50] Wrap upNew episodes every Friday at BuiltThisWeek.com#Claude #Fable #AI #BuildWithAI #Enterprise #AIAgents #SpaceX #BuiltThisWeek #AIOne #ContextOne
• Your Pipeline Is Lying to You. This AI Fixes It After Every Sales Call 05.06.2026 26dk

  This week on Built This Week we sit down with Anis Bennaceur, co-founder and CEO of Attention, to demo the AI-native Revenue Operating System that automates CRM updates, sales coaching, and pipeline forecasting after every call. Sam also demos a Monte Carlo forecast dashboard he built on top of Attention's open source coaching stack.We cover:What Attention is and how it automates sales operations end to endSam's live Monte Carlo forecast dashboard built on Attention's open source stackHow AI listens to every call and updates your CRM automaticallyWhy filling the CRM is the painkiller every sales team actually needsReal-time coaching scorecards and how reps get scored during the callPipeline forecasting and how AI catches deal risk before you doHow to manage LLM token costs at scale without killing developer productivityWhy Anis personally approves every token budget overrage at AttentionAnthropic filing for an IPO and what it means for the AI raceWhy Uber capping developer token spend is the wrong moveAgents vs deterministic workflows — the honest truth about what actually works in productionWhy the companies letting their teams run free with AI are pulling aheadIf you are in sales, building a revenue operations stack, or want to understand where AI is taking enterprise software, this episode is for you.Find Anis and Attention:Website: attention.comLinkedIn: linkedin.com/in/anis-bennaceurTwitter: x.com/anisbennaceur1Company LinkedIn: linkedin.com/company/attentiontechCompany Twitter: x.com/tryattentionTIMESTAMPS[00:00] Intro[01:03] Meet Anis — CEO and co-founder of Attention[01:50] Sam demos his Monte Carlo forecast built on Attention's open source stack[04:51] What Attention actually does — the core product[06:30] Painkiller vs vitamin — why CRM accuracy is the real problem[07:45] Real-time coaching scorecards and call scoring[09:20] Pipeline forecasting and deal risk detection[11:00] Who is using Attention and why[12:30] Automating work for reps, managers, leaders, and RevOps[14:00] News — Anthropic filing for an IPO[15:10] Uber CEO capping developer token spend[17:00] How Attention tracks LLM cost per client, per feature[19:05] Claude token caps and how Anis approves overrages personally[20:30] The token budget chaos — tracing where the spend went[22:30] Agents vs deterministic workflows — what actually works[24:34] Why workflows beat agents in most production scenarios[25:10] How to find Anis and Attention[25:30] Wrap upNew episodes every Friday at BuiltThisWeek.com#AI #Sales #CRM #BuildWithAI #Anthropic #AIAgents #RevOps #BuiltThisWeek #Attention
• This AI Platform Lets Anyone in Your Company Manage Operations Without a Single Engineer 29.05.2026 23dk

  This week on Built This Week we sit down with Wiley Jones, CEO and co-founder of Doss, to demo an AI-native operations platform built for mid-market companies managing the flow of goods, dollars, and data. He incorporated the company a month before ChatGPT existed.We cover:What Doss is and why he calls it an Adaptive Resource Platform not an ERPA live demo of the platform including inventory management, procurement, and order managementHow Doss lets companies build their own data model instead of forcing them into the shape of the softwareDOSBOT — an AI agent that can self-introspect the entire system and answer complex operational questionsWhy switching costs in enterprise software are only relevant if you are talking to the wrong customerHow to identify the 5 to 10 percent of the market that actually wants to moveThe ICP — physical product companies doing 20 million to a few hundred million in revenueNews — Robinhood launching AI agents to trade stocks and whether that is innovation or gamblingWhether AI trading bots can actually generate alpha or just raise everyone's tide equallyIf you are building in enterprise software, working in operations, or want to understand where AI is taking business systems, this episode is for you.
• The AI Product Team Replacement? Inside Autonomy AI’s Live Demo 22.05.2026 25dk

  This week on Built This Week we sit down with Adir, CEO and co-founder of Autonomy AI, to demo the platform helping enterprise teams build, update, and ship product changes directly on top of their existing codebase.No slides. Just a live walkthrough of the real product.We cover:What Autonomy AI is buildingHow non-technical teams can work directly with existing codebasesWhy the handoff between product, design, and engineering is still brokenBuilding new product views from a simple promptConnecting AI-generated work to real APIs and pull requestsDesign mode, Figma-style editing, and mobile responsivenessWhy companies are using less Figma and JiraWho is actually buying AI product-building toolsKarpathy joining Anthropic and what it means for the spaceGoogle’s new AI agents and the future of searchIf you are building with AI, managing product teams, or trying to understand how software development workflows are changing, this episode is for you.
• The Voice AI Platform Built for Enterprises That Actually Need to Scale 15.05.2026 23dk

  This week on Built This Week we sit down with Karim, founder and CEO of Breeze (heybreez.ai), to demo the enterprise voice agent platform built for companies that actually need to run AI at scale. No slides. No prep. Just a live walkthrough of the real product.We cover:What Breeze is and how it differs from other voice AI platformsA live demo of the platform built from a blank screenWhy multi-agent architecture matters for enterprise complianceHow to prevent voice agents from being jailbrokenThe latency and model selection decisions that make or break productionThe operational layer of voice AI that everyone is ignoringPhone groups, smart routing, and running 10,000 calls a dayWho is actually buying enterprise voice AI and whyBreeze's partnership model and expansion into MENA and South AmericaAnthropic raising at a $900 billion valuation and what it meansWhether AI is replacing junior developers and what comes nextIf you are building with AI, scaling voice agents, or trying to understand where enterprise AI is heading next, this episode is for you.Find Karim and Breeze:Website: heybreez.aiLinkedIn: linkedin.com/in/kmalhasTwitter: x.com/kmalhas_TIMESTAMPS[00:00] Intro[01:05] Meet Karim — founder and CEO of Breeze[02:12] Live demo — building a voice agent from scratch[07:34] Multi-agent architecture explained[11:55] Latency vs quality tradeoff in voice AI[12:56] OTP security and jailbreak prevention[14:13] The operational layer nobody is building[16:41] Version control, compliance, and phone groups[18:43] Who is the ideal customer for Breeze[21:49] Partnership model and global expansion[22:55] News — Anthropic raising at $900B valuation[24:28] Will AI replace junior developers[26:05] Building from the Middle East — why it matters[28:23] Where to find Karim and Breeze[28:52] Wrap upNew episodes every Friday at BuiltThisWeek.com#VoiceAI #AIAgents #Enterprise #Anthropic #BuildWithAI #BuiltThisWeek #AIStartup #heybreez
• This Headset Reads Your Brain in Real Time. We Demo It Live. 08.05.2026 21dk

  This week on Built This Week we sit down with Ramses Alcaide, founder of Neural, to demo a noninvasive brain computer interface that tracks your focus in real time through a pair of headphones. No surgery. No implants. Just data.We cover:What a brain computer interface actually is and how it worksA live demo of focus tracking during the episodeA browser plugin that adjusts podcast speed based on your brain activityHow the technology detects brain fatigue before you feel itGaming, medical, and sports applicationsHow AI finally unlocked BCI for consumer devices after 40 years in labsThe science behind ice baths affecting men and women differentlyWhy kids are bypassing age verification AI with a fake mustacheWhy AI security cameras are still failing at basic common senseThe edge compute problem nobody in consumer hardware wants to talk aboutWhy your brain signature might be the future of identity verificationIf you are building with AI, interested in wearables, or want to understand what brain computer interfaces actually are today, this episode is for you.TIMESTAMPS[00:00] Intro[00:44] Meet Ramses — what is a brain computer interface[01:40] How the headphones track focus in real time[02:28] Live focus tracking demo on the podcast[03:00] Browser plugin that adjusts podcast speed to your brain[04:35] How to use biofeedback to stay focused[07:02] Brain health tracking — cognitive strain and brain age[07:33] Gaming use case — overclocking your brain with HP[08:16] ER doctors and high stakes focus applications[09:08] How AI finally brought BCI out of the lab[10:01] Origin story — PhD, family tragedy, US Army backing[11:45] How to find Ramses and the product[13:09] Ice bath experiment — men vs women brain data[14:45] News — AI security cameras calling dogs bears[15:13] Why edge AI for consumer hardware is brutally hard[16:28] Brain data and camera AI share the same constraint[17:08] Kids bypassing age verification with a fake mustache[19:23] Brain signature as the future of identity verification[20:03] Wrap upNew episodes every Friday at BuiltThisWeek.com#BCI #AITools #Neuroscience #BuiltThisWeek #BrainComputerInterface #AI #Wearables #EdgeAI
• Claude Design Changes Everything (Figma in Trouble?) 24.04.2026 20dk

  This week on Built This Week, we break down one of the most interesting new AI product launches in recent memory: Claude Design.No demos. No fluff. Just what happens when AI starts replacing traditional design workflows.We cover: • What Claude Design is and how it works • Creating ad campaigns, decks, and full product redesigns with simple prompts • Why it could become a serious competitor to tools like Figma • How teams are exporting AI designs directly into production code • The rumored xAI / Cursor deal and what it means for the coding race • ChatGPT Images 2.0 and whether it lives up to the hype • Why Google might be quieter now—but still dangerous long termIf you're building with AI, working in design, or trying to understand where creative tools are heading next, this episode is for you.⏱ TIMESTAMPS[00:00] Intro [00:45] Claude Design overview [01:50] First impressions after using Claude Design [03:00] How the interface works [04:20] Building decks, ads, and redesigns with prompts [06:10] Creating ad campaigns for Hip Train [07:45] Exporting projects, sharing, and production handoff [10:15] Full internal app redesign with AI [12:45] Is Claude Design a Figma killer? [13:00] xAI / Cursor acquisition rumors [16:15] ChatGPT Images 2.0 reactions [18:30] Why AI is still in the early innings [21:40] Google’s new TPUs and staying in the race [22:40] Wrap up & what’s next for Built This WeekLinksBuiltThisWeek.comNew episodes every FridayJordan Metznerhttps://x.com/mrjmetzSam Nadlerhttps://x.com/Gravino05
• This AI Tool Turns Meetings Into Jira Tickets Instantly 17.04.2026 19dk

  This week on Built This Week, we break down how AI helped a non-technical teammate build a real internal product that now helps teams move faster across the company.No buzzwords. No fake use cases. Just real AI in production.We cover: • The AI tool that automates meeting follow-up work • How transcripts become tickets, reports, and dashboards • Why internal AI products are becoming a huge advantage • How companies can train non-technical teams to build • What happens when everyone can create software • Why the next wave of AI is about empowermentIf you're serious about using AI to improve your business, this episode is for you.⏱ TIMESTAMPS(00:00) Intro (00:32) Welcome back (00:40) Guest introduction (01:28) Inside the Radar tool (02:36) Solving workflow bottlenecks with AI (03:23) Instant task generation from meetings (04:45) Smarter project visibility with dashboards (05:56) Real productivity gains (07:00) From personal tool to company product (08:08) Future roadmap (09:24) AI-generated business reviews (10:19) Building an AI-first culture (11:30) Teaching non-technical teams (12:49) Real examples across departments (13:57) Why this changes work forever (15:06) News segment (17:44) Closing thoughts🎙 HOST INFOHosted by Jordan Metzner and Sam Nadler Co-founders of Ryz LabsWe build AI-native companies and tools used by startups, enterprises, and investors.🔗 CTA + LINKSSubscribe for weekly breakdowns of real AI builds and what actually matters New episodes every FridayFollow along: YouTube: Built This Week Spotify: Built This Week Apple: Built This Week
• We Built an AI Tool That Replaced a Week of Work 10.04.2026 23dk

  This week on Built This Week, we break down a real AI tool we built that’s already saving days of work in production.No demos. No fluff. Just how AI is actually being used inside a real business.We cover: • The internal tool that replaced complex spreadsheets and cut turnaround time in half • How we generate client-ready presentations instantly with AI • Why tool selection matters more than ever in the agentic era • Google AI Studio and how we use it to prototype fast • Anthropic’s unreleased model and what it means for AI safety • Meta’s latest push into AI and why competition is heating upIf you're building with AI or thinking about how to apply it inside your company, this episode is for you.⏱ TIMESTAMPS00:00 Intro 00:40 What we’re covering this week 01:30 The problem with planning large offsites 02:28 How you lose money without perfect cost visibility 03:23 The AI tool we built (Offsite estimator) 04:29 Hidden costs AI catches that humans miss 05:36 From spreadsheets to automated workflows 06:04 Instant client presentations with AI 07:19 Cutting turnaround time from 10 days to 3 08:09 Tech stack behind the tool (Codex, Supabase, React, AWS) 08:58 Real customer impact and results 10:05 What we’re building next (automation + client portal)10:40 Google AI Studio deep dive 11:14 How we actually use it for prototyping 12:55 Image, music, and video generation tools 14:48 When to use which AI tool15:33 The real framework for choosing AI tools 16:45 Anthropic’s unreleased model 17:54 Why it might be a security risk 18:32 Who should control powerful AI19:45 Meta’s new AI push 21:10 Why competition is accelerating22:30 Wrap up🎙 HOST INFOHosted by Jordan Metzner and Sam NadlerCo-founders of Ryz LabsWe build AI-native companies and tools used by startups, enterprises, and investors.
• Why AI Inference Is So Expensive (And How Positron Is Solving It) 03.04.2026 29dk

  Training gets the headlines.Inference is where the money is.In Episode 37 of Built This Week, we sit down with Mitesh, CEO of Positron AI, to break down one of the biggest bottlenecks in AI today: inference infrastructure.While the world focuses on trillion-parameter models and frontier labs, the real constraint isn’t intelligence — it’s memory, bandwidth, energy, and cost.We cover:• Why inference is where 90% of AI spend happens • The memory wall problem in large models • Why GPUs weren’t designed for text generation • How Positron is building terabyte-plus memory chips • The economics of 10 trillion parameter models • Why memory bandwidth utilization matters • Why CPUs are suddenly back in demand • The difference between speed-optimized and cost-optimized AI systems • The slider bar future of AI infrastructureWe also dive into:• OpenAI’s $122B valuation • Anthropic vs OpenAI secondary market dynamics • Why Nvidia isn’t going anywhere • Why commodity memory might beat premium stacks in certain use cases • The rise of agentic workflows and what that means for computeIf you care about the future of AI, silicon, infrastructure, or trillion-dollar companies — this episode is for you.New episodes every Friday.⏱ TIMESTAMPS(0:00) Why inference is the real AI bottleneck (2:00) What Positron AI is building (4:30) The memory problem in trillion-parameter models (6:30) Why GPUs struggle with inference economics (9:00) Energy, bandwidth, and supply chain constraints (12:00) Memory capacity vs memory speed tradeoffs (16:00) The “slider bar” model of AI infrastructure (18:30) OpenAI’s $122B valuation discussion (21:00) Anthropic vs OpenAI secondary markets (23:30) CPUs making a comeback (26:00) Agentic workflows and compute demand explosion (28:00) Closing thoughts on AI infrastructure
• How We Built an AI Video Editor for Recruiters (Remotion + Claude + Codex) 22.03.2026 18dk

  Our recruiters are not video editors.But now they can cut highlight reels in minutes.In Episode 36 of Built This Week, we break down a tool we built internally at Ryz Labs that lets our recruiting team generate polished candidate highlight videos without touching Premiere, Final Cut, or CapCut.The problem:When presenting candidates to clients, resumes are standard. But seeing a candidate speak for 60 seconds changes everything.The issue was speed. Editing sizzle reels required our video team, added delays, and was not scalable.So we built a highlight reel generator powered by:• EntreVista AI interview transcripts • Claude and Codex for clip selection • Remotion for video rendering via code • AWS S3 for instant share linksThe system automatically: • Analyzes transcripts • Identifies high signal clips • Groups them by communication, role fit, and personality • Allows light manual adjustments • Renders a branded video in 5 to 10 minutesNo editing experience required.Then we dive into Remotion and why “video as code” is one of the most underrated AI enabled workflows right now.Finally, we discuss the growing cost of AI usage inside organizations: • Token spend management • Surprise AI bills • Model access guardrails • Productivity vs cost tradeoffsAI is democratizing building.But it is also introducing a new management layer.New episodes every Friday.⏱ TIMESTAMPS(0:00) The problem: recruiters are not video editors (0:25) Welcome to Episode 36 (1:20) Why highlight reels improve candidate selection (2:30) The scalability issue with manual video editing (3:30) Demo: AI Highlight Reel Builder (4:15) How transcripts power automatic clip selection (5:00) Communication, role fit, personality grouping (6:10) Manual adjustments for recruiters (7:00) Rendering time and infrastructure challenges (8:00) Final sizzle reel output demo (9:00) How it was built with Codex (10:00) What is Remotion (11:30) Video editing as code explained (12:30) Other Remotion use cases: product trailers, documentation videos (13:45) Democratizing creative production (14:30) AI token costs inside organizations (15:15) Surprise AI bills and infrastructure lessons (16:30) Managing model access across teams (17:30) Productivity vs spend tradeoffs (18:15) Closing thoughts🔗 LINKSBuilt This Week New episodes every Friday https://builtthisweek.comJordan Metzner https://x.com/mrjmetzSam Nadler https://x.com/Gravino05
• AI Agents Are Replacing Entire Marketing Teams 14.03.2026 29dk

  Marketing teams are about to change forever.Instead of hiring designers, copywriters, analysts, SEO specialists, and performance marketers… companies are starting to run AI marketing agents that handle everything.From planning campaigns to creating content, analyzing performance data, generating ads, and optimizing strategy automatically.In this episode of Built This Week, Sam Nadler and Jordan Metzner sit down with Iliya Valchanov, CEO of Juma, to explore how AI agents are transforming modern marketing workflows.Juma is building an AI marketing super-agent that can autonomously plan, execute, and optimize marketing campaigns across channels like social media, ads, analytics, and SEO.During the episode, Ilia demos how a single prompt can generate a complete social media strategy, content calendar, and visual assets in minutes.Even more surprising — Ilia explains how their own company replaced a 7-person go-to-market team with just one person using AI agents.We also dive into the future of AI agents, how developers are working with coding agents like Claude Code and Codex, and why the next wave of AI tools may turn websites into constantly evolving, self-optimizing systems.In this episode we discuss:• How AI agents automate entire marketing workflows • Turning a single prompt into a full social media calendar • Why marketing teams are early adopters of AI • How AI agents connect to tools like Google Analytics, HubSpot, and Meta Ads • Why saving time isn’t the real benefit of AI • How AI increases marketing quality and experimentation • How agencies measure ROI and billable hour savings from AI • Why companies need a dedicated “AI transformation leader” • Claude Code vs Codex vs Cursor for AI coding workflows • Andrej Karpathy’s new auto-research AI experimentsThis episode is a glimpse at how AI agents may reshape marketing, coding, and digital products over the next decade.⏱️ TIMESTAMPS(0:00) Welcome to Built This Week (0:31) Introducing Ilia from Juma (0:46) What Juma is building (1:26) Live demo: AI marketing agent (2:10) Generating a social media calendar with one prompt (3:02) Researching competitors automatically (3:52) Building a full content strategy (4:30) Creating Instagram carousels with AI (5:21) Integrations with Google Analytics, HubSpot, and Ads (6:03) Can AI learn which content performs best? (6:49) Who is using Juma today (7:40) Marketing teams vs marketing agencies (8:05) Replacing a 7-person marketing team with AI (8:58) Publishing blog posts in 3 minutes (9:40) Why AI unlocks new marketing opportunities (10:27) Measuring ROI and billable hours saved (11:06) How AI removes the need for specialized marketing roles (12:00) Why ad optimization is the biggest AI opportunity (12:27) Biggest lessons from running AI agents in marketing (13:04) Why companies need an AI transformation leader (14:02) Claude Code vs Codex vs Cursor (16:00) The future of AI coding agents (18:56) Why developers are reading less code (20:45) How programming may change in the AI era (22:06) Andrej Karpathy’s new auto-research AI tools (24:38) AI experiments and self-optimizing websites (27:10) Final thoughts on the future of AI agents (28:06) Where to find Juma🔗 LINKSJuma https://juma.aiBuilt This Week New episodes every Friday🎙️ HOSTSJordan Metzner https://linkedin.com/in/jordanmetzner https://x.com/mrjmetzSam Nadler https://linkedin.com/in/sam-nadler-1881b75 https://x.com/Gravino05
• AI Is Rebuilding Clinical Trials 07.03.2026 26dk

  Clinical trials are one of the slowest and most expensive processes in modern medicine.It can take 10–15 years and up to $3 billion to bring a new drug to market — and many trials fail simply because they can’t enroll enough patients.In this episode of Built This Week, Sam Nadler and Jordan Metzner sit down with Dr. Chadi Nabhan, Chief Medical Officer at RyghtAI, to explore how AI-powered digital twins of clinical trial sites can dramatically improve the speed and success of clinical trials.RyghtAI has built a platform that creates digital twins of thousands of clinical trial sites worldwide, allowing pharmaceutical companies to instantly identify the best locations and investigators for any given trial.Instead of relying on manual site selection or reputation-based decisions, AI analyzes historical trial performance, patient demographics, biomarker capabilities, and infrastructure to determine which sites are most likely to enroll patients successfully.The result: faster trials, better patient representation, and potentially life-saving therapies reaching the market sooner.In this episode we discuss:• Why 80% of clinical trials fall behind schedule • Why half of clinical trial sites enroll 0–1 patients • How AI parses 200-page trial protocols in seconds • The role of digital twins in predicting trial success • How AI improves patient diversity in clinical trials • Why biomarker data is becoming essential in modern medicine • How AI agents infer site capabilities from historical trial data • Why informed patients using AI tools may actually improve healthcare outcomesIf AI can dramatically improve the speed and efficiency of clinical trials, it could reshape how quickly new treatments reach patients worldwide.⏱️ TIMESTAMPS(0:00) Welcome to Built This Week (0:37) Introducing Dr. Chadi Nabhan from Ryght AI (1:12) What RyghtAI is building (2:14) The problem with clinical trial site selection (3:07) Digital twins for clinical trial sites (4:01) Manual vs AI-driven trial strategy simulation (5:15) Why clinical trials fail (6:03) The massive cost and time of drug development (6:51) How AI identifies the best trial sites (8:00) Ranking clinical trial sites using AI scoring (9:03) Diversity challenges in clinical trials (10:02) Using census data to improve patient representation (10:35) Biomarkers and genomic trial requirements (11:48) Predicting future trial success from past data (12:14) How AI accelerates trial matching (13:04) AI agents reading clinical trial protocols (14:20) Parsing 200-page protocols in seconds (15:00) AI identifying investigators and site contacts (15:57) Helping overlooked clinical sites get discovered (17:47) AI’s expanding role in healthcare innovation (18:00) Eight Sleep raises $50M at a $1.5B valuation (21:09) Apple releases a $599 MacBook (23:00) Dr. Nabhan’s upcoming book: AI and Cancer Care (23:33) Will AI replace Google for patient research? (25:30) The future of personalized AI healthcare (26:10) Final thoughts and wrap-up🔗 LINKSRyght AI https://ryght.aiDr. Chadi Nabhan https://chadinabhan.comBuilt This Week New episodes every Friday🎙️ HOSTSJordan Metzner https://linkedin.com/in/jordanmetzner https://x.com/mrjmetzSam Nadler https://linkedin.com/in/sam-nadler-1881b75 https://x.com/Gravino05
• AI Is Transforming Construction — We’re Entering a Golden Era 27.02.2026 27dk

  Construction has lagged behind every major industry in technology adoption.Manual data entry. Spreadsheets. Email-based procurement. Slow invoice approvals. Paper delivery tickets.That’s finally changing.In this episode of Built This Week, Sam Nadler and Jordan Metzner sit down with Eldar (Field Materials AI) to break down how AI is automating procurement for commercial and civil contractors — from reading quotes and invoices to verifying pricing, matching delivery tickets, and integrating directly with ERPs.Field Materials builds AI agents that eliminate manual data entry across the procure-to-pay cycle for electrical, mechanical, concrete, drywall, and other commercial subcontractors working on hospitals, data centers, and billion-dollar infrastructure projects.We also explore:• Why construction productivity has barely improved in decades • How AI agents read and process supplier quotes automatically • How foundational model improvements upgrade products overnight • Why procurement automation directly impacts margin • The data center boom forcing construction to modernize • The difference between “adding AI” and building AI-first software • Whether incumbents like SAP and Salesforce are at risk • Why we may be entering a golden era for construction technologyThis isn’t theoretical AI.This is production AI operating inside large-scale commercial construction projects today.⏱️ TIMESTAMPS(0:00) Entering the golden era of construction tech (0:24) Welcome to Built This Week (0:43) Introducing Field Materials AI (1:12) What Field Materials actually does (1:41) Scenario modeling demo (BOM shock analysis) (3:51) Pricing intelligence and risk modeling (4:53) How the company started (6:13) Automating quotes, invoices, and delivery tickets (7:23) Who uses Field Materials (commercial subs) (8:49) How procurement actually works today (manual chaos) (10:07) Cutting overhead and scaling without hiring (11:29) Reducing material waste and pricing errors (12:25) Accelerating invoice approval cycles (13:04) AI agents for different document types (14:01) How foundational model upgrades improve the product (15:09) Why construction underinvested in tech (15:52) The data center boom forcing modernization (16:49) AI + robotics + prefabrication (17:31) Anthropic partnerships and enterprise AI integration (18:39) The next wave: AI with “hands” in enterprise systems (19:49) Why incumbents risk building gimmicks (21:07) Salesforce, SAP, and retention vs innovation (24:12) COBOL, modernization, and disruption cycles (26:39) Why building real AI tools is still hard (27:03) Where to find Field Materials🔗 LINKSField Materials https://fieldmaterials.aiBuilt This Week New episodes every Friday🎙️ HOSTSJordan Metzner https://linkedin.com/in/jordanmetzner https://x.com/mrjmetzSam Nadler https://linkedin.com/in/sam-nadler-1881b75 https://x.com/Gravino05
• From DNA to Drugs: How AI Is Rewriting Human Biology 21.02.2026 30dk

  DNA is just another language.In Episode 32 of Built This Week, we sit down with Dov Gertz, founder of Converge Bio, to explore how generative AI is transforming drug discovery.Every human can be represented as 3.2 billion nucleotides built from four letters: A, C, G, and T. If computers run on zeros and ones, we run on biological code.Converge Bio is training frontier foundation models on DNA, RNA, proteins, and small molecules — helping biotech and pharma companies design better drugs, faster and cheaper.We also demo a retro-inspired “Cell Defense Arena” game built for Converge to use at conferences.Then we pivot into AI infrastructure and agent workflows:The GPU bottleneck and pharma’s growing demand for compute Why molecular AI is 5 to 10 years behind text models How AI could reduce drug timelines from 10 years to 6 to 8 Why cancer and autoimmune diseases may benefit first The limits of FDA regulation in shortening approval cycles OpenClaw, multi-agent systems, and infinite AI teams Cloud versus on prem in the era of foundation modelsThe big takeaway:Chatbots are impressive. But AI applied to biology could extend human life.If you work in biotech, pharma, AI research, or frontier infrastructure — this episode is for you.New episodes every Friday.⏱ TIMESTAMPS(0:00) DNA as code: 3.2 billion nucleotides (0:32) Welcome to Episode 32 (1:00) Meet Dov Gertz and Converge Bio (2:02) Demo: Cell Defense Arena game (3:25) Converge Bio’s $33M raise and mission (4:05) Foundation models for molecular data (5:00) Turning DNA, RNA, and proteins into machine-readable text (6:02) How transformers apply to biology (7:03) 400x more DNA than text on the internet (8:02) Who Converge’s customers are (9:21) Faster, cheaper, better drug discovery (10:39) The three bottlenecks: data, architecture, compute (12:02) The future of personalized medicine (13:02) Which diseases benefit first: cancer, diabetes, autoimmune (14:00) Regulatory realities and clinical trial timelines (16:30) Will AI shorten drug approval cycles? (17:01) NVIDIA, GPUs, and scaling molecular AI (18:30) Pharma as a new AI infrastructure consumer (19:13) Hard pivot: OpenClaw and agentic AI (21:26) Managing teams of AI agents (22:20) Cloud versus on prem debate (25:02) Why developers must adapt weekly (29:26) Closing thoughts and where to find Converge Bio🔗 LINKSConverge Bio https://converge-bio.comBuilt This Week New episodes every Friday https://builtthisweek.comJordan Metzner https://x.com/mrjmetzSam Nadler https://x.com/Gravino05
• How AI Is Replacing 100-Hour Due Diligence (Claude 4.6, Private Equity, and Emblem) 13.02.2026 25dk

  Private equity due diligence used to take hundreds of hours. Now it takes seconds.In Episode 31 of Built This Week, we sit down with August Kiles, Head of Product at Emblem, to break down how AI is transforming investment funds — from venture capital to growth equity to private equity.Emblem is building what they call the “last platform investors will ever need” — a system that ingests entire data rooms, extracts financials, compares deals, generates reports in Word, Excel, and PowerPoint, and helps funds get to a “no” faster.We also demo a portfolio scenario simulation tool inspired by Emblem — showing how macro events like regulatory pressure or liquidity surges could impact a 30-company portfolio.Then we dive into the latest AI news:Amazon engineers pushing for Claude Code over internal toolsWhy Opus 4.6 is a step-function improvement for codingHow AI is changing software development workflowsElon Musk’s XAI reorg and what it signals about model competitionThe big takeaway:AI is not eliminating analysts. It’s increasing deal throughput and freeing them to focus on alpha.If you work in VC, private equity, family offices, or growth equity — this episode is for you.New episodes every Friday.⏱ TIMESTAMPS(0:00) Emblem’s mission: the last platform investors will ever need (0:25) Welcome to Episode 31 (0:55) Meet August Kiles from Emblem (1:28) Building a portfolio scenario simulation tool (2:05) Modeling regulatory pressure across a 30-company fund (3:00) Liquidity supernova scenario explained (4:00) What Emblem actually does for investment funds (5:00) AI-powered due diligence and data room indexing (6:00) From 100 hours of analysis to seconds (7:20) The old way vs the AI-powered way (8:30) Will AI reduce analyst headcount? (9:40) Getting to “no” faster in private equity (10:30) Where Emblem shines: seed vs private equity (12:00) Multi-agent model orchestration inside Emblem (13:00) How new models improved financial modeling (15:00) Amazon engineers pushing for Claude Code (17:30) Step-function improvements in Opus 4.6 (19:00) Coding workflows transformed by new models (21:30) Elon Musk’s XAI reorganization (23:00) Why model quality now matters more than IDE (25:00) Final thoughts and wrap-up🔗 LINKSEmblem https://emblem.peBuilt This Week New episodes every Friday https://builtthisweek.comJordan Metzner https://x.com/mrjmetzSam Nadler https://x.com/Gravino05
• Claude Opus 4.6, Codex 5.3, and the Rise of Multi-Agent AI 06.02.2026 18dk

  The biggest shift in AI isn’t a new model. It’s agents managing other agents.In Episode 30 of Built This Week, Sam Nadler and Jordan Metzner break down how they’re actually using the latest AI releases — including Claude Opus 4.6 and OpenAI Codex 5.3 — to build real software inside their own workflows.Jordan walks through a private, fully local AI system built with Claude Code that turns raw 23andMe data, blood work, medications, and personal health inputs into a unified health dashboard. The goal isn’t diagnostics — it’s creating a long-term, living record that surfaces insights doctors don’t easily connect.Sam then demos an AI-powered personal trainer built using the new Codex desktop Mac app and high-reasoning models. The system adapts workouts rep-by-rep, adjusts volume in real time, and highlights the tradeoffs between fast iteration tools and slower, deeper reasoning workflows.We close with the biggest AI platform launches of the week:Anthropic’s Opus 4.6 and Agent TeamsOpenAI Frontier and enterprise AI coworkersPerplexity’s Council Mode and LLM swarmsThe era of one chatbot at a time is over. The new skill is learning how to manage AI agents that manage other agents.No hype. No abstractions. Just what actually happens when builders use AI on themselves first.New episodes every Friday.TIMESTAMPS(0:00) The shift from single-agent AI to multi-agent systems (0:21) Welcome to Built This Week Episode 30 (1:00) Agenda and why this week matters (1:38) Why Jordan downloaded his 23andMe data (2:30) Turning unreadable DNA files into usable insights (3:50) Combining genetics, blood work, and medications (5:05) Drug response insights and hereditary signals (6:10) Generating doctor-ready reports for family (7:20) Why this system runs fully local (8:00) Building personal software instead of buying tools (8:40) Sam’s AI personal trainer built with Codex (9:50) Rep-by-rep workout feedback and fatigue detection (10:45) Designing AI interfaces for real-world use (11:40) Codex vs Claude Code: speed vs deep reasoning (12:20) Anthropic Opus 4.6 and Agent Teams (13:00) OpenAI Frontier and AI coworkers (13:25) Perplexity Council Mode and model swarms (14:05) Why multi-agent management is the real inflection (15:15) Becoming a manager of AI managers (16:00) How many agents one human can manage (17:00) AI’s impact on legacy software companies (18:15) Episode 30 wrap-up and what’s nextLINKSBuilt This Week New episodes every Friday https://builtthisweek.comJordan Metzner https://x.com/mrjmetzSam Nadler https://x.com/Gravino05
• We Built an AI Recruiter Coach in 6 Hours (Plus Claude Cowork in Real Time) 31.01.2026 20dk

  Can you really build serious internal AI tools in a few hours — and should everyone on your team be doing it?In Episode 29 of Built This Week, Sam Nadler and Jordan Metzner break down an internal AI product they built at Ryz Labs called ScreenEval — a recruiter screen analysis and coaching tool built in under six hours using Claude Code, Supabase, and AWS.We start with a live demo. Sam walks through how ScreenEval ingests recruiter screen transcripts, evaluates candidates, scores recruiter performance, and provides concrete coaching feedback — all without overriding human judgment. The real unlock is turning messy interview transcripts into searchable, structured hiring data across the entire organization.From there, we test Claude Cowork live — Anthropic’s new interface designed to make building accessible to non-technical users — and compare it to running Claude Code directly in the terminal. We discuss where Cowork shines, where terminal-based workflows still win, and why managing multiple AI agents is becoming a core skill.We wrap with AI news, including Anthropic’s massive funding round, pricing changes, and why enterprise-focused AI tooling is pulling spend away from other platforms.No hype. No abstractions. Just what actually happens when you put AI to work inside a real company.New episodes every Friday.================================================================================TIMESTAMPS(0:00) Why internal AI tools matter more than external products (0:55) Episode 29 kickoff and overview (1:45) Why Ryz Labs built ScreenEval (3:30) Live demo: recruiter screen transcript analysis (6:15) Candidate evaluation vs recruiter coaching (9:10) What recruiters miss in fast screening calls (11:40) AI feedback that doesn’t override human judgment (14:00) Searching transcripts instead of resumes (17:20) Manager dashboards and recruiter performance analytics (21:10) How long it actually took to build ScreenEval (23:30) The full stack: Claude Code, Supabase, AWS (25:45) Why Anthropic models power everything (27:30) Claude Cowork explained (29:15) Building a new product live with Cowork (32:40) Cowork vs Claude Code in the terminal (36:00) Managing multiple AI agents at once (39:30) Anthropic’s funding round and market momentum (42:15) Why we’re shifting spend away from other AI tools (45:10) AI inside organizations: efficiency without layoffs (48:30) What every team should be building next (50:45) Final thoughts and closing================================================================================LINKS SECTIONBuilt This Week New episodes every FridayJordan Metzner https://x.com/mrjmetzSam Nadler https://x.com/Gravino05Built This Week https://builtthisweek.com
• Why You Can't Pen Test an Airplane — AI Cybersecurity for Aviation 23.01.2026 20dk

  Can you really hack an airplane? And if so, how do you test for it without grounding the fleet for a year?In Episode 28 of Built This Week, Sam Nadler and Jordan Metzner sit down with Eero Salih, CTO of Syberian, to explore how AI is transforming cybersecurity for commercial aviation.We start with a live demo — a flight ops cyber radar Sam built to surface real-time security risks across airline operations. Then Eero breaks down what Syberian actually does: building digital twins of aircraft systems to run risk assessments without ever touching the physical plane.This is critical because traditional penetration testing would ground an aircraft for up to a year for recertification. Syberian's AI-powered approach analyzes over 100 technical documents to map every computer system on board — from avionics to entertainment to crew scheduling — and identify vulnerabilities before they become incidents.We also discuss:Why cyber attacks on aviation are now classified as safety threatsNew 2026 regulations forcing airlines to comply with stricter cybersecurity standardsHow small teams are replacing developers with AI agent managersThe tools Syberian uses: Claude Code, Windsurf, Anthropic, and GeminiWhy Google and Anthropic are rejecting ads while OpenAI explores themAn ex-Amazon exec who vibe-coded a full CRM replacement in 72 hoursNo hype.No theory.Just what happens when you put AI in charge of protecting critical infrastructure.New episodes every Friday.================================================================================TIMESTAMPS--------------------------------------------------------------------------------(0:00) Why you can't hack-test an airplane(0:45) Episode 28 kickoff and guest introduction(1:30) Live demo: Flight ops cyber radar dashboard(3:00) Analyzing real-time security threats across airline systems(4:30) What Syberian actually does (in plain English)(6:00) Why physical penetration testing grounds planes for a year(7:30) Using AI to build digital twins of aircraft systems(8:15) Hiring managers, not developers — AI agents do the coding(9:30) Tools of the trade: Claude Code, Windsurf, Anthropic, Gemini(10:00) New 2026 aviation cybersecurity regulations explained(11:00) How cyber attacks became classified as safety threats(12:30) The ripple effects: baggage weight, fuel calculations, pilot tablets(13:30) Who are Syberian's customers? Airlines, private jets, and more(14:55) AI News: Google and Anthropic reject ads in chatbots(16:30) Why Anthropic's no-ads stance matters for enterprise customers(17:30) Amazon exec vibe-codes full CRM replacement in 72 hours(18:30) Why vibe coding works for internal tools but not production(19:15) Final thoughts and closing================================================================================LINKS SECTION--------------------------------------------------------------------------------Built This WeekNew episodes every FridayJordan Metznerhttps://x.com/mrjmetzSam Nadlerhttps://x.com/Gravino05