AI Agent Playbooks for Smarter Business Decisions
Delegate thinking, analysis, and decision-making to AI — without building bots, writing code, or installing software.
What This AI Agent Playbooks Section Is
This section contains AI Agent Playbooks designed to help founders and operators delegate thinking work to AI inside everyday business workflows.
These are not ready-made agents or software tools.
They are practical, role-based guides that show how to use AI as a virtual team member for analysis, planning, review, and decision support.
AI Agent Playbooks Included (10)
Lead Follow-Up Agent
Helps draft, prioritize, and structure follow-up messages based on lead context so no opportunities fall through the cracks.
Proposal Review Agent
Reviews proposals for clarity, risks, gaps, and positioning before sending them to prospects or clients.
Content Planning Agent
Turns goals and ideas into structured content plans with themes, angles, and publishing logic.
Content Performance Agent
Analyzes content results and highlights what to improve, double down on, or stop producing.
Task Priority Agent
Helps decide what to work on next by evaluating urgency, impact, and effort across tasks.
Client Health Agent
Reviews client signals, communication patterns, and delivery status to identify risks early.
Revenue Insight Agent
Analyzes revenue inputs to surface trends, anomalies, and decision-ready insights.
Expense Control Agent
Reviews spending patterns and flags unnecessary or rising costs.
Weekly Review Agent
Summarizes the week’s activities, results, and lessons into clear takeaways and next actions.
Opportunity Evaluation Agent
Evaluates new ideas, partnerships, or opportunities using structured criteria to avoid impulsive decisions.
Best Practices for Using the AI Agent Playbooks
You do not need to use all agents.
Trying to use everything at once reduces clarity and results.
Start with one agent only.
Choose the agent that currently:
- Saves you the most time
- Reduces mental load
- Improves decision-making
Use agents manually first.
Run the agent by pasting context into ChatGPT and reviewing outputs.
This helps you understand how the agent thinks before adding automation.