How I Made Codex Subagents Measurable and Recoverable
How I rebuilt my Codex subagent setup around reliable browser control, bounded work, recoverable handoffs, and honest token measurement.
Rajeev Gill
I build practical software around AI, data, analytics, and adtech.
My work sits between product thinking and implementation, with a bias toward systems that make real work less messy.
Based in London. Interested in useful AI, clearer measurement, and software that holds up outside a demo.
Get in touchSelected projects
Things I have built
Research product
Open GTM Index
A transparent guide to open-source sales and marketing software.
TanStack StartReact 19TypeScript
AI research product
Local LLM Lab
A measured guide to every local AI model installed on my Apple Silicon workstation.
PythonReactVite
Operations product
Hackathon Voting App
A production-ready single-screen judging app built for a live hackathon room.
Next.js 14TypeScriptClerk
Recent writing
Notes from the work
The AI Work System I Built After 551 Codex Sessions
I spent weeks recording how an AI assistant worked on my computer. The real lesson was not about cleverness. It was about repeating myself, checking work it said was finished, and finding a simpler way to work together.
I Gave My AI a Team. Here Is What Happened to the Expensive Work.
A plain-English look at how I split Codex work between an OpenAI lead and lower-cost OpenRouter specialists, what the evidence shows, and what it does not.
Have something useful to build?
I am always interested in thoughtful software, analytics, and AI work where the practical details matter.
Email me