#llm
5 posts
How to design a responsible AI companion app
Practical rules for a responsible AI companion app: say it is an AI, skip engagement hooks, handle crisis moments, and give people control of memory.
Building a Hinglish AI chatbot: lessons for India
How to build a Hinglish AI chatbot people enjoy: match the user's register, handle Roman and Devanagari script, test code-mixed prompts and watch cost.
Routing between LLM providers to balance cost and quality
Why we route requests across more than one model provider, how prompt caching cuts repeat costs, and why routing changes pass offline evals first.
Designing AI memory that stays accurate
Long-term memory for an AI companion is about keeping facts current, not storing more. Recall, supersession, and why contradictions cost trust.
LLM evals for small teams: a practical starting point
How to build LLM evals with a small team: start from real failures, use pass/fail checks, calibrate an LLM judge and gate every prompt change.