Notes from the studio.
Engineering notes on AI, ML, custom apps, and the messy bits of shipping production software.
Building Neutral AI: How We Ship Production Systems Without the Hype
Hype-free engineering principles for AI products that serve users, not nudge them. Grounding, refusal, evals, cost-bounding — the boring decisions that actually ship.
AI Development in 2026: When to Use RAG, Fine-Tuning, or Just Better Prompts
A practical AI development guide — when retrieval-augmented generation beats fine-tuning, when prompt engineering wins, and the cost equation most teams skip.
Custom App MVP Development: What 4 Weeks Actually Buys You
What you can realistically ship in a 4-week custom app MVP — features, tradeoffs, and the timeline traps that kill startups.
Alexa Skill Development: A Production Guide for 2026
How to build an Alexa skill that gets certified and used. Voice UX rules, AWS Lambda backend, multi-modal Echo Show, and the metrics that decide retention.
Machine Learning in Production: Beyond the Jupyter Notebook
A working model is not a working product. The full production ML stack — data pipelines, deployment patterns, monitoring, drift detection.
Chatbot Development: Why Most Bots Fail (and How to Build One That Does Not)
The chatbot engineering decisions that decide success — log-driven intent design, the human handoff feature, channel-specific behavior, and metrics that matter.