Build or Buy? Standing Up an AI Development Team
Hiring a full AI team is slow and expensive. Doing nothing is slower. Here is how to think about the middle path.
The Talent Trap
The instinct, once a company decides AI matters, is to hire for it. Post a job for an AI engineer, wait three months, pay a premium, and hope the one person you land knows strategy, engineering, evaluation, and your domain.
That bet rarely pays off quickly. The skills are scarce, the market is hot, and a single hire cannot cover the full surface from roadmap to production to maintenance.
What an AI team actually needs to cover
Shipping agents well takes more than a model wrangler. The real work spans:
- Strategy to pick the right problems and sequence them.
- Engineering to wire agents into your tools and ship to production.
- Evaluation to prove the thing works and keep it working.
- Operations to monitor, tune, and extend over time.
One person can do a slice of this. Few can do all of it, and the ones who can are expensive and busy.
The middle path
You do not have to choose between a full internal team and nothing. The pattern we see work:
- Bring in an external team to ship the first one or two workflows fast.
- Have them build alongside your people, not in a black box.
- Hand over the repository, dashboards, and runbooks so your team owns what was built.
- Hire internally later, against real systems and a proven roadmap, instead of a job description and a guess.
Own the capability, rent the head start
The goal is not to depend on an outside team forever. It is to compress the slow, risky early phase and come out the other side with working systems and a team that understands them.
Build for ownership from the start. The best outcome is the day your team no longer needs us for the day-to-day, because the capability now lives with them.
