What to Expect From an AI Development Partner
Not all AI agencies are the same. Here's how to evaluate whether a potential partner will actually ship, or just bill you for a slide deck.
Hiring an external team to build AI is a different kind of engagement than hiring a typical software agency. The field is moving fast, the talent is scarce, and there’s a wide gap between firms that can deliver production-grade systems and those that can put together an impressive demo.
If you’re evaluating partners, here’s what to actually look for.
Questions That Reveal Depth
“Can you show me something you’ve shipped?” Not a demo video. Not a sandbox. A live system that real users depend on. If they can’t point to deployed production work, you’re likely funding their learning experience.
“How do you handle model failures?” Every AI system fails sometimes. The quality of the answer here tells you a lot. A strong team will immediately talk about evals, fallback logic, human escalation paths, and monitoring. A weaker team will tell you their model is very accurate.
“What did you get wrong on a recent project?” This is the most revealing question. Teams that have shipped in production have specific, honest war stories. Teams that haven’t tend to give vague answers about “learning opportunities.”
“Who owns the system after you leave?” A good partner builds systems your team can maintain. Watch out for black-box implementations that create permanent dependency on the vendor.
Red Flags
- Proposals heavy on research phases, light on deliverables
- No discussion of evaluation methodology before starting
- Promises of accuracy percentages without asking about your data
- “We’ll use the latest model” without understanding your latency/cost constraints
- No questions about what happens when the system is wrong
What a Good Engagement Looks Like
A serious AI development partner will push back on vague requirements. They’ll want to understand your users, your failure tolerance, your data situation, and your success metrics before proposing a solution. They’ll scope a focused first phase that produces something real — not a six-month engagement with a demo at the end.
They’ll also be honest when AI isn’t the right tool. Not every problem needs a model. Sometimes a well-designed search index or a rule-based system gets you 90% of the outcome at 10% of the cost and complexity.
What You Should Bring to the First Conversation
- A concrete problem, not “we want to use AI”
- Some sense of what success looks like (even rough metrics)
- Willingness to share examples of real user inputs/outputs
- An honest view of your team’s capacity to maintain what gets built
The more specific you can be, the better the conversation will be. Vague briefs produce vague proposals.
If you’d like an honest, no-pressure conversation about what AI could realistically do for your business, that’s exactly what our free first call is for.