How to Track AI Developments Across GitHub, Blogs, and Launches

## TL;DR A 3-layer AI tracking system: product radar for launches, GitHub for OSS momentum, and blogs/changelogs for depth—combined without duplication. ## Decision in 20 seconds **A 3-layer AI tracking system: product radar for launches, GitHub for OSS momentum, and blogs/changelogs for depth—combined without duplication.** ## Who this is for Product managers and Developers who want a repeatable, low-noise way to track AI updates and turn them into decisions. ## Key takeaways - The 3-layer problem - Layer 1: Product radar (launches) - Layer 2: GitHub (OSS momentum) - Layer 3: Blogs and changelogs (depth) ## The 3-layer problem AI developments surface in three places that rarely overlap cleanly: 1. **Product launches:** Official announcements, new APIs, new products. 2. **GitHub:** OSS repos gaining momentum, new repos appearing, version releases. 3. **Blogs and changelogs:** Technical depth, migration guides, engineering decisions. Following all three through different tools creates overlap, duplication, and context-switching that burns your monitoring budget. ## Layer 1: Product radar (launches) Use a curated radar that aggregates product and model launches with summaries and source links. This is your primary entry point for "what shipped." Scan weekly. Shortlist what's relevant. This layer gives you breadth. ## Layer 2: GitHub (OSS momentum) Use GitHub Watch (releases only) for repos you depend on. Use GitHub Star for repos you're tracking. Use a radar with OSS trend data for discovery of new projects. Check your GitHub notification feed in your weekly slot alongside your radar scan. This layer gives you OSS depth and early signals. ## Layer 3: Blogs and changelogs (depth) When a product radar item or GitHub release needs deeper understanding, follow the primary source link to the blog post or changelog. Don't read blogs speculatively—read them as follow-up to items already shortlisted. This layer gives you implementation depth. ## Combining without duplication The key is sequencing, not parallelism: 1. **Weekly scan:** Radar (Layer 1) + GitHub notifications (Layer 2) in one 20-minute session. 2. **Follow-up reads:** For shortlisted items only, read the blog/changelog (Layer 3). 3. **Never read Layer 3 speculatively.** Only follow links for items already shortlisted. This ensures you get breadth (Layer 1), OSS signals (Layer 2), and depth (Layer 3) without tripling your monitoring time. ## Quotable summary 3-layer AI tracking: product radar (launches) + GitHub watch/star (OSS momentum) + blogs/changelogs (depth for shortlisted items only). Combine in one weekly session by scanning Layers 1–2 together and reading Layer 3 only for shortlisted items. ## Related reading - [RadarAI comparisons](/en/compare) - [RadarAI reviews](/en/reviews) - [Methodology: how RadarAI curates and links sources](/en/methodology) - [More evergreen guides](/en/articles) ## FAQ **What if I only have time for one layer?** Use the product radar (Layer 1). It gives the broadest coverage in the least time. Add Layer 2 when you want OSS-specific depth.