16 posts across articles, notes and newsletter issues.
The site you are reading this on just shipped. It has its own MCP server, which means an agent can draft posts here directly, review queue included. Plus agent-memory-server went open source.
I run several coding agents that share one durable memory made of markdown, JSON and git commits. Here is why plain files beat a vector store, and how sessions, leases and decisions work.
A short note on a naming habit from the mutexai.net assistant. Read-only tools get plain verbs. Anything that writes gets a verb that says so, on purpose, so a reviewer never has to guess.
Three agents on one checkout means trampled files and lost work. Giving each task its own git worktree, its own model and a deterministic merge step fixed that for me.
Happy-path demos tell you nothing about what an agent does when a tool returns a 500. I test agents like distributed systems: inject faults on purpose and score recovery against bluffing.
Clone, install, run the tests, then separate real regressions from environmental noise. Why I built repo-doctor as a deterministic pipeline first and an agent second.
A short note from building cron-for-agents. The first version kept its watermark in memory, a restart erased it, and an agent reprocessed a week of old data. State belongs on disk.
Plain cron runs your agent on time, then wastes tokens reprocessing old data and spams you with identical summaries. Watermarks and content-hash dedup fix both.
Two months of unglamorous infrastructure. A cron tool that does not spam duplicate summaries, sandbox M-Pesa tools for agents, and the start of a proper way to test how agents fail.
What MCP is, why payments are the hardest tools to give an agent, and how I am designing Daraja tools around sandbox defaults, idempotency keys, reconciliation and human approval.
Worktrees do not disappear when an agent's task ends. A short note on the cleanup step I almost skipped while building worktree-orchestrator, and the disk space and confusion it saves.
How I built the assistant on mutexai.net with Laravel's HTTP client: a bounded tool-use loop, a daily spend cap, a local fallback that always answers, and a human-reviewed learning queue.
