🎮 The Next Input — Issue #060

⚡ The Briefing — 60 sec

• Australia’s future economy will be dominated by AI. The second Gold Rush? This time it’s silicon, not shovels.

• OpenAI expands its affordable ChatGPT Go plan to Indonesia. That’s 2-for-2 in countries that start with “IND.”

• OpenAI and Nvidia announce a systems partnership. It’s finally happening. The AI giants officially link arms.

🛠️ The Playbook — AI Economic Radar for Market Signals

Mission Stand up a lightweight AI-driven system that scans news, funding reports, and government releases to flag early indicators of economic shifts driven by AI adoption.
Difficulty Advanced | Build time 2–3 hours (pilot)
ROI Strategy teams save ≈ 8–12 h/week and catch trends months before they hit mainstream analyst decks.

0) Why This Matters

With governments like Australia projecting entire economies around AI, and OpenAI rolling out lower-cost access globally, the macroeconomic narrative is shifting in real time. The earlier you detect patterns—funding spikes, policy changes, infrastructure partnerships—the faster you can adapt GTM and hiring.

1) Architecture

2) End-to-End Workflow

1. Collect – Scrape top feeds + APIs daily at 6am.

2. Normalise – Strip boilerplate, dedupe, tag source & geography.

3. Cluster & Summarise – LLM prompt: “Cluster these items into {Policy, Funding, Infra, Adoption}. Summarise in ≤80 words with source + date.”

4. Score – Assign “signal strength” based on recurrence, investment $$, government involvement.

5. Store – Write {title, cluster, signal_strength, summary, url, date} to Supabase.

6. Digest – Slack push: “Top 5 AI-economic signals today.”

7. Visualise – Looker chart: frequency by cluster over time.

3) Example Prompt

SYSTEM: You are an economic intelligence analyst.
INPUT: {news_items}
TASK: For each, output JSON:
{
 "cluster": "Policy | Funding | Infra | Adoption",
 "signal_strength": 1-5,
 "summary": "≤80 words, include orgs + region",
 "url": "...",
 "date": "..."
}
RULES:
- Funding > $50M = strength +2
- Govt initiative = strength +2
- Multiple independent sources = strength +1

4) Guardrails

• Deduplication: Same story across outlets counts once.

• Attribution: Always include original URL.

• Privacy: No proprietary trading advice—signals = public data only.

• Human Checkpoint: Analysts review “strength 5” signals weekly before exec reports.

5) Pilot Rollout — 90 Minutes

1. Build Apify scraper for 3 sources (Reuters Tech, TC AI, Gov press releases).

2. Push to Make/Zapier → Claude clustering.

3. Store 20 signals in Supabase.

4. Deliver first Slack digest next morning.

5. Ask execs: “Would this have changed your week?”

6) Metrics That Matter

• Avg signals/day.

• % execs rating digest “useful.”

• Time saved vs manual scanning.

• “Hit rate” → how many signals later appear in mainstream analyst reports.

🎯 The Arsenal — Tools & Prompts

From today’s signals, select top 5 by strength.
Output markdown bullets:
- [Cluster] Title — Summary (≤30 words) (Source + Link)

💡 Free Office Hours

Want an AI radar for policy, funding, and adoption signals?
Book a free 15-minute Office Hours slot—no sales pitch, just workflows solved.

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

🕹️ Game Over

Ship one signal radar today—tomorrow your execs will see the AI economy before it hits Bloomberg.
Share your win; you could headline Issue #061.

— Aaron
Automating the boring. Amplifying the brilliant.

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