Most importantly, you need iterators and tinkerers. The playbook for production agents barely exists so your team is going to need to learn on the job. To solve for this. I look for “learn-it-alls” who are genuinely excited about working on agents. People who are eager to tinker– try new things, fail and try again, happily.
Without buy-in and support from the broader organization, even the best team will struggle. I’ve seen brilliant agent teams get stuck because they can’t access the data they need, or because security teams block their API integrations, or because business stakeholders won’t participate in the iterative testing process that agents require. Unlike traditional software projects, where you can build in isolation and deploy when ready, agents need ongoing collaboration with the people whose work they’re automating.
You need legal teams willing to review new AI policies, security teams who understand the unique risks of LLM-based systems, and business users who will provide honest feedback during the messy early phases when your agent gets things wrong half the time. You need engineers who can tackle new problems, like how to delegate authorization or how to safely manage the tools LLMs can utilize. But most importantly, you need executive air cover when things don’t go smoothly. And, rest assured, they won’t always go smoothly. The organizations succeeding with agents have leadership that treats early failures as learning opportunities rather than reasons to shut down the program.
