Vanishing Gradients
de Hugo Bowne-Anderson
Episódio mais recente
The Science and Engineering of Agent Work
The Science and Engineering of Agent Work
Sobre este podcast
A podcast for people who build with AI. Long-format conversations with people shaping the field about agents, evals, multimodal systems, data infrastructure, and the tools behind them. Guests include Jeremy Howard (fast.ai), Hamel Husain (Parlance Labs), Shreya Shankar (UC Berkeley), Wes McKinney (creator of pandas), Samuel Colvin (Pydantic) and more.
hugobowne.substack.com
Episódios
Os 20 episódios mais recentes de 86
- The Science and Engineering of Agent Work · 2 h 22 minHilary Mason, CEO of Hidden Door, works with agents across software development and creative projects. Drawing on Richard Hamming’s distinction between science and engineering…
- The State of Agentic Data Science · 59 minAgents can write the code, run the analysis, and produce a convincing explanation. How do you check that they’ve answered the right question, used the data appropriately, and…
- How to Build a Coding Agent with Nico (Amp Code) · 1 h 52 min“It’s an LLM, a loop, and enough tokens.” —Nicolay Gerold, Amp Code So why does a coding agent forget your instructions, keep reading tiny pieces of a file, or struggle with an…
- The Rise of the AI Scientist · 1 h 10 min“If you feel that a product is hard to eval, or you feel like, ‘I don’t even know how to eval this,’ it’s a strong smell that your product isn’t good.” — Hamel Husain, on AI…
- If Developers Build on Chinese Open-Weight Models, Who Leads AI? · 1 h 18 min“It would be sad if local models were not an option and there were only proprietary models. It’s good to have alternatives. Competition is good for business.” — Sebastian…
- Four Months Inside a Production AI Agent: What Real Users Changed · 1 h 4 minWhen ML/AI Engineer William Horton last joined me, Maven Assistant had reached its first external users the day before. The healthcare AI agent was available to 20 percent of…
- Building an Enterprise AI Agent for Healthcare · 1 h 8 minEvery capability in an agent needs its own evidence and release bar. A model-provider slip, an incorrect tool call, and a wrong fertility-benefits answer should not be held to…
- What Claude Fable Means for Coding Agents · 1 h 2 minNicolay Gerold works all day and night on AMP, one of the most interesting coding-agent harnesses out there. If you’re building with coding agents, this conversation will help…
- The Future of Agentic Data Science · 1 h 4 minSo I think we’re really at a historical moment, and the opportunity is massive. Almost 15 years ago, we were promised that data science was going to be this incredible thing and…
- Agent-Harness.ipynb* · 1 h 19 minOne thing that I don’t like about Claude is that you get into this weird mental state: oh, I think I trust the model. Let’s do the slot machine. Hit click, which puts you in an…
- Agentic Engineering and the Lost Art of Verification · 1 h 32 min> I almost don’t read code now. My approach with Roborev is it’s like my code reader. The mantra is: Roborev reads every line of code that is generated. It gets read multiple…
- Next Level AI Evals for 2026 · 54 minThere are a lot of reasons why we should do AI evals. For many companies doing AI evals is the way to build the feedback loop into the product development lifecycle. So it is…
- Privacy Theater Is Not Privacy Engineering: What It Actually Takes to Ship Safe AI · 1 h 6 minKatharine Jarmul, Privacy in ML/AI Expert & Author of Practical Data Privacy, joins Hugo to unpack why most AI privacy advice is theater: and what technical privacy actually…
- LLM Architecture in 2026: What You Need to Know with Sebastian Raschka · 1 h 18 minIf you take a model release as an anchor point, let’s say Nemotron 3 or Qwen 3.5, you can go in both directions: You can either plug them into an agent and play around with that…
- Episode 72: Why Agents Solve the Wrong Problem (and What Data Scientists Do Instead) · 1 h 33 minI often see what I would consider to be b******t evals, especially in data, like write this dumb SQL. Almost every one of these dumb SQL questions that I’ve seen for benchmarks…
- Episode 71: Durable Agents - How to Build AI Systems That Survive a Crash with Samuel Colvin · 51 minOur thesis is that AI is still just engineering… those people who tell us for fun and profit, that somehow AI is so, so profound, so new, so different from anything that’s gone…
- Episode 70: 1,400 Production AI Deployments · 1 h 9 minThere’s a company who spent almost $50,000 because an agent went into an infinite loop and they forgot about it for a month. It had no failures and I guess no one was monitoring…
- Episode 69: Python is Dead. Long Live Python! With the Creators of pandas & Parquet · 55 min> It’s the agent writing the code. And it’s the development loop of writing the code, building testing, write the code, build test and iterating. And so I do think we’ll see for…
- Episode 68: A Builder’s Guide to Agentic Search & Retrieval with Doug Turnbull & John Berryman · 1 h 28 minThe best way to build a horrible search product? Don’t ever measure anything against what a user wants. Search veterans Doug Turnbull (Led Search at Reddit + Shopify; Wrote…
- Episode 67: Saving Hundreds of Hours of Dev Time with AI Agents That Learn · 1 h 18 min This is continual learning, right? Everyone has been talking about continual learning as the next challenge in AI. Actually, it’s solved. Just tell it to keep some notes…
