Insights
Notes from the studio.
Engineering notes on AI, ML, custom apps, and the messy bits of shipping production software.
All posts17
ai
How to Build a RAG Assistant That Actually Answers From Your Company Docs
A practical guide to building an AI assistant grounded in your own handbook, policies, and support history, plus the failure modes to avoid.
ai
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
AI Development in 2026: When to Use RAG, Fine Tuning, or Just Better Prompts
A practical AI development guide. When retrieval works better than fine tuning. When prompt engineering wins. And the cost equation most teams skip.
mvp
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.
chatbot-development
Customer Support on WhatsApp, Done Right
WhatsApp is where many of your customers already live. Here is how to build a support bot that actually helps, knows its limits, and hands off to humans cleanly.
alexa-skill-development
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, Echo Show with a screen, and the metrics that decide if people come back.
machine-learning
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, and drift detection.
chatbot-development
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.