Shell scripts are the highest-ROI layer under your AI skills
The glamorous layer is the agent. The load-bearing one is the boring shell script underneath — and that's where most of your reliability actually lives.
Aug 10, 20266 min read1
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Deterministic context beats generated context — when structure exists
The prompt is only about 10% of what your LLM actually sees. Most of the other 90% is context you assemble — and when your data has structure, you should build it with code, not another LLM call.
Aug 6, 202612 min read15I stopped being my second brain's scheduler
Cadences that surface what's due, habits that flag a slipping streak, and a live HUD that watches the vault — and it ships without a single background cron. SMRITI v2.1.
Aug 2, 202610 min read49
Building Production RAG on ArXiv — Part 1: Architecture & Ingestion
I'm building an open-source system to interrogate the AI-research firehose — RAG now, a multi-agent researcher by the end, in public over five parts. Part 1 is the foundation: the architecture, the ingestion, and the eval bug that would have shipped meaningless numbers.
Jul 30, 202618 min read17Sub-Agents Lie About Finishing — and the Fix Isn't a Better Prompt
A sub-agent that writes to your system will tell you it succeeded. It's reporting what it intended to do, not what actually landed — and the gap is where silent data corruption lives.
Jul 15, 20266 min read3Parallel Sub-Agents Change How You Plan, Not Just How You Build
You can plan a day around what you can do, or around what you can decide. Until recently those were the same plan, so it never mattered which you meant. Parallel sub-agents pull them apart — and the i
Jul 11, 20266 min read12AI's Value Compounds at the Task Layer, Not the Model Layer
When a team sets out to add AI to something, the first real argument is usually about the model. Which provider, which version, this one or the one shipping next month. It feels like the decision ever
Jul 8, 20266 min read7Route to the Cheapest Oracle That Can Decide
When you build on top of a language model, routing every decision to the model is the path of least resistance. One interface, one prompt, one place to add logic. It works beautifully in a demo. Then
Jul 1, 20267 min read18What a developer survey taught me after 6 weeks of AI code review
Six weeks into running AI-assisted architect code reviews, I did something I should have done earlier: I asked the team directly. I'd been running a pipeline that scanned pull requests, generated arch
Jun 26, 20267 min read29