The companies pulling away in the AI race right now aren't necessarily choosing better models — though I'd wager that's fast becoming its own unique debate. Orgs and their teams are learning faster, which is a different beast entirely.

I've started looking at Forward Deployed Engineering less as a software discipline and more as an educational one. The code and infrastructure matter, but none of it changes an organization until people begin making different decisions on account of its being there.

Education Is the Deployment infographic, Forward Deployed Field Notes No. 001. Technology is easy to buy, hard to embed. A flowchart runs from AI models, where intelligence is available and potential is not the problem, through the forward deployed engineer, part engineer, part educator, part translator, out into education, governance, and workflows, and lands on the organization: a new operating rhythm, better decisions, sharper questions, AI as a capable member of the team. Margin notes read: the hard part isn't the model, it's the system around it; good deployments don't end with software, they end with transformation. Real adoption happens when the technology fades into the background and the team moves faster. The exhausted Island Mountain mascot takes a break on top of the workflow.
Forward Deployed Field Notes, No. 001: the whole argument, one flowchart.

I'm watching teams in 2026 spend six months evaluating models when the bottleneck hasn't historically been the model. (Again, that debate is morphing in real time.) It's ownership and buy-in coupled with trust and decision-making. Teams are starting to blur the line where humans stop and the machine starts.

Buying intelligence is easy — a tad spendy. It's integration into a daily organizational rhythm that's the hard part.

It's why I love this work and this moment in time.

A good deployment leaves behind a team approaching the work in front of them in a fundamentally different way. The technology kind of fades into the background, enabling faster decisions. Questions are refined as people start treating AI like another capable member of the team.

We're entering a chapter where organizational AI-wired education's the biggest competitive advantage at the enterprise level.

To be clear, I'm talking about more than a prompt workshop or a lunch-and-learn. This is whole-organization education; teaching a company how to think with a new tool.

That's the squeeze-worthy juice I'm talking about.

Sidenote: the exhausted icon taking a break on the workflow will be an Island Mountain signature to look for from now on.

Summary: The organizations pulling ahead with AI aren't the ones choosing marginally better models; they're the ones learning faster. Forward Deployed Engineering is as much an educational discipline as a software one — the code and infrastructure matter, but nothing changes until people make different decisions because the system is there. Buying intelligence is easy; integrating it into a daily organizational rhythm is the hard part. A good deployment leaves behind a team that works in a fundamentally different way, with the technology fading into the background and AI treated like another capable member of the team. Whole-organization AI education — not a prompt workshop, not a lunch-and-learn — is becoming the biggest competitive advantage at the enterprise level.