🔎 Ops Prompt of the Week
Prompt:
“Design a pair of AI agents that collaborate on root cause analysis: one collects historical data and tags anomalies across production runs, while the other builds causal links and suggests prioritized action items. Include an auto-generated executive summary as the final output.”What it does: Automates complex root cause workflows with coordinated AI agents.
Why it matters: Reduces time-to-insight while capturing patterns that humans may overlook.
How to vary: Swap in different data types (e.g., support tickets, energy consumption) or final outputs (e.g., visual diagrams, risk scores).
📰 AI in Ops – News
- Amazon rolls out Project Lumen: AI-driven supply chain forecasting platform: The new service, announced June 17, combines internal logistics data with third-party trend signals to improve lead time accuracy by up to 22%. Read more
- OpenAI’s GPT‑4o adds memory editing for custom assistants: As of June 10, users can now view, delete, and add memory entries for GPT-based custom assistants—bringing finer control to enterprise agent applications. Read more
💡 AI Insight of the Week
Insight: Use alternating perspectives in prompt structure
Instead of asking AI what you should do, try assigning it a role:
- “As a skeptical operations auditor, what would you challenge in this plan?”
- “From the perspective of a seasoned machine operator, what risks stand out?”
This technique uncovers blind spots, improves realism, and prompts the model to simulate different stakeholders more effectively.
🎉 Fun Prompt of the Week
“Design a team of whimsical AI agents to run your backyard lemonade stand. Include a CFO squirrel, a marketing parrot, and a robotic juicer. Write a Slack thread where they debate pricing strategy after a heatwave.”What it does: Exercises multi-agent creativity in a playful, low-stakes scenario.
Why it’s fun: Turns ordinary teamwork into a comical AI improv session.
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