Few ideas have moved from conference stage to product roadmap as quickly as AI agents: systems that don't just answer a question but plan a series of steps, call tools and act on the results. The promise is real. So is the gap between a convincing demo and something you would trust with a customer's account.
Start with a narrow job
The agents that hold up in production tend to have a small, well-defined remit — triaging support tickets, reconciling invoices against purchase orders, drafting the first pass of a report from known sources. A narrow job means a short list of tools, a clear definition of done, and failures that are easy to spot. "An assistant that can do anything" is where projects stall.
Treat tools as the real interface
An agent is only as capable, and as safe, as the tools it can call. Give each tool a precise contract, validate every input the model produces, and put the dangerous actions — refunds, deletions, anything irreversible — behind a confirmation or a person. Open standards such as the Model Context Protocol make it easier to expose tools consistently, but the design of each tool is still yours to get right.
Measure before you scale
Agents fail in ways that are hard to see from a handful of test runs. Before widening the rollout:
- Collect real tasks from the job the agent is meant to do, with an agreed idea of what a good outcome looks like.
- Run the agent against that set on every change to a prompt, a model or a tool, and compare.
- Track cost and time per completed task, not per request — an agent that loops is expensive long before it is wrong.
Design the handover
The best agents make a person faster rather than trying to replace them. Show what the agent did and why, make it easy to correct, and route the cases it is unsure about to a human with the context already gathered. Trust is earned one visible, reversible step at a time.
If you are weighing where agents fit in your product, our AI & Machine Learning practice starts from the job to be done, and our Product Engineering team builds the tools, guardrails and monitoring around it.