The Next Input — Issue #099

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⚡ The Briefing — 60 sec

• Trump to resume selling AI chips to China under new export framework
  A full 180. Months of “no chips for China,” and now? Green light—just… with paperwork. Geopolitics stays unpredictable.

• Claude Code is coming to Slack — and it’s a bigger deal than it sounds
  Dev workflows just changed. Slack isn’t chat anymore—it’s the command line with emojis.

• Teens relying on AI chatbots for mental health support
  High stakes here. Helpful when it works—dangerous if it doesn’t. These models need to be solid, not cute.

🛠️ The Playbook — The AI Policy Early-Warning System

Mission Create an automated feed that tracks policy shifts, export rules, and global AI announcements—and tells you instantly what actually changed and why it matters.
Difficulty Medium
Build time 2 hours
ROI Protects your roadmap from being blindsided by sudden political whiplash.

0) Why This Matters

One policy move can alter:

• GPU access

• cloud pricing

• deployment rules

• data flows

• customer risk

Trump flipping chip export restrictions again proves every AI team needs a system that catches these swings immediately—not when the news hits LinkedIn three days later.

1) Architecture

2) Workflow

1. Feedly tracks a curated list: gov sites, financial press, global tech policy.

2. Perplexity fetches summaries every 4 hours.

3. Claude 4.5 Haiku tags each update:

   • export/semiconductor

   • safety/regulatory

   • privacy/data

   • geopolitical movement

4. GPT-5-mini generates an “Impact Snapshot”:

   • what changed

   • who’s affected

   • immediate risk

   • suggested watchpoints

5. System stores everything in Notion with timestamps + impact level.

6. Slack alert fires for high-impact moves (e.g., chip export reversals).

3) Example Prompts

Classification Prompt (Claude 4.5 Haiku)

Classify this policy update:
- export controls
- international relations
- safety regulation
- privacy/data
Return the category and a one-sentence summary.

Impact Snapshot (GPT-5-mini)

Explain the operational impact of this policy shift:
- what actually changed
- immediate risks
- who is affected (infra, pricing, access, timelines)
Keep it concise and practical.

4) Guardrails

• Don’t overreact to early drafts of policies—only act on confirmed moves.

• Keep internal alerts factual, not speculative.

• Prioritise updates that affect GPU supply, data rules, or go-to-market strategy.

• Add human review before high-severity alerts.

5) Pilot Rollout — 2 hours

1. Build a Notion DB with fields: category, source, summary, impact.

2. Add Feedly + Perplexity automation via Make.com.

3. Test the classifier with 20 recent policy stories.

4. Validate “impact” summaries with a product or ops lead.

5. Turn on Slack high-impact alerts.

6) Metrics

• Number of policy shifts captured per month

• Alert accuracy (manual review)

• Time between policy announcement and internal notification

• Percentage of roadmap decisions influenced by early warnings

• Reduction in “wait, when did this change?” moments

Pro Tip: Track reversals separately. Policy whiplash often matters more than the initial decision.

🎯 The Arsenal — Tools & Platforms

• Feedly AI · Real-time policy and regulation feed tracking · https://feedly.com

• Notion DB · Store policy shifts + historical impact logs · https://notion.so

• Make.com · Automate ingest → classify → alert flows · https://make.com

• Bolt Io · Slack-native alerting for high-impact events · https://bolt.new

Copy-paste prompt block:

You are my AI policy impact analyst.
Turn updates into:
- what changed
- who is affected
- immediate risks
Tone: crisp and operational.

💡 Free Office Hours

Want help implementing anything? Book a free 15-minute Office Hours slot—no sales pitch, just workflows solved.

→ https://calendly.com/aaron-cylentis/the-next-input-office-hours

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🕹️ Game Over

The rules of AI shift fast—your system shouldn’t lag.

— Aaron Automating the boring. Amplifying the brilliant.

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