Model routing
Different tasks receive different execution policies instead of routing everything through one model path.
AI Radar
Evidence-aware intelligence for AI ecosystem decisions.
AI Radar turns messy AI ecosystem signals into structured insight, trend awareness, project judgment, and learning without letting weak evidence become automatic action.
Operating Model
Quality-controlled intelligence loop
Signal intake
Messy external and manual inputs enter one normalized review stream.
Evidence gate
Relevance is separated from evidence before downstream actions are allowed.
Project judgment
Project Takeaways move into Confirm, Watch, Action, Reject, or Dismiss.
Learning loop
ReviewRecords and CalibrationEvents become durable trajectory context.
Model routingClaim verificationBlocked actionsMetrics
Pipeline
Signal to learning, with gates between the steps.
01
Signal
External AI ecosystem events, uploads, repo activity, product launches, and friction reports.
02Insight
Structured interpretation: why it matters, project fit, career relevance, and synthesis.
03Trend
Topic momentum, rising themes, and repeated patterns across signals over time.
04Strategic Intelligence
Evidence-aware synthesis that connects market movement to active project judgment.
05Decision
Project Takeaways convert intelligence into confirm, watch, action, reject, or dismiss choices.
06Review
Human judgment records whether the system's interpretation was useful, weak, or wrong.
07Learning
ReviewRecords and CalibrationEvents become trajectory memory and project learning context.
Track AI ecosystem signals
Collect RSS, official sources, GitHub, Hacker News, Product Hunt, and manual material into one signal stream.
Open surfaceSeparate relevance from evidence
A signal can be strategically relevant while still too weak to support automatic action.
Open surfaceTurn intelligence into judgment
Project Takeaways make strategy reviewable, watchable, actionable, and learnable over time.
Open surfaceQuality Layer
The distinctive work happens below the visible workflow.
AI Radar is built to keep interpretation useful without treating every generated sentence as evidence.
Claim verification
Generated claims stay separate from source evidence and carry support labels before downstream use.
Blocked downstream actions
Weak evidence can enter Watch or Review, but it cannot quietly become low-risk Action.
Runtime metrics
Pipeline runs, collector runs, LLM calls, artifacts, and verification events are observable.
Work Surfaces
Open the product from the stage you need.
DashboardDaily operating cockpit for intake, review, and metrics.SignalsInspect signal detail, evidence grounding, and generated insight.RadarRead daily topic momentum and strategic priority output.KnowledgeReview convergence across supply-side and demand-side signals.Project ReviewConfirm, Watch, Action, Reject, or calibrate Project Takeaways.TrajectoryTrace how review and calibration history becomes learning.