Vanishing Gradients
Hugo Bowne-Anderson, Sebastian Raschka, PhD, Hamel Husain, Eleanor Berger, Bryan Bischof, John Berryman, Antaripa Saha, Luca FiaschiEverything you wanted to know about data, ML, and AI, but were too afraid to ask.
| Platform |  | Pricing | Only free issues | Publishes | Twice weekly |
|---|---|---|---|---|---|
| Issues | 89 | Founded | 2 years ago | Last Issue | 5 days ago |
| Active | |||||
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hugobowne.substack.comLatest Issues
The Agentic Software Factory Hierarchy of Needs
Agentic software factories are here
Stripe’s Minions turn engineering requests into candidate pull requests. Ramp’s Inspect puts coding agents to work in the background, with tools to check their changes. Warp Factories takes work from...
Claude’s fraud detector looked excellent. It leaked the answer.
Producing 15 YouTube Shorts used to take me four or five hours. Now agents find potential clips, cut the video, add branding and subtitles, check the renders, and upload drafts. My part is about 20 minutes of choosing moments and reviewing...
Agentic Data Science: Specify the Work, Verify the Claim
When an AI agent can explore a dataset, choose a modeling approach, run the analysis, and explain its findings, what should the data scientist do?
Traditionally, data scientists chose each step and implemented much of the analysis themselv...
Does Your AI Agent Actually Work? A Guide to Evals
You have a collection of documents, so you build a retrieval system. Then you add an agent that can reason over them. The demo looks promising, and the team starts suggesting improvements: a different model, better chunking, more tools.
Bu...
The 6 Most Common AI Agent Mistakes
How to choose where an agent belongs, diagnose what goes wrong, and test whether your changes help.
You have a collection of documents, so you build a retrieval system. Then you add an agent because it can reason over the whole collection....
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Authors
The writers behind this newsletter.
I help teams build with AI. I’m an independent data and AI consultant who’s advised and taught engineers from Netflix, Meta, and Amazon, and written about data science and AI for publications such as Harvard Business Review and VentureBeat.
I'm an LLM research engineer 10+ years of experience in artificial intelligence. My expertise lies in AI & LLM research focusing on code-driven implementations. I am also the author of "Build a Large Language Model From Scratch" (amzn.to/4fqvn0D).
I am a machine learning engineer with over 20 years of experience. More about me @ https://hamel.dev
I lead ai at Theory Ventures.
I was an early product engineer on GitHub Copilot. And I wrote a couple of books! One on Prompt Engineering (https://amzn.to/4gChsFf) and one on Relevant Search (https://amzn.to/3TXmDHk)
ML Engineer working on evals and search.
I advise leaders, build production systems, and scale teams. My work helps businesses grow revenue, improve customer experiences, and run more efficiently.
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