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The AI Engineering Playbook
Practical thinking about AI engineering, building production systems, and making dev teams better with AI. No hype. No jargon walls. Just useful ideas from the work we do every day.
Your AI Is Live. Now What? A Field Guide to LLM Observability
89% of teams with agents in production have observability set up. Only 52% run evals. Here's why that gap is a problem, and what the full stack actually looks like.
12 min read
How to Measure AI ROI Without Lying to Yourself
49% of organizations can't demonstrate the value of their AI investments. The problem isn't the AI. It's how they're measuring it.
10 min read
The Model Price Collapse: What to Build Now That You Couldn't Six Months Ago
Frontier models just got 67% cheaper. Here's what that actually means for the economics of building with AI.
8 min read
Which AI Agent Framework Should You Actually Use?
LangGraph, CrewAI, AutoGen, and the OpenAI Agents SDK are all fighting for the same territory. An honest breakdown of which one ships and which is still demo-ware.
10 min read
Your Dev Team Is Using AI Tools Wrong
Every developer has AI tools. Most teams get wildly inconsistent results. The problem isn't the tools. It's the lack of structure around them.
10 min read
Understanding MCP: The Protocol Changing AI Integration
Model Context Protocol is redefining how AI agents interact with tools and data sources. A practical introduction for engineering leaders.
10 min read
From Pilot to Production: Why 82% of AI Projects Fail
The gap between a working demo and a production system is where most AI initiatives die. Here's what separates the 18% that make it.
12 min read
Is Your Business Ready for AI Agents?
A practical framework for evaluating whether your organization is ready to deploy autonomous AI agents, and what to do if you're not there yet.
8 min readHave a question about AI?
Whether something here sparked an idea or you're working through an AI challenge, we're always happy to talk it through.