Your New Job Is to Onboard AI Agents. The Best Companies Already Know This.

The most interesting shift in tech right now is not a new model or a funding round. It's quieter than that. The best companies have stopped using AI as a tool and started treating it as a colleague.

Peter Yang published a detailed look at how three companies, Linear, Ramp, and Factory, actually operate day to day. The pattern across all three is the same: the human's job is no longer to do the work. It's to manage the AI that does the work.

And wherever there's a new skill that companies desperately need but few people have, there's a business to build.

How Linear thinks about agents

Nan Yu, Head of Product at Linear, described something that most companies haven't caught up to yet:

"You'll have AI team members that you can assign tasks to and talk to just like how you talk to people."

At Linear, AI agents read every customer conversation coming in from Intercom, Zendesk, and Gong. They create issues, de-duplicate them against the existing backlog, and assign them to the right team. Agents now create the majority of tickets. The humans review, adjust context, and decide what to prioritize.

For bugs and small features, coding agents handle the implementation directly through tools like Codex and Cursor. The human's role is to define what needs to be built and why. Then hand it off.

Ramp's proficiency framework

Ramp's CPO, Geoff Charles, said something worth sitting with:

"If you're not using Claude Code, no matter what your role is, you're probably underperforming."

That's not a suggestion. Ramp has built an internal framework with four levels of AI proficiency, and they expect every employee to climb it. This is a company that's making AI adoption mandatory, not optional, and measuring people against it.

Factory's reusable skills

Factory's CTO Eno Reyes took a different approach:

"We codified product management, frontend UI, data analysis, and more into reusable skills that any employee can invoke."

They turned their best people's expertise into AI skills. Now any team member can invoke specialized workflows without needing to be a domain expert. A junior engineer can use the "product management" skill to write specs. A designer can invoke the "data analysis" skill to pull insights.

The knowledge isn't trapped in people's heads anymore. It's encoded and reusable.

The business opportunity

These three companies are ahead. Most companies are not. And the gap between "we should use AI more" and "we have AI agents integrated into every workflow" is enormous. That gap is where you can build a business.

Here are five concrete approaches.

Agent onboarding consulting

Most Series A through C startups with 20 to 200 employees know they should be doing what Linear and Ramp are doing. They just don't know where to start.

You can audit their current workflow, design an agent integration plan, set up the first three to five agent workflows, and train their team on managing agent output. An engagement like this runs $5,000 to $25,000 depending on scope and company size.

The skill you're selling is rare right now. In a year, it won't be. That's why the window matters.

A course on managing AI agents

There are hundreds of courses on "how to use ChatGPT." There are almost none on "how to manage AI agents as a team." Peter Yang's article makes clear that PMs, designers, and marketers all need this skill. They need to learn how to write specs that agents can execute, how to set up workflows in Linear and Cursor, how to measure agent output quality, and how to decide when to delegate versus do it themselves.

A cohort-based course covering these topics could price at $200 to $500 per seat. The first credible course in this space will have a significant advantage.

Pre-built agent skill packs

Factory built reusable skills for their own team. You can build them for the market.

A sales agent pack with lead scoring, outreach drafting, and CRM updates. A content pack with blog writing, social scheduling, and SEO workflows. A customer support pack with ticket triage and escalation logic.

Sell them at $50 to $200 per pack on a marketplace or directly to companies. The skills are hard to build well, which makes them defensible.

AI proficiency audits

Ramp created four levels of AI proficiency internally. You can productize that framework as an external assessment.

Level one: using AI for basic tasks like drafting emails. Level two: AI-assisted workflows like coding with Cursor. Level three: agent delegation, assigning real tasks to AI. Level four: AI-first operations where agents create most of the output and humans review.

Assess a company's current state, score them, and sell the roadmap to get them to level four. Price it at $2,000 to $10,000 per audit.

An "AI Operations Manager" community

This job title barely exists yet. In two years it will be common. You can own the community now.

Weekly breakdowns of how top companies use agents. Templates and playbooks. A job board as the role gets created at more companies. Slack or Discord for practitioners to share what's working.

Price it at $20 to $50 per month. Build the audience while the category is forming, and monetize through membership and sponsorships as it matures.

What to take from this

The companies pulling ahead are not the ones with the best models. They're the ones who figured out how to onboard AI as team members. That's a skill gap. And skill gaps are where businesses get built.

Pick one approach. Start this week. The window for being early in this space is still open, but it's closing.