Articles
Long-form, interactive
Deeper pieces that don't fit a Medium post — built as standalone interactive pages. For shorter posts, see Medium.
Get new articles by email
No spam, just a short note whenever I publish something new. Unsubscribe anytime by replying.
Building a Grounded Chatbot for My Portfolio
How the "Ask Anupam's AI" widget works: a build-time chunk index over the whole site, dependency-free BM25 retrieval (no embeddings API), page-aware boosting, Groq-then-Gemini streaming over SSE, the guardrails that keep it from inventing facts, and three real incidents from the week it went live.
Your AI Assistant Can Query My Portfolio
A public, read-only Model Context Protocol server for this site: the 8 tools it exposes, why it targets protocol version 2025-06-18 instead of the newest one, why it's hand-rolled JSON-RPC instead of the official SDK on a serverless route, and how to connect Claude, Claude Code, Cursor, or curl to it.
Taming the Dice
The complete field guide to LLM reliability, written for everyone from zero background to production. How language models actually work, why the same prompt gives different answers even at temperature 0 (including the 2025 batch-invariance finding), temperature vs top_p vs top_k defined with worked numbers, what seed and system_fingerprint really buy you, model-agnostic prompt engineering, structured outputs and constrained decoding, how to test any of it, and a tour of every other way these systems bite in production. Seven diagrams, thirty-one cited sources.
Why Your RAG Pipeline Is Confidently Wrong
The failure modes that never show up in a demo - silent retrieval misses, semantic near-misses, stale embeddings, citation-answer mismatch - why "it worked in testing" is a trap without a retrieval trace, and a concrete reliability playbook from two production RAG systems.
Same Prompt, Different Answer
Why LLM output determinism is a legal problem, what Azure OpenAI's seed and system_fingerprint actually guarantee (less than you'd hope), why AWS Bedrock has no equivalent for text models, a practical audit-logging playbook, and an honest opinion on building on something that's fundamentally guessing the next word. Scrollable field notes with real vendor docs cited.
The War of the Agents: Mid-2026 Check-in
A deep dive into GPT-5.6 Sol Ultra, Claude 5 Fable/Mythos, and Gemini 3.1. We look past the heavily gamed Terminal-Bench 2.1 scores to see what these frontier models actually mean for everyday developers, and why the community is pushing back on "safety-gated" reasoning capabilities.
The Everyday AI Playbook
How to make AI save you real hours - whether you're a student, a doctor, a researcher, running a business, or just getting through your to-do list. A developer's field guide to the durable habits behind good AI use: the right mindset, per-track use cases, the two skills that decide whether any of it works, and how to stay out of the trap where AI quietly costs you more than it saves. Scrollable, illustrated guide.
Maximum Output with Claude Code
A field guide to running AI like a system, not a chat box - persistent context, a research-first planning gate, controlled execution with subagents, and the two human checkpoints that catch what automation can't. Scrollable, illustrated walkthrough.