Build the world
Give the agent realistic services, data, policies, and state without connecting it to production.
A half-day workshop with the Enderis founders
Autonomous agents are scary because they take action.
A chatbot can give a bad answer. An autonomous agent can change a customer record, send a message, approve a transaction, or trigger a workflow. We show teams how to test that behavior before it reaches production.
Length: half day
Format: working session
Focus: one agent or workflow
How agents get shipped
The biggest companies in the world build autonomous agents around tests.
The model will always have some freedom. You cannot make an autonomous agent reliable by writing a perfect prompt or predicting every sequence of tool calls.
Strong AI teams define the situations the agent must handle, give it a safe world to act in, and test the outcomes. Those tests let them change models, prompts, and tools without losing the behavior the product depends on.
Real situationsSimulated servicesObservable actionsExpected outcomes
It is all about the tests
Here is how to build them.
A useful agent test is more than a prompt and an expected answer. It gives the agent a world, lets it act, and checks the consequences.
Put the agent in a situation
Start from a known state and give the agent a concrete job, including the ambiguity and edge cases it will face in practice.
Check what happened
Judge the outcome: what the agent changed, what it communicated, and whether it knew when not to act.
Simulated services make the test safe and repeatable. The agent can read and change realistic state while production systems and customer data stay untouched.
What we will do
Bring your agent. We will build the testing approach together.
- 01
Bring your agent
We start with one agent or workflow your team owns. A prototype, prompt, repository, tool definition, or architecture diagram is enough.
- 02
Define what it should do
We choose the situations that matter and make the expected behavior precise enough for product, engineering, and domain experts to agree on.
- 03
Design the test environment
We map the services and state around the agent, then show how to simulate them so tests are safe, repeatable, and independent of production.
- 04
Build the first tests
We turn real examples into test cases with a known starting state and observable outcomes, then identify the next tests your team should add.
You leave with a clearer definition of the agent, a design for its test environment, and the first set of test cases to build.
Who we are
We have built, trained, evaluated, and shipped AI systems.
Half day · one real agent
Bring the agent your team needs to trust.
Tell us what it does today and which actions make the team nervous. We will plan the workshop around that workflow.
Talk to Tommy and Meni