AI EngineeringCurriculum in development
AI Harness Engineer
Build the context, tools, memory, evaluation, and controls that make model behavior useful and reliable.
Designed forBackend, platform, and AI engineers building agentic applications around foundation models.
Recommended foundationComfort with Python or TypeScript, APIs, data structures, and backend service design.
Problems you will learn to solve
Work from real constraints, not generic tool demonstrations.
Prevent malformed or unsafe tool execution
Control what context reaches the model
Diagnose why an agent failed across multiple steps
Working environment
Python, TypeScript, model APIs, MCP, vector stores, evaluation frameworks, tracing, Docker
System mapA reliable agent harness
User goal
Context + router
Retrieval + memory
Tools
Model
Evals + guardrails
Tracing + improvement
Provisional curriculum
Six connected modules
The sequence will be validated with practitioners before enrollment opens.
- 01Agent loops and state
- 02Context construction and retrieval
- 03Tool contracts and structured output
- 04Memory and persistence
- 05Permissions, approvals, and guardrails
- 06Evaluation, tracing, and recovery
Planned capstone
Finish with evidence of applied skill.
A controlled agent harness with retrieval, tools, persistent state, approvals, evaluations, and traces.
Focused lessonsUnderstand the underlying ideas
Guided practiceWork through realistic constraints
Applied projectProduce a demonstrable result
Structured reviewRevise the work after feedback
Program updates
Register your interest in AI Harness Engineer.
This is not enrollment and no payment is required. We will use your response to validate demand and contact you when the curriculum and cohort details are ready.