The Remote Forward Deployed Engineer

This is a little early. It is also more relevant than most people want to admit.

Wearables are already teaching robots how humans do a job. Picture someone at a laundromat with a camera on a hat. It watches how they fold, how they run the machines, how they work the register, how they restock detergent, how they close the place down. Over enough days that footage becomes a pattern. The pattern becomes training data. The training data becomes a machine that can run more of that shop than you are comfortable admitting out loud.

That same curve is coming for desk work. Systems analysts. Researchers. Marketers who live in rote sequences. SDRs hunting leads through inbound and outbound loops. Spreadsheet people. Data people. Anyone whose week is mostly coordination, chase, and carefully repeated judgment. A lot of that is going to get automated with AI agents. The question is not whether the doom headline shows up. The question is what you do in the months before it does.

The job that shows up when the old one thins out

I call it the remote forward deployed engineer.

Not “engineer” as in write compilers from scratch. Engineer as in the person who takes a real skill they already earned in the wild — five or ten years in a domain — and turns that skill into something an AI agent can learn from fast. You are not competing with the model on raw speed. You lose that fight. You win on taste, nuance, and the ugly edge cases that only show up after you have lived inside the work.

The people who get replaced and sit still will feel doom. The people who get replaced and dump their brain into an agent-friendly form will feel boom. Same pressure. Different move.

Automate your knowledge while you still have the job

If you think your role might thin out in the next few years, start now. Not with a panic course titled “learn Python in a weekend.” Start with your core competency.

Use AI to build a second brain online. Map what you actually do. Draw the connections. Write down the conclusions you make without thinking. Then look for ways to monetize that map:

• A skill an agent can load when it needs your kind of spreadsheet taste
• A small library of skills around data analysis or research hygiene
• A short course that is agent-friendly — structured so a model (or an agent watching the course) can pick up the job faster than cold-start training
• Even a thin platform that packages your domain judgment for other teams

You are duplicating what used to live only in your head and only in your manual week. You are packaging it so an agent can do the grind, while a human still owns the exceptions and the taste.

That package is the product.

Why companies will pay for you from anywhere

Companies are still dependent on humans. When they say “let’s put an AI agent on this,” there is a learning curve. Rough ranges I see today — illustrative, not a case study:

• About a week for something basic like inbox triage
• Two to three weeks for research and analysis loops
• Two to three months before customer service feels “as good as an agent can do today” without real human touch

In that gap sits the accelerator: a human who already knows the domain, who fine-tunes the agent through its training and early live runs, who corrects the dumb misses, who tightens the prompts and the skills and the escalation rules. You shrink “two or three months” toward “a week” because you already paid the tuition of living in that industry.

That is forward deployed work. The remote part is the punchline. You can be a systems analyst who used to sit in Seattle, dump your brain into skills and workflows this month, and next quarter help a company in Tokyo or Istanbul ramp an agent that would otherwise crawl. Geography stops mattering when the deliverable is packaged judgment plus a tuned agent, not a badge swipe.

Early, not imaginary

Yes — this sits out on the frontier. Wearables training robots for physical shops. Knowledge workers turning careers into agent-ready modules. Token usage exploding because millions of people will try to cross the bridge from “I have a job” to “I monetize the onboarding of agents into businesses.”

The ones who move first will not wait for a tidy job title on LinkedIn. They will spend a weekend with agents — Grok Bot and tools like it — and leave with a working product: a skill pack, a course, a second brain that sells. A few days is enough to get something real on the table when the agent is doing the technical lifting and you are supplying the domain truth.

This onboarding wave — humans helping companies adopt agents without a three-month stumble — is not a side quest. I think it is a main plot for the next two to five years.

Doom-gloom vs boom-boom

If you still have a job, that is an asset, not a trap. Use the seat you have. Start the dump. Build the second brain. Ship one agent-friendly skill around the thing you already do well. Treat replacement risk as a product brief.

AI doom and gloom is one reading of the same chart. The other reading is AI boom-boom: you train agents, you service companies worldwide, you turn what used to be only a salary into a remote forward deployed practice.

The work is already here. The title is just catching up.

If you want to start that dump with a calm interview instead of a blank page, talk to Gini. Laptop can stay closed. The agents keep working.