How to Choose an AI Development Partner: The CTO's Evaluation Checklist

What 15 years of being “the agency” taught me about choosing one

I’ve spent my career on the agency side — building products for clients, managing client relationships, delivering against expectations. That experience, ironically, makes me good at advising on what to look for when hiring a development partner. I know what matters because I know what goes wrong.

Technical evaluation

Ask to see RAG implementations, not chatbot demos. Every agency can wrap a ChatGPT API. Few can build a production RAG system with proper chunking, citation verification, and evaluation metrics. Ask for specific accuracy numbers from past projects — retrieval precision, answer faithfulness, hallucination rates. If they can’t provide numbers, they aren’t measuring, and if they aren’t measuring, they don’t know if their systems work.

Ask about their evaluation methodology. How do they measure whether an AI system is working? If the answer is “we test it manually” or “the client tells us if something’s wrong,” that’s a red flag. Look for teams that define metrics upfront, build automated evaluation pipelines, and track performance across iterations.

Ask about anti-hallucination techniques. If the team can’t articulate their specific approach to preventing hallucinations — beyond “we use RAG” — they haven’t solved the problem in production.

Domain experience

AI development for regulated industries (legal, financial, healthcare, education) requires domain knowledge that generic AI skills don’t provide. A team that’s never worked with FCA compliance will underestimate the regulatory burden by 30–50%. A team that’s never built legal AI won’t understand why citation accuracy matters more than response speed.

Ask for case studies in your specific industry. Not “we’ve built chatbots for various industries” — specific examples with specific outcomes. We can reference the AAA ChatBook tools for legal AI, AdvisorEngine for wealth management, SuitsMe for financial inclusion, EmanuelAYCE for edtech — because those are real projects with real outcomes.

Communication and process

This is where most agency relationships fail, and it’s what AdvisorEngine taught me most deeply. As the project grew from 5 to 40 people, the biggest challenges weren’t technical — they were about communication. Managers intermediating between stakeholders and developers created information loss. Emails that one side treated as agreements were ignored by the other.

Evaluate how the agency communicates during the sales process. If they’re unclear, slow to respond, or overpromise before understanding your problem — that’s how they’ll be during the project, but worse. Look for teams that ask good questions before proposing solutions, that push back on unrealistic timelines, and that name specific risks rather than promising smooth sailing.

Red flags

Promising specific accuracy without seeing your data. No responsible AI team guarantees 99% accuracy before understanding your content and use case. Inability to explain trade-offs. Every AI architecture decision involves trade-offs — speed vs. accuracy, cost vs. quality, build vs. buy. If the team presents every decision as obvious, they’re either oversimplifying or inexperienced. No evaluation methodology. If they can’t describe how they’ll measure whether the system works, they won’t know when it doesn’t. Fixed-price quotes without discovery. AI projects have inherent uncertainty. A fixed price without a discovery phase means the team is either padding the estimate or planning to cut corners.

“The best signal is how an agency handles the first conversation. Do they ask about your business problem, or do they jump to technology solutions? Do they discuss trade-offs, or do they promise everything? Do they mention risks, or only benefits? The agencies that ask hard questions upfront are the ones that deliver later.”

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Evaluating AI development partners? Contact us — we’re happy to be evaluated against these criteria. Start with a conversation and judge for yourself.