AI Tinkerers - "One-Shot"

Joe Heitzeberg
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AI Tinkerers "One-Shot" takes you 1:1 with AI practitioners, software engineers, and tech entrepreneurs around the world -- the best of the AI Tinkerers global network. Each session includes live demos of real AI projects, detailed code walkthroughs, and unscripted discussions led by a technical host who explores practical applications and implementation challenges. As an AI builder, you'll gain actionable insights into emerging tools, techniques, and use cases, plus opportunities to connect with a global network of peers working on similar problems.

  1. What Happens When You Hit Claude’s Limits? | Sam Hesson (Meta AI)

    FEB 25

    What Happens When You Hit Claude’s Limits? | Sam Hesson (Meta AI)

    Description: Sam Hesson — technical founder and newly minted member of Meta's AI incubation team — joins the AI Tinkerers One-Shot podcast for a deep-dive into the custom CI/CD pipeline he built to orchestrate parallel AI agents at scale. Sam became notorious for spending $50,000 on tokens in just two months while pushing the limits of what agentic development systems can do. In this episode, he shares his complete architecture. Sam walks through his "Token Abundance Mindset" and explains why moving beyond single-turn prompting is the key to unlocking a fully automated, multi-agent development workflow. From structuring your codebase for AI readiness to running adversarial LLM judges that self-heal pull requests, this is one of the most technically advanced conversations we've had on the show. Topics covered in this episode: The Darwinian CI/CD — running multiple parallel agents in competition to produce the best pull requestLLM Judge — rubric-based quality control and adversarial agents for self-healing PRsAI Dev Readiness — DB seeding, snapshots, and codebase prep for reliable agent testingThe Walk Flow — converting high-level conversations (via Meta Ray-Bans) into structured PRDs and Tech SpecsDevPlan — generating detailed, unambiguous coding prompts that eliminate guesswork for agentsTimestamps: 00:00 Introduction: Sam Hesson & Claude Maxing 02:17 The Alpha of 10x Agentic Systems 03:30 The $50k Token Spend & Abundance Mindset 07:25 The Walk Flow: Ray-Bans to PRD/Tech Spec 11:17 AI Adherence to Implementation Patterns 15:21 Playwright & AI Codebase Readiness 17:35 The Darwinian CI/CD: Parallel Agents 21:47 LLM Judge & Rubric-Based Self-Healing 31:03 Bruno API Client: Code-Like Specs 32:47 Self-Healing PRs & Agentic Graph RAG 38:40 DevPlan: Turnkey Structured Prompting 58:43 The Future of SDLC & AI Agent Adoption Resources: Sam Hesson on LinkedIn: linkedin.com/in/samhessenauerNanome.ai (Sam's former company)AI Tinkerers: aitinkerers.orgOne-Shot Podcast: aitinkerers.org/podcastAI Tinkerers One-Shot is a podcast for builders and innovators defining the future of AI — going under the hood with the people actually shipping it.

    54 min
  2. The Architecture of Vibe Coding: Inside Bolt.new's Stack

    JAN 29

    The Architecture of Vibe Coding: Inside Bolt.new's Stack

    In this conversation, Eric Simons, founder and CEO of StackBlitz, walks through one of the fastest and most consequential pivots in modern developer tooling. After nearly seven years building deep browser infrastructure and reaching roughly $700k in ARR, the company reoriented around Bolt, effectively defining the vibe-coding category and scaling past $15M ARR in a matter of months. We go under the hood of the WebAssembly-based architecture that lets Bolt run a full Node.js environment directly in the browser, delivering near-instant feedback and fundamentally different unit economics than cloud-hosted VMs. Eric explains the specific model breakthrough that made full-stack, one-shot app generation viable, and why this moment reordered who actually builds software inside companies. 00:00 Introduction 00:36 The 7-Year History and Pivot Point 01:01 The Original WebAssembly Vision 03:20 Near Bankruptcy: $700k ARR 10:49 Sonnet 3.5: The Vibe Coding Unlock 14:23 The $15 Million ARR Board Meeting 17:19 The Web Container/WASM Advantage 22:07 Bolt Demo: Full-Stack App from a Prompt 31:09 The Changing Role of PMs and Designers 36:23 Mitigating AI-Generated Code Security Risks 47:31 The Entrepreneurial Mindset 53:35 What Eric is Tinkering With Now

    54 min
  3. Inside Browser Automation: Andrew Baker on Agents, Playwright, and Claude Draws

    JAN 16

    Inside Browser Automation: Andrew Baker on Agents, Playwright, and Claude Draws

    In this episode of AI Tinkerers One-Shot, Joe sits down with Andrew Baker—serial builder, former Twilio engineer, and hands-on experimenter in agentic systems—to explore the rapidly evolving frontier of browser automation and AI-driven agents. Andrew shares how his journey began with simple scripting experiments and gradually evolved into sophisticated browser agents capable of handling complex, real-world workflows. One standout example: an airline seat selector that used browser agents to secure optimal seats for frequent flyers—highlighting both the power and the limitations of today’s tooling. Along the way, Andrew breaks down the practical challenges builders face when working with browser agents at scale: • Vision model accuracy and UI interpretation • DOM complexity and brittle page structures • Authentication hurdles and session persistence • The real economics of running large-scale automations The conversation then shifts to “Claude Draws,” Andrew’s playful yet technically impressive side project that brings the classic 90s app Kid Pix into the age of AI. He explains how he wired up a remote PC, streamed sound output, and carefully crafted prompts that allow Anthropic’s browser agent to control a nostalgic art application—brushes, stamps, chaos, and all. The result is both a technical deep dive and a reminder that creativity is often where agentic tooling shines most. Joe and Andrew also zoom out to examine the broader ecosystem shaping the future of browser-native agents. They discuss why UI accessibility matters for agents, how frameworks like Stagehand and Playwright are transforming automation workflows, and why personal evaluation benchmarks are becoming essential for builders pushing these systems beyond demos and into real usage. 💡 Resources & Links Andrew Baker: https://www.linkedin.com/in/andrewtorkbaker AI Tinkerers: https://aitinkerers.org Andrew’s newsletter: https://implausible.ai What you’ll learn • How browser automation evolved from basic scripts to autonomous agents • Why DOM parsing, vision models, and page structure still trip up agents • How Claude for Chrome was used to control a web-based Kid Pix experience • The architecture behind remote execution, sound streaming, and automation hacks • How Stagehand and Playwright support modern browser automation • The technical, economic, and ethical considerations shaping the future of browser agents Chapters 00:00:15 — Introduction and AI Tinkerers Community 02:49 — Twilio Origins and Browser Automation Journey 04:50 — Building the Airline Seat Selector 07:51 — Browser Agent Challenges and Vision Models 10:44 — Stagehand Framework and Browser Automation Stack 13:28 — Claude for Chrome and Authentication 16:58 — Kid Pix Origins and Demo Setup 21:33 — Technical Architecture and Playwright Tricks 29:24 — Evaluation Platform and Personal Benchmarks 37:42 — Future of Browser Agents and Web Economics Subscribe for more conversations with the builders shaping the future of AI, automation, and agentic systems.

    24 min
  4. Scaling AI in the Real World: Lukas Biewald on Tools, Teams & Tinkering

    JAN 5

    Scaling AI in the Real World: Lukas Biewald on Tools, Teams & Tinkering

    What happens when a lifelong tinkerer turns curiosity into two major AI companies? In this episode of AI Tinkerers One Shot, Joe talks with Lukas Biewald—founder of Weights & Biases and CrowdFlower—about how early projects like robot cars and Raspberry Pi experiments shaped his engineering mindset and entrepreneurial path. Chapters: 00:00 — Intro & Guest Background 02:07 — Early Tinkering and CrowdFlower 03:06 — Building Robot Cars and Meeting Pete Warden 08:41 — From Tinkering to Weights & Biases 12:27 — Parenting, Vibe Coding, and Kids as Makers 21:56 — 3D Printing and Creative Play 24:25 — AI Tools, Team Structure, and Company Growth 26:43 — Agentic Coding: Opportunities and Challenges 35:40 — AI in Production: Observability and Real-World Use Cases 49:28 — The Future of AI, Fine-Tuning, and RL https://youtu.be/S84CjOrlMcY

    43 min
  5. Beyond Instructions: How Beads Lets AI Agents Build Like Engineers

    2025-11-26

    Beyond Instructions: How Beads Lets AI Agents Build Like Engineers

    In this episode of AI Tinkerers One-Shot, Joe sits down with Steve Yegge—engineer and creator of the Beads framework—to explore how open source tools are transforming the way we build with AI. Steve shares the story behind Beads, a new framework that gives coding agents memory and task management, enabling them to work longer, smarter, and more autonomously. From his days at Amazon and Google to leading engineering at Sourcegraph, Steve reveals how Beads is already reshaping developer workflows and why it’s gaining hundreds of contributors in just weeks. What you’ll learn: - How Beads gives coding agents “session memory” and lets them manage complex, multi-step projects. - Why Steve believes the future of engineering is about guiding and supervising AI—rather than just writing code. - The evolution from chaotic markdown files to structured, issue-based workflows. - Techniques for multimodal prompting, automated screenshot validation, and “landing the plane” for session cleanup. - The challenges and breakthroughs in deploying AI tools at scale within organizations. - How Beads and similar frameworks are making it easier for both junior and senior developers to thrive in the age of AI. Whether you’re a developer, tinkerer, or just curious about the next wave of AI-assisted coding, this deep dive with Steve Yegge will show you what’s possible now—and what’s coming next. 💡 Resources: Beads – https://github.com/steveyegge/beads Steve Yegge – https://www.linkedin.com/in/steveyegge/ & https://x.com/Steve_Yegge AI Tinkerers – https://aitinkerers.org Subscribe for more conversations with the builders shaping the future of AI and robotics! 00:00 - Introduction to Steve Yegge and Beads Framework 02:10 - Steve's Background and Source Graph AMP 08:00 - Building a React Game Client with AI Agents 15:36 - Multimodal Prompting and Screenshot Validation 23:16 - Code Review Techniques and Agent Confidence 32:01 - The Evolution of Beads: From Markdown Chaos to Issue Tracking 43:11 - Landing the Plane: Automated Session Cleanup 52:09 - Deploying AI Tools in Organizations 58:59 - Code Review Bottlenecks and Graphite Solution 01:02:57 - Closing Thoughts on AI-Assisted Development

    1h 3m
  6. The Future of Home Robotics: Axel Peytavin on Building Robots That Feel Alive

    2025-10-17

    The Future of Home Robotics: Axel Peytavin on Building Robots That Feel Alive

    What if your home robot didn’t just clean, but felt alive — learning, adapting, and becoming part of your family? In this episode of AI Tinkerers One-Shot, Joe talks with Axel Peytavin, Co-founder & CEO of Innate, about his mission to create robots that aren’t just functional, but truly responsive companions. From his early start coding at age 11 to building one of the first GPT-4 Vision-powered robots, Axel shares how his team is creating an open-source robotics kit and one of the first agentic frameworks for robots — giving developers the tools to teach, customize, and build the next generation of embodied AI. What you’ll learn: - Why Axel believes “robots that feel alive” are the future — beyond flashy demos of backflips and kung fu. - How Innate is making robotics accessible with an open-source hardware and SDK platform. - The breakthroughs (and roadblocks) in fine motor manipulation, autonomy, and real-time learning. - How teleoperation, deep learning, and reinforcement learning are shaping the next era of household robots. - Axel’s vision for robots as companions: cleaning, tidying, assisting — and even calling for help in emergencies. Whether you’re a tinkerer, developer, or just curious about how soon robots will fold your laundry, this deep dive shows what’s possible now — and what’s coming next. 💡 Resources: - Innate Robotics – https://innate.bot/ - Axel Peytavin’s Twitter – https://x.com/ax_pey/ - AI Tinkerers – https://aitinkerers.org Subscribe for more conversations with the builders shaping the future of AI and robotics! 0:00 Axel’s mission — building robots that feel alive 00:57 The open-source kit that lets any tinkerer train new behaviors 05:00 Why applied mathematics is the foundation for AI + robotics 08:17 Early projects: Minecraft plugins with 200K+ downloads 11:04 Innate’s vision for teachable household robots 12:01 Why fine-motor manipulation is the real breakthrough, not backflips 15:19 How deep learning is driving rapid robotics progress 17:11 Teleoperation as the engine for data collection and training 23:21 Why tidying up, laundry, and dishes are the killer apps for home robots 32:24 Live teleoperation demo of Maurice in action 36:08 Breaking down the system architecture — Wi-Fi, WebSockets, Python SDK 41:40 Maurice shows delicate fine-motor skills with object pickup 43:53 How Innate built one of the first agentic frameworks for robots 49:50 The rise of an open-source robotics community around Maurice 57:03 Viral GPT-4 Vision robot demo — and what it revealed about the future

    1h 18m
  7. Building GPT-2 in a Spreadsheet — Everything You Wanted to Know About LLMs (But Were Afraid to Ask)

    2025-10-17

    Building GPT-2 in a Spreadsheet — Everything You Wanted to Know About LLMs (But Were Afraid to Ask)

    Learn how to demystify large language models by building GPT-2 from scratch — in a spreadsheet. In this episode, MIT engineer Ishan Anand breaks down the inner workings of transformers in a way that’s visual, interactive, and beginner-friendly, yet deeply technical for experienced builders. What you’ll learn: • How GPT-2 became the architectural foundation for modern LLMs like ChatGPT, Claude, Gemini, and LLaMA. • The three major innovations since GPT-2 — mixture of experts, RoPE (rotary position embeddings), and advances in training — and how they changed AI performance. • A clear explanation of tokenization, attention, and transformer blocks that you can see and manipulate in real time. • How to implement GPT-2’s core in ~600 lines of code and why that understanding makes you a better AI builder. • The role of temperature, top-k, and top-p in controlling model behavior — and how RLHF reshaped the LLM landscape. • Why hands-on experimentation beats theory when learning cutting-edge AI systems. Ishan Anand is an engineer, MIT alum, and prolific AI tinkerer who built a fully functional GPT-2 inside a spreadsheet — making it one of the most accessible ways to learn how LLMs work. His work bridges deep technical insight with practical learning tools for the AI community. Key topics covered: • Step-by-step breakdown of GPT-2 architecture. • Transformer math and attention mechanics explained visually. • How modern LLMs evolved from GPT-2’s original design. • Practical insights for training and fine-tuning models. • Why understanding the “old” models makes you better at using the new ones. This episode of AI Tinkerers One-Shot goes deep under the hood with Ishan to show how LLMs really work — and how you can start building your own. 💡 Resources: • Ishan Anand LinkedIn – https://www.linkedin.com/in/ishananand/ • AI Tinkerers – https://aitinkerers.org • One-Shot Podcast – https://one-shot.aitinkerers.org/ 👍 Like this video if you found it valuable, and subscribe to AI Tinkerers One-Shot for more conversations with innovators building the future of AI!

    1h 16m
  8. From SOP to API in Seconds: Steve Krenzel on Automating Business Logic with AI

    2025-10-17

    From SOP to API in Seconds: Steve Krenzel on Automating Business Logic with AI

    In this episode of AI Tinkerers Global Stage, we go deep with Steve Krenzel, founder of LogicLoop and ex-CTO office at Brex. Steve shows us how his company turns standard operating procedures (SOPs) into fully functioning APIs—complete with schema generation, test cases, structured outputs, and backtesting—within seconds. We break down: 1. Why Steve avoids agentic frameworks 2. How Logic automates 100K+ tasks/month for real customers 3. The power of structured output for reasoning and reliability 4. How prompt caching and append-only templates unlock scale 5. His open-source coding agent that builds software from scratch 6. How they achieved less than 2% error rates beating human teams 7. His famous Prompt Engineering Guide that went viral in 2023 If you’re building with LLMs, designing autonomous workflows, or just want to see what the future of developer productivity looks like—this is a must-watch.

    1h 6m
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About

AI Tinkerers "One-Shot" takes you 1:1 with AI practitioners, software engineers, and tech entrepreneurs around the world -- the best of the AI Tinkerers global network. Each session includes live demos of real AI projects, detailed code walkthroughs, and unscripted discussions led by a technical host who explores practical applications and implementation challenges. As an AI builder, you'll gain actionable insights into emerging tools, techniques, and use cases, plus opportunities to connect with a global network of peers working on similar problems.

Information

  • Creator
    Joe Heitzeberg
  • Years Active
    2025 - 2026
  • Episodes
    34
  • Rating
    Clean
  • Copyright
    © (c) AI Tinkerers, All Rights Reserved
  • Show Website
    AI Tinkerers - "One-Shot"

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