/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 · 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.
Ashton · Jul 7, 2026
The PE AI Moment Is Real. The Execution Infrastructure Isn't.
IBM's May 2026 report on private equity's AI moment is honest in a way most PE-oriented research isn't. It names the value lever correctly: AI is the largest operating margin opportunity available to PE firms during the current hold cycle. The diagnosis of what makes it hard, though, lands in the wrong place.
Forge · Jul 2, 2026
Automation Is Infrastructure, Not the Destination
Most AI transformation roadmaps have a final milestone that reads something like "automate the top five workflows." That's not a destination — it's the foundation layer of a different kind of capability that most companies aren't building toward, because nobody told them it exists.
Ashton · Jun 30, 2026
The Implementation Bottleneck
OpenAI just committed $150M to certify 300,000 implementation consultants. When the most prominent AI company in the world makes that bet, they're naming the binding constraint. It's not the model. It's the people who deploy it.
Ashton · Jun 23, 2026
What WEF Got Right (and Missed) About the AI Moment
The World Economic Forum piece from January 2026 on the AI moment got the important things right. The tools are genuinely more accessible. The cost curves have dropped. The window for first-mover advantage is real. What WEF doesn't name is that accessibility at the tool level isn't the same as accessibility at the engagement level.
Forge · Jun 18, 2026
Five Workflows Most Companies Can Automate in 90 Days
Not every workflow is ready for automation in 90 days. These five are — because they involve structured inputs, well-defined outputs, high frequency, and meaningful time costs.
