Every post comes from something I've done on a real project. AI tools, development approaches, how I actually build things. You're getting a curation of my taste, not takes on stuff I don't use. Subscribers also get extras: things that went wrong, how my thinking about AI is changing, hacky workflows I use every day, and the occasional personal update. Stuff I share with subscribers because it's a little too personal or unpolished to blast across the internet.
two ai workflows. 1 practical, 1 experimental
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Hey this is Isaac, Here are a couple demos of things I thought were cool. Then an update on a new project i'm working on with Hamel Husain. First, I’ve been working on Raw2Draft (my writing tool). I just added D3 diagrams to markdown and html text editing and I use one or the other most working hours. D3 is a low level visualization library that gives maximum flexibility but is very painful to write. But agents write D3 surprisingly well and it's amazing for adding visuals to help with clarity and thinking through a problem.
Second, the experiment. I’m working on an agent memory system backed by Anki (spaced repetition flashcards). I want a memory system where I learn alongside my agents. When the agent finds a useful pattern, correction, or gap in my understanding, that can become a card I review later instead of disappearing i nto the chat transcript. This gives me something to study, provides memory of that to my agent, and creates a clear review surface.
I’ll keep sharing personal experiments like this publicly. But as anyone building AI products knows, getting from experiment to a reliable and desirable production tool is much harder. To help builders actually solve those gaps, most of my time is shifting from SpecStory to a paid community (the Advanced AI Engineering Club) I’m running with Hamel Husain. Inside the community, Hamel and I will be doing weekly deep dives on topics like retrieval, memory, evals, and agents with real prod architectures. We'll also do operator reviews where members bring their product, evals, and logs to get blunt, tactical feedback on where reliability will break. For example last week the founder of Ankihub showed the product, evals, and current focus and we diagnosed his bottlenecks relating to annotator alignment and query disambiguation live with the community. This means I can focus completely on creating the most complete walkthroughs, live builds, and direct feedback (the first community deep dive is tomorrow!). If that is useful for what you’re building, you can see more details here. If you’re here for the public writing, keep reading. I’ll still be here. p.s. We'll be doing a free public talks as a sample of kind of deep dives we'll do weekly in the community. Hope to see you in the Tool Architectures (1500+ signup already) one or the Better RAG with Late Interaction one. Otherwise here's a sample of some of the topics we'll cover in the community, tough we will adapt based on what problems members are facing in practice. Thanks, Isaac |
Isaac Flath
Every post comes from something I've done on a real project. AI tools, development approaches, how I actually build things. You're getting a curation of my taste, not takes on stuff I don't use. Subscribers also get extras: things that went wrong, how my thinking about AI is changing, hacky workflows I use every day, and the occasional personal update. Stuff I share with subscribers because it's a little too personal or unpolished to blast across the internet.
Hey this is Isaac, Hamel Husain and I are doing a free public talk on why better RAG starts with late interaction. Most RAG still follows the "embed the chunks, embed the query, compare the vectors” approach. But top retrieval architectures follow a new approach. People do not upgrade because it requires a different setup and they think it’s only an incremental improvement. Companies like Nvidia, AWS, and Cursor have adopted it because it’s a big step up. It’s not just benchmark games. A...
Hey this is Isaac, Hamel Husain and I are doing a free public talk on tool architecture anti-patterns for agents: MCP, skills, CLIs, plugins, and custom tools. Some of the most popular and widely used skills, CLIs, and mcp’s fall into one of these anti-patterns. Is MCP good? Are skills enough? Should this be a CLI? That is the wrong starting point. A tool call is a product surface and should be created with the same care given to any other user facing page. When it’s treated like plumbing to...
Today's post is about a project that I will take concepts from to improve my own work. So I studied the OSS prototype of it to understand how it works. Point and Talk: How Clicky’s AI Interface Works Clicky is an AI buddy made by Farza that lives on your Mac. You press a key, talk, and a glowing blue triangle flies across your screen, points at whatever you asked about, and talks you through the answer. Most apps with an agent should have something like this. Point and talk is closer to how...