Productivity

Everything starts great. You give your AI agent instructions, it follows them to the letter. You define policies, it complies. You pass it work protocols, it executes them. It is fast, precise, and never complains. Until one day it stops. No error. No warning. It simply ignores rules it used to follow. It makes stupid mistakes. It repeats questions you already answered. What changed? The answer is the context window — we get into the work and stop paying enough attention to it. ...

On March 31, 2026, the Claude Code source code was briefly exposed. A Korean developer named Sigrid Jin made a clean-room port to Python and Rust before Anthropic took it down. The claw-code repository does not contain the original code, but it does include snapshots, subsystem metadata, and a partial runtime port that reveals how Claude Code works under the hood. Understanding how your tool works lets you use it better, so it was worth digging into it thoroughly. For obvious reasons it would take me several years to review every line of code, but that is what Jarvis is for — he got to work and abstracted away the first 50K hours of effort for me ;-) ...

There is a lot of noise about AI and programming. Copilots, autocomplete, code generators… Most tools stop at suggesting the next line. But you can do something different, something more: work with an AI agent that operates as another developer on the team. My digital teammate is called Jarvis. It has its own GitHub account, its own Jira access, and a workflow identical to any human developer: branch, implementation, commit, pull request, code review. I have been running this system in production for months, and this is what I have learned. ...