• Your Agent Needs a Dollar Limit, Not a Token Budget

  If you let an autonomous coding agent run in an unbounded loop, I have bad news for you, or rather, your wallet. It happens easily. An agent gets handed a task, runs into an unhandled error or a failing test, and gets stuck in a retry loop. …

• How I Would Build Observability for an Autonomous Agent

  I have not built a full production observability stack for an autonomous agent. I’ve built lots of small wrappers around existing coding harnesses. I have a pretty good idea how quickly their output can turn into a wall of model responses, …

• Your Justfile Is Your Repo's API

  Ask your agent to run the tests in a repo it has never seen before and watch what happens. It’s gonna load so many things into the context to try to figure it out, digging through the repo to find the right command and what framework you’re …

• The Human Job Is Choosing What Not to Build

  Coding agents have made one word much harder to say. No. You describe a feature, and the agent can already see the model, the migration, the command, the tests, and the docs it needs to touch. The whole thing sounds like an afternoon …

• When I Use a Subagent and When I Don't

  Give a good harness access to subagents and everything starts looking like a team project. You’ve got one agent working with the database layer. Another can research the API. Another can write the tests. Another can check the work. Another …

• Where Should This Agent Knowledge Live?

  Every agent has a junk drawer. It usually starts with project instructions. Then I added build commands, personal preferences, database warnings, old architecture decisions, and things to fix later. The agent could see everything if I …

• Not Every Agent Task Needs an Issue

  I’ve written before that your AI agent needs a task manager, and I stand by it. Chat history is not project state. Context windows compact. Sessions end. If the work matters tomorrow, it needs to live somewhere tomorrow’s agent can find it. …

• Tests Are Evidence, Not a Definition of Done

  I’ve watched thousands of tests run over the years. When they pass it has felt good. A huge screen of green checks in the terminal is incredibly rewarding as a software developer. But the work is never finished. The tests are always …

• Every Feature Opens a Maintenance Account

  Coding agents have developed a dangerous little habit. You ask for one change, and somewhere near the end they offer to add three more. Would you like a configuration flag? A JSON output mode? A retry option? Maybe a dashboard while we’re …

• Code Is Cheap Now. Decisions Aren't

  I’ve spent a lot of time working on software backlogs with coding agents. Pick an issue, inspect the code, make the change, run the tests, close it, move to the next one. The strange part is how often writing the code is no longer the hard …

• Pi and Hermes Are Trying to Solve Different Problems

  I went looking for a talk from Mario Zechner, the creator of Pi, because I wanted to understand why someone would build another coding agent when we already have a pile of them. I found: a talk called “Building pi in a World of Slop.” …

• Don't Build a Full Agentic Harness. Wrap One Instead.

  I keep seeing people talk about building an “Agentic OS”. A personal system where agents get tools, memory, sub-agents, long-running tasks, permissions, and maybe a little dashboard with colored dots so you know the robots are thinking. I …

• Your Coding Agent Should Not Own Your Editor

  Every coding agent wants to become the place where you work. It starts life as a command-line tool. Then it grows a chat interface, a diff viewer, a permission system, a terminal, a model picker, and eventually an editor integration. …

• Graphify Turns Your Repos Into a Map You Can Query

  Navigating code dependencies inside a single repository is already hard enough. But if you’re on a microservice setup, or a split frontend and backend, tracking what depends on what across multiple repos is a special kind of misery. A …

• What Are Embeddings, Really? (And Why You Can't Just Use GPT-4 to Make Them)

  If you’ve built a RAG pipeline, a semantic search box, or an AI agent with vector-backed memory, you’ve used embeddings. You probably called a Mistral or Gemini embedding endpoint, took the array of floats that came back, dumped it into …

• Why Your AI Stack Needs a Gateway

  Picture an autonomous agent loop dying at step 45 of a plan it’s been grinding through for the better part of an hour. Not because the plan was wrong. Because OpenAI handed back an HTTP 429 at exactly the wrong moment, and the whole thing …

• Autopilot for Your Docs: A Look at LangChain's OpenWiki

  Writing documentation for a repo is the chore nobody volunteers for. Keeping it current is somehow worse. You refactor one service or change a database schema, and the architecture overview you wrote three months ago is instantly a lie. So …

• Amnesia-Free Agents: GBrain and the LLM Wiki Idea

  Every agent I work with has amnesia. Open a new terminal session, spin up a subagent, start a fresh chat, and the thing forgets everything. Your project guidelines, your coding style, your database schemas, the meeting where you decided why …

• Julia: High-Performance Computing Without the Two-Language Tax

  I hadn’t heard of Julia until someone posted about it on Bluesky. The language was new to me, so I went reading, and this post is a summary of what stood out. Fair warning: I haven’t written any Julia myself yet. The thing Julia is built to …

• Adding Types to JSON with Dhall

  A few months ago I wrote a post asking whether there’s something better than JSON. Two configuration languages that sit above JSON kept coming up: CUE and Dhall. Both give you the things JSON lacks when you author config by hand, and both …

• Building Speech and Thought Bubbles in Svelte

  Have you ever looked at a comic-style speech bubble and thought “that’s just a rounded rectangle with a little triangle”? That’s what I thought too. Then I tried to build one that stays intentional at every size, and I was wrong. Bubble Lab …

• Running Mem0's Memory Backend as Real Infrastructure with Ansible

  Mem0 works best when you treat its memory backend as infrastructure, not as some throwaway process you start by hand and forget about. There are two pieces worth automating early: the vector store and the graph store. Qdrant holds the …

• Geni vs. Goose for lightweight database migrations

  I have a pretty simple rule for database migrations: the tool lets me write SQL, check status, apply the next change, and roll back when I need to. I don’t want much more standing in the way. That’s why I like both Geni and Goose. Neither …

• Embeddings Are Cheap Enough for Personal Wikis Now

  My Obsidian vault is my main second brain: around 1,800 Markdown notes. Lately I’ve been less interested in what to put in it and more interested in a different question: what useful tools could I build on top of it? A few ideas came to …

• Build Your Own Skills Repo

  If you’ve been working with AI coding agents for a while, you’ve probably started collecting workflows. You might not call them that yet, but they’re there. Another name for workflows is Skills. Some are tiny: run these checks before …