Why Startups Choose an AI Agency Over Hiring
When founders reach the point where they need to build AI into their product, the first instinct is usually to hire. Post a job for a "Senior ML Engineer," offer equity, and wait. Most of them eventually work with an AI agency for startups instead — not because hiring is wrong in principle, but because the math doesn't work at the stage they're at.
Here's an honest comparison of both paths.
The Real Cost of Hiring an AI Developer
The posted salary is the starting number, not the ending number.
A senior AI/ML engineer in the US costs $180,000–$240,000 in base salary in 2026. Add employer taxes, benefits, equity dilution, recruiting fees (typically 20–25% of first-year salary when using a recruiter), and the hardware or tooling budget they'll request in week one — and you're looking at $250,000–$320,000 in year-one loaded cost for a single hire.
Then there's the time to hire. Median time-to-fill for senior AI engineers is 3–5 months. That's three to five months where your roadmap is blocked, your competitors are shipping, and your runway is burning.
And that's assuming you hire the right person the first time. If the hire doesn't work out — wrong skill set, mismatch on pace, wrong technical bets — you're back at zero, down six months and potentially six figures in severance.
For a pre-seed or seed startup, this is rarely the right call. The bet doesn't match the stage.
What an AI Agency Actually Costs
A scoped AI agency engagement for a startup typically runs $5,000–$50,000 depending on scope. At 100x Engineering, our entry sprint is $4,999 and ships in 21 days. Larger engagements for multi-workflow products or integrations with existing systems are quoted per project, typically $15,000–$40,000.
You pay for work done, not for headcount you're carrying through the months where your AI engineer is "ramping up," "exploring the problem space," or "doing architecture reviews."
See our full MVP development sprint guide for a week-by-week breakdown of what that $4,999 delivers.
Speed: The Comparison That Matters
| | Hiring | Agency (100x) | |---|---|---| | Time to first output | 4–6 months | 5 days | | Time to production | 8–12 months | 21 days | | Iteration speed | Weeks | Days |
Speed isn't just about impatience. For a startup, it's about whether you're learning faster than you're spending. An agency gives you a working product in three weeks — something you can put in front of users, investors, or design partners. A hire gives you a human who is still onboarding.
Risk: Where Each Model Breaks
Hiring risks:
- Wrong technical direction. An ML engineer will optimize for the approach they know, which may not be the right one for your use case.
- Dependency. If that engineer leaves, your AI roadmap leaves with them.
- Scope drift. Internal teams have a natural tendency to build more than is needed. It's what engineers do when they're curious and not constrained.
Agency risks:
- Knowledge transfer. If you don't manage the handoff well, you end up with a product you can't maintain.
- Communication overhead. Bad agencies treat clients as ticket submitters. Good ones involve you at each decision point.
- Fit. Not every agency can move at startup speed. Ask for references from companies at your stage.
We solve knowledge transfer with structured documentation and a 60-minute handoff call included in every engagement. We solve fit by doing a 15-minute scope call before you pay anything — if the scope doesn't fit our model, we say so and you lose nothing.
When to Hire Instead
To be direct: hire when you have product-market fit and a clear AI roadmap that requires 12+ months of sustained engineering. At that stage, owning the capability in-house is the right long-term bet.
Agency relationships are for when you're still discovering what to build, when you need speed over depth, and when the risk of a bad hire outweighs the premium of agency pricing.
The Hybrid Path Most Fast-Moving Startups Use
Start with an agency to validate and ship. Then hire one strong engineer to own and extend the foundation that was built. This gives you speed in the critical early phase and capability ownership once you've validated the direction.
It's not agency vs. hiring. It's sequencing.
If you're at the stage where you need to ship something AI-powered in the next 30 days, schedule a 15-minute scope call. We'll tell you honestly whether the sprint model works for your situation.
For a broader comparison of agency vs. in-house tradeoffs at different stages, see /compare/in-house-vs-agency-ai-development.
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