Field notes from shipping AI
No thought leadership, no hype cycles — practical writing from engineers who build AI products for a living.
Self-Healing AI Agents in Production: Lessons from a Real Deployment
What it actually takes to run a closed-loop generate–test–diagnose–repair agent in production: architecture lessons, real numbers, and when not to build one.
How Much Does an AI MVP Cost in 2026? (Real Numbers)
Real cost ranges by complexity tier, what actually drives AI development budgets, hidden costs founders miss, and how to cut cost without cutting quality.
From Idea to AI MVP in 30 Days: Our Exact Process
The week-by-week process we run on every AI MVP: thin-slice prototyping, eval-first development, and the deliberate cuts that keep 30 days honest.
RAG vs Fine-Tuning: Which Does Your Product Actually Need?
A decision framework for the most common AI architecture question — with the misconceptions cleared up and a real production example.
7 AI Product Mistakes That Kill Startups Before Launch
The seven failure patterns we see most in AI startups — from demo-driven development to ignored inference costs — and the concrete fix for each.
Hiring Dedicated AI Engineers vs Building In-House: Total Cost Breakdown
The true year-one cost of a US AI hire versus a dedicated engineer model — with an honest look at when each option actually wins.
How to Write an AI Product Spec That Developers Can Actually Build
The seven sections of a buildable AI spec, a complete worked example, and how a tight spec changes the quotes you get from agencies.
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