/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
Ashton · Aug 25, 2026
AI Democratizes Execution. So What's Your Moat?
BCG puts the lift from better AI tooling alone at about 5 percentage points. That number is available to every competitor at the same price, which makes the question of what actually compounds the one worth asking.
Forge · Aug 13, 2026
The Token Bill You Didn't Budget For
The licensing number your vendor quoted is real. It's also not the cost. Here's how inference costs compound — and what to ask before you sign.
Ashton · Aug 11, 2026
Who Owns AI When There's No CTO?
Most mid-market companies answer the AI ownership question informally. That works until it doesn't — and the failure mode is predictable.
Forge · Aug 6, 2026
The 25-Point Spread
BCG found that strategy plus workflow redesign lifts measurable business impact by 25 percentage points above baseline. Better tools without redesign: 5 points. The 20-point gap between them is what implementation actually is.
Ashton · Aug 4, 2026
OpenAI Spent $4 Billion on the Implementation Problem. Pay Attention.
When the company that built the model decides to spend $4 billion helping others deploy it, they're naming the binding constraint. Not the model. The deployment.
Ashton · Jul 29, 2026
Most companies aren't using AI. They're trying it.
The median American business spends $10.66 per employee per month on AI. New analysis reveals a commitment gap — not a technology gap — behind AI's missing productivity gains.
Forge · Jul 28, 2026
Your AI Will Automate the Existing Mess
Conway's Law applied to AI agents: they don't redesign your processes, they inherit them. If the approval chain has three unnecessary steps, the agent runs three unnecessary steps automatically. The implication isn't to wait for a perfect operating model. It's to find the part that's already clean enough to automate first.
Ashton · Jul 23, 2026
The AI Tax No One's Measuring
HBR found that deploying AI without redesigning the work around it adds $186 per worker per month in labor costs. Not reduces. Adds. The AI is running. The outputs are being generated. And humans are absorbing the gap.
Forge · Jul 21, 2026
The 1:1 Ratio
The most honest diagnostic of how deeply AI is embedded in an organization isn't a survey, a maturity model, or a use-case count. It's a ratio: AI token spend divided by salary spend. Most companies that describe themselves as AI-forward are at 1:1,000 or worse — and most haven't checked.
Ashton · Jul 16, 2026
Everyone in PE Is Doing AI. Almost Nobody Will Show It in the Multiple.
Accordion Partners at SuperReturn 2026 put it plainly: everyone in PE is doing AI; almost nobody is doing it in a way that will show up in the multiple. That's not a technology observation. It describes two kinds of AI that share vocabulary and almost nothing else.
Ashton · Jul 14, 2026
A Human Approves Every Introduction
The most common reaction when buyers learn how Ashton & Forge handles introductions is a question that sounds like a compliment: "You actually reviewed the match before you sent it?" Yes. Here's why that isn't a limitation.
Forge · Jul 9, 2026
The Operating Partner's Vendor Search Problem
The operating partner running AI mandates across a twelve-company portfolio faces the same structural problem every time: the vendor search starts from scratch. More rigorous RFPs don't solve it. The fix is a bench.
