AI Tinkerers - "One-Shot"

Joe Heitzeberg

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. 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
  2. Beyond Instructions: How Beads Lets AI Agents Build Like Engineers

    11/26/2025

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

    10/17/2025

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

    10/17/2025

    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
  5. From Viral AI Demos to YC: Robert Lukoszko

    10/17/2025

    From Viral AI Demos to YC: Robert Lukoszko

    Discover how Robert Lukoszko, CEO of Stormy AI, is building the future of AI-powered marketing by automating influencer outreach end-to-end. This interview goes deep into his journey from viral AI demos to Y Combinator, revealing critical insights for AI builders and founders. You’ll learn: • The surprising challenges and limitations of building AI applications that deeply integrate with operating systems. • Why local AI models, despite their appeal, often struggle to compete with cloud-based solutions for real-world business cases. • Robert’s unique approach to AI-assisted development, leveraging tools like Claude 3.7 for rapid prototyping and efficient coding. • How Stormy AI uses advanced AI to find niche influencers, analyze engagement, and automate outreach, transforming traditional marketing. • The strategic importance of distribution and market fit over pure technological innovation for venture-scale AI companies. Robert Lukoszko, previously co-founder of Fixkey AI (acquired) and an alumnus of Y Combinator (S24 with Stormy AI, W22 with ngrow.ai), shares his extensive experience in applying AI to new modalities and building high-growth startups. This episode of AI Tinkerers One-Shot offers a practical look at the technical and entrepreneurial realities of building in the generative AI space. 💡 Resources: • Stormy AI - https://stormy.ai • Robert Lukoszko’s LinkedIn - linkedin.com/in/robert-lukoszko • AI Tinkerers - https://aitinkerers.org • One-Shot Podcast - https://one-shot.aitinkerers.org/ Social Media: @AITinkerers @stormy_hq @Karmedge 👍 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! 00:00 – Introduction & Background 02:38 – Visual AI, Demos & Startup Idea 06:27 – Local vs. Cloud Models 10:07 – Desktop AI App & Context Importance 14:11 – Building the App & OS Integration 23:13 – Ambient AI & Contextual Vision 32:17 – Stormy AI Pivot & Demo 38:35 – AI Mindset & Content Creation 43:57 – AI Model Comparison & Cost

    56 min

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.