/Field Notes Blog
Notes from the forge.
On AI strategy, implementation, and the distance between a pilot and a system that ships. Written by the people who vet the work.
/The archive
Forge · Jun 2, 2026
The Workforce Framing Is Right. It Skips the First Question.
BCG's March 2026 piece on AI and workforce transformation is correct about the destination. AI transformation does restructure how human and machine work divide. The problem is sequencing. BCG's framing implies that workforce transformation is the starting condition. It's actually the outcome.
Forge · May 29, 2026
Do I Need a Data Scientist to Do This?
For most first AI deployments at mid-market scale, you don't need a data scientist. You need a different kind of expertise. Knowing which is which prevents expensive hiring decisions that don't solve the actual problem.
Forge · May 26, 2026
What a Workflow Audit Actually Produces
"We do a workflow audit" is the most common thing AI agencies say and the least often explained. Here is exactly what a real one produces — so you can tell the difference.
Ashton · May 19, 2026
The 5% Problem
BCG's Widening Gap study buried the most important number in the executive summary: 5% of companies are generating meaningful EBIT impact from AI. Not 40%, not 25%. Five percent. The question isn't why AI isn't working. It's what those five percent are doing differently.
Ashton · May 15, 2026
What's the Difference Between ChatGPT and an AI Deployment?
ChatGPT and a production AI deployment share underlying technology and almost nothing else. The distinction matters because one produces individual productivity uplift and the other produces structural organizational change.
Forge · May 12, 2026
The AI You're Already Paying For
If you're on a paid tier of Salesforce, HubSpot, or ServiceNow, there's a reasonable chance you're already paying for AI agents that haven't been turned on. The gap isn't reluctance. It's friction.
Ashton · May 5, 2026
The Compounding Gap
The companies that started 18 months ago aren't 18 months ahead of you. They're multiple capability iterations ahead — and the gap compounds in a way that time alone won't close.
Forge · May 1, 2026
What Is AI Currently Bad At?
Knowing what AI is bad at is as important as knowing what it's good at — because the expensive failures happen when buyers overestimate AI's current capabilities and deploy it where it reliably fails.
Forge · Apr 28, 2026
When Production AI Agents Die
Most production AI agents don't die at launch. They die between month two and month six. The launch is usually fine. Then, sometime in the next few months, the agent degrades. Outputs drift. Someone stops checking them. By month six, the agent is technically still running and effectively unused.
Ashton · Apr 21, 2026
The CEO Who Got Religion
There's a recognizable moment when a skeptic becomes a convert. The mandate becomes real, the urgency is genuine — and almost everything that happens next is wrong.
Ashton · Apr 17, 2026
Can I Really Trust the AI?
The question isn't really "can I trust AI" — it's what is AI trustworthy for, what isn't it, and how do you build the right guardrails for each. The answer to trust is architecture, not faith.
Forge · Apr 14, 2026
Discovery vs. Brief: Two Agency Models and How to Choose
The most common source of failed AI agency engagements isn't a bad agency. It's hiring the wrong type. Two fundamentally different models exist, and most buyers don't know they're choosing between them.
