These are not academic models. Each one exists because something in a real business needed a name before it could be managed. The diagrams are deliberately simple: if a framework cannot survive being drawn on a whiteboard, it is not a framework.
Try the five-check preflightA framework you can use
Your Monday Morning Preflight
Five checks from the essay. Work through them with your team, then print a copy for the conversation.
Open the five-check worksheet
This tool does not submit or save your entries. Print a copy to keep it.
Review the five checks with your team.
A discussion aid, not a certification that an agent or workflow is ready.
Based on The Monday Morning Preflight by Prateek Saxena.
The Operator's Harness
The operating system around an AI model: the workflows, permissions, verification steps and audit trails that let agents act safely inside a real company.
The model sits inside a working system.
- ToolsThe actions the agent can take.
- PermissionsThe boundaries it must respect.
- ContextThe business information it needs.
- MemoryWhat it should retain between tasks.
- WorkflowHow work moves from one step to the next.
- ObservabilityA record of what happened.
- FeedbackLessons from the result.
Verification across all seven layers: check evidence before an action, and confirm the result before work counts as done. This is my practical operating model, not a universal technical standard.
Self-Improvement Protocol (SIP)
A structured feedback loop for AI agents: record a failure, review the cause, test a correction and approve a versioned rule for reuse. It can reduce repeated errors, but each result still needs verification; it does not automatically retrain the model.
Review and test a correction before reusing it.
- MistakeIdentify what went wrong.
- CorrectionTest a correction against the failure.
- Human reviewReview and approve the lesson.
- Standing ruleApprove and version a reusable rule; keep checking its results.
Next task → apply the rule → check the result → improve again.
Monday Morning Preflight
A readiness test for AI agents: can they turn Friday's loose ends into a clear Monday operating plan before the team loses time organizing itself.
From Friday’s loose ends to Monday’s plan.
- Data truthCheck the facts in the live business records.
- ContextUnderstand what the numbers and follow-ups mean.
- HandoffsMake the next owner and action clear.
- JudgmentEscalate decisions that need human review.
- AuditKeep a traceable record of the plan.
Friday’s open follow-ups → agent preflight → a clear Monday operating plan.
Vibe coding in a suit
A business operator using AI agents and plain language, not code, to build the tools, dashboards and systems their company actually needs.
A loop between business intent and working tools.
- OperatorUnderstand the business need and write a plain-language brief.
- AI agentsBuild the proposed tool, dashboard or system.
- Working toolsReview the result against the real business need.
Review → refine the brief → build again.
Briefing an AI agent
Giving an agent a business goal, the context to understand it, the constraints it must respect and the review criteria for its work. You are not asking for an answer; you are asking it to do work.
A useful brief gives the agent four things.
- Business goalWhat the work should achieve.
- ContextWhat the agent needs to understand.
- ConstraintsThe limits it must respect.
- Review criteriaHow the result will be checked.
Brief → agent does the work → verify the result before calling it done.
Terms behind these frameworks are defined plainly on the definitions page. New here? The Start Here page suggests a reading order, and the AI agents for business operators hub collects the practical guidance in one place.