CoreWise Academy

Topic tag

verification

12 guides in the catalogue cover this topic.

All topics: agent safetyautomationcareerClaude CodeCodexcost controldelegationdesigninstruction filesknowledge basesmemorymodel behaviormodel choiceplanningskillsteamsverificationwriting prompts

  1. Nº 008 Automate the step that slows you down Agents & Automation · Broad

    Automating the bottleneck means finding the constraint that sets your pace and pointing Claude at it: four working rules distilled from Anthropic's own engineers.

  2. Nº 016 Guardrails for hours-long agent runs Prompting & Context · Deep

    Guardrails are the support structure that keeps an hours-long agent run honest: an audit instruction, a memory that survives resets, and fresh-eyed verifiers.

  3. Nº 028 Keep a growing knowledge base accurate Agents & Automation · Practitioner

    Wrong agent answers usually trace to the files the agent reads. The four ways a growing knowledge base drifts from reality, and the habits (a router file, read-only audits, scheduled pulls, backtracking) that catch the drift.

  4. Nº 029 Loop the agent until the work passes Agents & Automation · Practitioner

    A rerun loop makes the agent redo its own work until a check passes. Script the repetitive half of a skill, end it with a pass or fail verdict, wrap both in a loop, and keep a human at the checkpoints where errors are expensive.

  5. Nº 030 Trim the instructions your model outgrew Prompting & Context · Practitioner

    Audit Claude Code instructions, preserve project requirements, and test a smaller setup against the work you already trust.

  6. Nº 031 Why AI makes slop and how to catch it Practice · Broad

    Models got good where the work grades itself, and they aim at the most likely answer, which in design and writing is the average one. The fix: break your quality standard into checkable rules and keep human judgment for taste.

  7. Nº 034 Split big AI tasks into steps and checks Agents & Automation · Broad

    One big question in one chat makes the model decide, research, write, and grade itself in a single pass. Map the work instead: parallel research jobs, a checker that did not write the answer, a merge, and your approval before anything expensive.

  8. Nº 035 Score your agent on known good answers Building with AI · Practitioner

    One successful run proves an agent worked once. Collect real examples with answers a person already judged good, grade each run with a script or a judging model, and rerun the set after every change so you know whether it helped.

  9. Nº 050 Keep Claude automations working Agents & Automation · Practitioner

    Turn a tested task into a reusable skill, choose where it runs, and catch failed work before it wastes more time.

  10. Nº 052 Learn a work skill with AI Practice · Broad

    Choose a task you need to do, learn from checked sources, then test your understanding by doing the work and explaining your decisions.

  11. Nº 053 Compare AI agents on your own work Agents & Automation · Practitioner

    Compare agents on one repeatable task, check the tools each can use, and keep your skills usable when you switch.

  12. Nº 054 Make skills improve after each run Agents & Automation · Practitioner

    Use failed runs to repair skill descriptions, scripts, and checks. Test each change before keeping it, with Harness Firmware as a working example.

All topics: agent safetyautomationcareerClaude CodeCodexcost controldelegationdesigninstruction filesknowledge basesmemorymodel behaviormodel choiceplanningskillsteamsverificationwriting prompts