Primary audience
- Non-technical AI PM learners who want structured daily signals.
- NGO and education practitioners tracking applied AI developments.
- SME decision-makers who need business-aware summaries.
ABOUT
Why AI PM Radar exists
AI PM Radar is a static MVP for turning daily AI and business research into a readable front-end experience for non-technical readers.
It is also an AI Product Manager portfolio case study showing MVP scope control, source-aware content design, human review, validation, and low-cost static deployment.
Version 1 boundaries
The site is intentionally small: local JSON data, static export, and no user accounts, forms, or background jobs.
Design and engineering principles
- Static first
- Human review before publishing
- Source-aware summaries
- No premature backend complexity
- Validation before build
Portfolio value
This project demonstrates how a lightweight AI product can be scoped, documented, validated, and deployed without over-engineering.
STATIC DAILY BRIEF
Safer daily update workflow
The update flow stays static and review-first: curated sources, structured notes, human review, validation, then build.
1. Curate sources
Start with approved news, official docs, or research links instead of uncontrolled scraping.
2. Draft structured notes
Convert each source into summary, business angle, AI PM angle, and risk fields that match the JSON schema.
3. Human review
Check wording, scoring, and source fit before anything is treated as publish-ready.
4. Validate and build
Run the existing validation and static build commands before deployment to keep the demo stable.
Safety boundaries
- No paywall or login bypass.
- No uncontrolled scraping or external AI API calls in the helper script.
- Source links are required before publish.
- Human review stays in the loop before any final JSON is used.