The Next Input — Issue #063

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⚡ The Briefing — 60 sec

• Trump shares bizarre AI video promoting “med bed” conspiracy. We saw you, Trump.

• South Korea plans to outpace OpenAI and Google with homegrown AI. “I got the whole country behind me!”

• Jobs that may be future-proof against AI. First they told us “get a job!” Now they tell us AI will take it… never ends!

🛠️ The Playbook — AI Workforce Impact Radar

Mission Build a system that continuously scans labor news, job postings, and workforce studies to flag which roles are being automated, augmented, or emerging.
Difficulty Advanced | Build time 3–4 hours (pilot)
ROI HR, strategy, and policy teams save ≈ 12–15 h/week, and leadership gets early warning on shifts that affect hiring, training, and investment.

0) Why This Matters

Executives keep asking: “Which jobs are safe? Which ones are at risk?” Answering this from gut instinct is dangerous. With automation accelerating, companies need live intelligence on workforce trends to guide L&D, hiring, and policy.

1) Architecture

2) Workflow

1. Collect

   • Scrape labor feeds + job APIs nightly.

2. Normalise

   • Deduplicate headlines; tag {industry, geography, role}.

3. Classify

   • Prompt LLM to assign category: Automated, Augmented, Emerging.

4. Score

   • Apply weights: funding size, number of mentions, government involvement.

5. Store

   • Insert {role, category, score, summary, url, date} into DB.

6. Digest

   • Weekly Slack digest: “Top 5 shifting roles this week.”

3) Prompt — Role Classifier

SYSTEM: You are a labor market analyst.
INPUT: {headline, article_text}
TASK: Classify the job/role status:
- Automated (AI replacing tasks)
- Augmented (AI assisting tasks)
- Emerging (new roles from AI ecosystem)
Return JSON:
{
 "role": "...",
 "category": "Automated|Augmented|Emerging",
 "score": 1-5,
 "summary": "≤50 words",
 "url": "...",
 "date": "..."
}

4) Guardrails

• Attribution: Always log source + URL.

• Transparency: Store classification confidence; escalate <0.7 to human reviewer.

• Privacy: Avoid scraping personally identifiable candidate info.

5) Pilot Rollout — 2 Hours

1. Scrape 50 job-related headlines via Apify.

2. Run classifier prompt; log into Supabase.

3. Build Looker chart: count by category (Automated, Augmented, Emerging).

4. Share Slack digest with execs Friday morning.

6) Metrics That Matter

• % of roles flagged automated vs augmented.

• Avg “signal strength” per role/sector.

• Time-to-insight vs analyst manually compiling reports.

• How often flagged roles appear in HR or board discussions.

🎯 The Arsenal — Tools & Prompts

From this week’s signals, select top 5 roles shifting most.
Output markdown bullets:
- {Role} — {Category} — {Summary} (Source)

💡 Free Office Hours

Want an AI workforce radar to track automation risks?
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

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🕹️ Game Over

Spin up one labor-signal radar today—tomorrow your HR team sees automation before it blindsides them.
Share your win; you could headline Issue #064.

— Aaron
Automating the boring. Amplifying the brilliant.

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