Agent building

What it includes

• Design the agent: goal, tools it can use, data it accesses, and what it must NOT do.
• Pick the model per task (cost vs. reliability) instead of using the biggest one for everything.
• Build the scaffolding: prompts, orchestration, retries and error handling.
• Define autonomy limits: what it decides alone and what it sends to a human.

When you need it

• You already know which process to automate and need to build the piece that runs it.
• You have prototypes in a notebook that nobody has taken to production.
• Every team is rolling its own agent with no common pattern or guardrails.

How it’s measured

• Task success rate (correctly resolved cases / total).
• Cost per run and per resolved case.
• Human escalation rate and the reason for escalation.

Common mistakes

• Using the most expensive model for everything "to be safe", inflating cost without gaining reliability.
• Giving the agent broad system access with no limits on what it can touch.
• Shipping without evals: with no way to measure whether it’s right, you can’t improve it or trust it.

FAQ

Should you build custom agents or just buy a tool?

It depends on the process. Common tasks usually have a tool; for proprietary processes that are a competitive edge, building gives control over cost, data and reliability. That decision is the build-vs-buy capability.

What makes an agent different from normal automation?

An agent decides at each step what to do with the tools it has, instead of following a fixed flow. That flexibility is powerful, which is exactly why it needs explicit limits and evaluation.

Related capabilities