Build a Business AI Agent with AGENTS.md, Skills and Evals
Turn one repeatable business job into a narrow file-aware agent with durable context, a custom skill, permissions, held-back evals, and a verified launch pack.
Define One Agent Job and Outcome
Choose one repeatable business job, define the useful output, and turn quality into binary evidence.
Choose the Smallest Native Surface
Choose among a prompt, AGENTS.md, skill, specialist agent, connector, plugin, or schedule.
Write Durable Repository Guidance
Write concise AGENTS.md guidance that identifies context, sources of truth, boundaries, and conditional detail.
Build a Concise Custom Skill
Create a discriminating skill with progressive detail, deterministic helpers, and trigger tests.
Set Permissions and Human Gates
Define reads, writes, external actions, secrets, limits, approvals, and human decisions.
Create Real and Held-Back Evals
Build structural, deterministic, behavioural, boundary, hostile-input, and discovery tests.
Run, Grade, Repair, and Record
Execute the same cases, grade independent outcomes, diagnose failures, and preserve run evidence.
Verify Launch, Rollback, and Maintenance
Test the installed copy and finish invocation, update, disable, rollback, and maintenance instructions.
What you will work towards
Work through this course to prepare a launch pack for one bounded business agent. The curriculum takes you through durable repository guidance, a concise skill, permission boundaries, evals and operating instructions.
Start with one recurring job, a working folder and an example of an acceptable output. Use synthetic information while learning when permission to use live records is unresolved.
A practical case to carry through the lessons
An agent preparing a weekly account brief needs approved source files and a clear output format. It does not need permission to contact the customer or change the CRM.
Hold some evaluation cases back while building. A repair that passes the example used to write the instructions still needs a fresh check.
How to know the work is ready for review
Before calling the exercise complete, check that another operator can run, grade, disable and roll back the agent using the recorded instructions.