What makes an AI agent production-ready?
Updated · By Algen AI
Demo versus production
| A demo | Production-ready | |
|---|---|---|
| Scope | In the author's head | Purpose and limits written down |
| Tools | Work for the happy path | Described, typed, and fail gracefully |
| Runs | Stop when they stop | Bounded in steps, time or spend |
| Errors | Swallowed or printed | Surfaced to someone who can act |
| Risky actions | Just happen | Wait for a person's approval |
| Quality | Looks right in testing | An evaluation set, traced runs |
The two-stripe baseline
- Purpose documented: Someone new can tell from the agent's documentation what it does, who it is for, what it takes in and what it produces.
- Runnable: Someone else can run the agent from documented steps.
- Tool interfaces clear: Each tool tells the model what it does and when to use it.
- Secrets protected: No credentials are committed to the repository; secrets come from the environment or a secret store.
- Runs bounded: A run cannot continue without limit in steps, time or spend.
- Failures surfaced: Errors are reported or handled, never silently swallowed.
- Untrusted input separated: Content that can come from users or the outside world (tool results, documents, web pages, stored memories) is passed to the model as data, not as instructions.
- Consequential actions controlled: Actions with real-world effect wait for a person's approval, or are otherwise constrained so a mistake can't do serious harm.
The third stripe: evaluated
Stripe 3 needs an evaluation set from real tasks that the agent passes, and runs you can read: tracing with any OpenTelemetry-compatible tool. You run them and submit the results.
Browse versioned agents with their stripes, permissions and delivery paths.
What makes an AI agent production-ready: common questions
How do I know if my AI agent is ready for production?
Check it against the two-stripe baseline: written scope, a way to run it, described tools, no committed secrets, bounded runs, surfaced errors, untrusted input kept apart, and approval before consequential actions. AgentStripes checks a public repository for free.
Do I need tracing for a production agent?
Yes, from the third stripe. Without traces you can't tell why a task failed. Any OpenTelemetry-compatible tool works.
Is a framework's default step limit enough?
For the second stripe, yes: LangGraph, CrewAI and the OpenAI Agents SDK stop runaway runs by default. Deliberate limits in steps and time or spend rate higher.