Built This Week

Jordan Metzner, Samuel Nadler
  • 5.0 (4)
  • ENTREPRENEURSHIP

Built This Week is a weekly podcast where real builders share what they're shipping, the AI tools they're trying, and the tech news that actually matters. Hosted by Sam and Jordan from Ryz Labs, the show offers a raw, inside look at building products in the AI era—no fluff, no performative hype, just honest takes and practical insights from the front lines.

  1. 5D AGO

    How We Built an AI Video Editor for Recruiters (Remotion + Claude + Codex)

    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 links The 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 minutes No 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 tradeoffs AI 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 🔗 LINKS Built This Week New episodes every Friday https://builtthisweek.com Jordan Metzner https://x.com/mrjmetz Sam Nadler https://x.com/Gravino05

    19 min

  2. MAR 14

    AI Agents Are Replacing Entire Marketing Teams

    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 experiments This 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 🔗 LINKS Juma https://juma.ai Built This Week New episodes every Friday 🎙️ HOSTS Jordan Metzner https://linkedin.com/in/jordanmetzner https://x.com/mrjmetz Sam Nadler https://linkedin.com/in/sam-nadler-1881b75 https://x.com/Gravino05

    29 min

  3. MAR 7

    AI Is Rebuilding Clinical Trials

    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 outcomes If 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 🔗 LINKS Ryght AI https://ryght.ai Dr. Chadi Nabhan https://chadinabhan.com Built This Week New episodes every Friday 🎙️ HOSTS Jordan Metzner https://linkedin.com/in/jordanmetzner https://x.com/mrjmetz Sam Nadler https://linkedin.com/in/sam-nadler-1881b75 https://x.com/Gravino05

    27 min

  4. FEB 28

    AI Is Transforming Construction — We’re Entering a Golden Era

    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 technology This 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 🔗 LINKS Field Materials https://fieldmaterials.ai Built This Week New episodes every Friday 🎙️ HOSTS Jordan Metzner https://linkedin.com/in/jordanmetzner https://x.com/mrjmetz Sam Nadler https://linkedin.com/in/sam-nadler-1881b75 https://x.com/Gravino05

    28 min

  5. FEB 21

    From DNA to Drugs: How AI Is Rewriting Human Biology

    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 models The 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 🔗 LINKS Converge Bio https://converge-bio.com Built This Week New episodes every Friday https://builtthisweek.com Jordan Metzner https://x.com/mrjmetz Sam Nadler https://x.com/Gravino05

    30 min

  6. FEB 13

    How AI Is Replacing 100-Hour Due Diligence (Claude 4.6, Private Equity, and Emblem)

    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 🔗 LINKS Emblem https://emblem.pe Built This Week New episodes every Friday https://builtthisweek.com Jordan Metzner https://x.com/mrjmetz Sam Nadler https://x.com/Gravino05

    26 min

  7. FEB 7

    Claude Opus 4.6, Codex 5.3, and the Rise of Multi-Agent AI

    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 next LINKS Built This Week New episodes every Friday https://builtthisweek.com Jordan Metzner https://x.com/mrjmetz Sam Nadler https://x.com/Gravino05

    19 min

  8. FEB 1

    We Built an AI Recruiter Coach in 6 Hours (Plus Claude Cowork in Real Time)

    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 SECTION Built This Week New episodes every Friday Jordan Metzner https://x.com/mrjmetz Sam Nadler https://x.com/Gravino05 Built This Week https://builtthisweek.com

    20 min
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About

Built This Week is a weekly podcast where real builders share what they're shipping, the AI tools they're trying, and the tech news that actually matters. Hosted by Sam and Jordan from Ryz Labs, the show offers a raw, inside look at building products in the AI era—no fluff, no performative hype, just honest takes and practical insights from the front lines.

Information

  • Creator
    Jordan Metzner, Samuel Nadler
  • Years Active
    2025 - 2026
  • Episodes
    37
  • Rating
    Clean
  • Copyright
    © 2025
  • Show Website
    Built This Week

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