Insights
Field notes on the operational reality of production AI
The model was never the hard part. This is where we write about everything after it: what breaks in production, what a reliable agent actually requires, and what to fix before an AI project starts.
Category
What Is Forward-Deployed Engineering?
The delivery model behind this practice: engineers embedded in your codebase, shipping the system itself instead of a recommendation.
Production
Why AI Pilots Die in Production
Where the gap between a working demo and a production system actually opens up, and what a pilot has to prove before it scales.
Reliability
Harness Engineering: How to Make AI Agents Reliable
Evals, guardrails, tool contracts, and observability — the enforcement surfaces that make an agent reliable, not the prompt wording.
Engineering
Prompt Engineering Is the Smallest Part of the Work
Context, data, and evaluation engineering do more for reliability than the prompt ever will. Here’s where the effort should actually go.
Data
Data Readiness Before AI: What to Fix First
The data problems that quietly block AI systems, and a practical way to check readiness before a pilot starts.
Strategy
Build vs. Buy: The Honest AI Decision Framework
What each path actually costs, when each one wins, and how to avoid the expensive failure mode of doing both badly.
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