🛠 Pro Tip: Treat Your AI Agents Like a Real Team, Not Random Bots

Before you wire AgentKit or any workflow builder into production, design an internal “agent org chart.” Each agent is a role with a name—think Support Triage Specialist Agent, Revenue Ops Analyst Agent, Deal Desk Assistant Agent, Research Scout Agent—with a clear mission, tools, and decision rights.

Example Prompt (paste into your model of choice):

You are my AI org designer.

Context: We are a B2B SaaS company with 40 people and ~US$8M ARR.

Design a 4–6 member AI agent team with:
- A short name (e.g. "Support Triage Specialist Agent")
- Mission and success metrics
- Inputs (data + systems) and tools/APIs they can call
- Decisions they are allowed to make without a human

Deliver:
1) A table of agents.
2) A 1-page spec for the highest-ROI agent.
3) A 30-day implementation checklist.

• Why it matters (1): You avoid a zoo of disconnected bots and instead deploy a small, accountable “AI team” mapped to real business outcomes.
• Why it matters (2): Engineering gets a clear spec for each agent—data, tools, and guardrails—so pilots ship faster and break fewer things.

💡 Productivity Gem: Fireflies + Slack for the All-Hands Morning Brief

Combine your company’s meeting recorder (like Fireflies.ai) with your LLM’s built-in Slack connector to generate a complete morning brief for every department. Here’s how it works:

• Use Fireflies (or your note-taker of choice) to automatically capture transcripts and key decisions from the previous day’s meetings.
• Connect your LLM’s official Slack app (ChatGPT, Claude, Gemini, etc.) to your internal channels. This connection is built-in—just enable it under integrations.
• Set a scheduled task (7:30am recommended) for your model to pull the latest Fireflies summaries and Slack threads, then condense them into a one-page company brief: key wins, blockers, risks, and follow-up owners.
• Ask the model to tag each item with a suggested next action and @-mention teammates to ensure follow-up happens directly in Slack.

Why it matters: Your entire company starts the day aligned, with AI-generated suggested outreach and follow-ups already inside Slack—no extra meetings or status emails required.

⚕ AI-Enabled Health Tip: Weekly Wearable Debrief Instead of Metric Doomscrolling

Turn all that sleep and recovery data into something you’ll actually act on. Use your AI assistant to turn a week of wearable stats into a short briefing and two simple experiments for the next week.

• Once a week, export 7 days of sleep, resting heart rate, and HRV from Apple Health, Oura, Fitbit, or Garmin as a CSV or PDF and upload it to your model.
• Ask it to spot correlations between bad nights and late meetings, travel, or caffeine, and to propose 2–3 schedule changes to test.
• Paste the summary and experiments into a note pinned to next week’s calendar so you see it while planning your days.

Why it matters: You stop guessing about burnout drivers and start treating energy like a metric, with a simple weekly feedback loop tied to your actual calendar.

🧠 AI for Kids Tip: ‘Explain It 5 Ways’ Study Buddy (Ages 9–14)

Set up a supervised chat where your child asks about a topic from school and the AI has to explain it five different ways instead of just giving them the homework answer.

• In the instructions, tell the model to avoid browsing, keep answers age-appropriate, and never ask for personal information.
• Have it answer with: (1) a simple explanation, (2) a short story, (3) a real-world example, (4) an analogy, and (5) a three-question quiz.
• Review the chat history weekly, correct anything off, and turn the hardest questions into experiments or reading you explore together.

Why it matters: Kids get layered, multi-angle explanations that actually build understanding, while you stay in control of what the AI is teaching them.

If you try any of these workflows—or break something gloriously in the process—hit reply and tell me what happened. I read every message and I respond to everyone.

-Pierre