Hiring the wrong partner for an AI agent build is an expensive way to learn a lesson. Large agencies often run a long discovery phase, hand your requirements to developers you never speak with directly, and bill by the hour against a scope that keeps drifting. Freelance platforms go the other way — fast to start, but with no real accountability if the integration breaks six weeks after launch.
Meanwhile, in-house hiring for this specific skill set is slow and expensive: agent engineering sits at the intersection of software integration, prompt and tool design, and production monitoring, and very few candidates are strong across all three. Most small and mid-size businesses can't justify a full-time hire for one build.
The result is a lot of companies stuck between "too expensive to do properly" and "too risky to hand to a generalist contractor," while the manual work the agent would have replaced keeps costing real hours every week.