Evaluate your agent
/lab-evaluate t3- Submit your task implementation.
- Replay scenarios in the cloud simulation.
- Inspect final-state assertions and the pass matrix.
A Learning Environment for Human Expertise Development
Build the expertise that matters in the AI era.
Access the knowledge, environments, and guidance
to practice complex work and build your expertise.
OUR LEARNING COMMUNITY
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AI expands what
people can accomplish.
Much of the conversation around AI focuses on the jobs it may replace. We believe it also expands what people can accomplish: enabling more people to solve complex problems and take on more meaningful, higher-value work.
New possibilities. Familiar barriers to learning.
Consider robotics, enterprise AI, cybersecurity, and large-scale data processing. Entering these fields has often required access to scarce training environments and domain-specific knowledge built through experience. Small, dispersed professional communities have made high-quality training and guidance difficult to scale.
These are the barriers we are working to break.
Agentist provides simulated Enterprise Labs for repeated practice, simulated users that make requests and test outcomes, and real-time guidance from Mentor Agents grounded in domain-specific knowledge. Through practice, feedback, and repeated validation, learners build the capabilities to take on higher-value work.
Turn the possibilities AI opens into capabilities people can build.
Explore the labsExlen Virtual LabReal tasks. Simulated users. Domain guidance.
Choose a capability. Practice in its environment.AI-generated concepts · Not actual facilities
The case for virtual labs
Solve complex problems.
Deliver meaningful outcomes.
Practice understanding problems, making decisions, designing solutions, and validating results through industry-based tasks. With prepared environments, domain knowledge, and simulated users, turn what you know into the professional expertise to solve complex problems.
A system already in motion
Start with data, APIs, state machines, and mocked dependencies. In Signal Studio, mocks are built from recorded traffic and validated through contract tests.
Guidance with project context
Ask /lab-assistant about project-specific behavior, hidden interface constraints, and known pitfalls. Get guidance when you need it.
Users that exercise your work
Simulated users run your agent through repeated scenarios. Use /lab-evaluate to inspect outcomes and decide what to improve next.
Build · Evaluate · Improve
Work in the tools you know.
Improve with evidence.
Use your coding agent, submit a completed task for evaluation, and ask for project guidance when you get stuck.
Get project-aware guidance
/lab-assistant why does the handshake fail?- Ask a concrete question about your task.
- Get context grounded in the project and reference implementation.
- Apply the feedback and run another evaluation.
Evidence · Signal Studio
Built against real interfaces.
The video lab uses recorded traffic to reproduce OBS and editing API behavior. Evaluation checks both what the agent calls and what it leaves behind.
Repository snapshot, September 2026. Reference implementation results are not learner scores. Meridian Air is open; the other two launch in late September.
Inspect the evaluation snapshot ↗Tasks7A progressive engineering sequence
Knowledge points8Project-specific learning objectives
Reference tools37Tools in the solution implementation
Validationk = 3Reference cloud acceptance runs
Availability
One lab open.
Three more in development.
OPENSignal Studio · VideoRecorded traffic, OBS and editing mocks, contract tests, and a cloud evaluation worker. Plugin-side evaluation availability follows the release schedule.
OPENMeridian Air · Airline ERPPassenger records, policy constraints, booking changes, and final-state consistency checks inspired by the τ-bench airline setting.
LATE SEPTEMBERKinema Robotics · Embodied AIUR5 grasping simulation, camera streams, task planning, and safety assertions.
LATE SEPTEMBERSubstrate Inference · Model servingTenant routing, quotas, billing, traffic replay, and service-level checks.
Your next engineering challenge
Start with a problem
worth solving.
Explore the environments, choose an engineering role, and follow a concrete sequence of tasks.
← Back to labs
Choose your engineering challenge.
Select an environment and explore its infrastructure, engineering roles, and task sequence. Signal Studio is open; the other environments are planned.