What Actually Breaks When You Ship a GPT to Production (And How to Stop It)
5% of production LLM requests fail. Here’s the operational breakdown — prompt drift, rate limits, rollback complexity — and the engineering controls that stop it.
Why Running AI Agent Fleets in Production Is Nothing Like Running a Single Agent
57% of organizations have AI agents in production, but only 2% reach true fleet scale. Here’s what changes — and what breaks — when you go from one agent to many.
From Ideas to Runs: How to Design AI-First Workflows That Actually Execute
Most AI workflows fail not because the model is wrong, but because the workflow was never properly designed. Here’s the end-to-end discipline — from idea validation to production observability — that separates reliable runs from impressive demos.
The Deployment Gap: Why Most AI Workflows Die Between the Notebook and the Network
Only 48% of AI projects reach production. Here’s why they fail and how the fastest teams ship workflows in weeks, not months, in 2026.
The Ops Tax on AI Agents: How to Ship Autonomous Systems Without Wrecking Your Infrastructure
80-88% of AI agents fail in production. Here’s the operational discipline — blast radius, budget governance, observability, and circuit breakers — that separates teams who ship durably from those who don’t.