Benchmark Radar Day 10: AI Briefing, GPT Insight, and Launch Prep
Published:
The radar started talking. Day ten added AI-generated briefings, GPT-powered insights, and launch copy for Chinese social platforms.
Author: Koutian Wu; GitHub: ktwu01
What shipped
Bounded daily AI briefing. A new feature generates a daily briefing from the radar’s findings. The briefing is bounded to fit within token budgets and does not truncate mid-sentence.
GPT radar insight. Evidence-rich insights are now generated by GPT, with each claim linked to specific evidence sources. The briefing includes the temporal collection context (when data was gathered, what window it covers).
OpenAI rate limit handling. Rate limit errors from the OpenAI API are now diagnosed and retried with exponential backoff. Truncated API error responses are contained instead of crashing the pipeline.
Token budget fitting. The insight packet is fitted to the token rate budget, preventing truncation at the API boundary.
Briefing evidence links. The homepage briefing now links to cited evidence. Evidence details are collapsed by default to keep the page scannable.
Daily findings ranking. Findings are ranked by how much a reader learns from them, not just recency. The largest drops in the selection funnel are attributed.
Eligible record retention. Records below the recommendation threshold are retained if they meet eligibility criteria, preventing unnecessary data loss.
Archive-wide observation rendering bounded. The rendering of observations across the full archive is now bounded to prevent performance issues.
Scan date filter fix. The filter now allows showing all dates, not just individual ones.
URL parameter fix. The automatic frontier is kept out of shared URLs to prevent confusing recipients.
Launch copy. Launch posts were drafted for Chinese social platforms. The Xiaohongshu draft was made publishable with appropriate score caveats.
Why it matters
The daily briefing was the first output that a human could read without opening the dashboard. It transformed the radar from a tool you visit into a tool that visits you. The GPT insight layer added interpretation on top of data: not just “these benchmarks were collected” but “here is what changed and why it matters.”
The rate limit handling was a production necessity. OpenAI’s API has per-minute token limits. Without retry logic, a single rate limit error would kill the entire daily briefing run.
Issues addressed
- #121: bounded daily AI briefing
- #125: Sources panel collapsed when connectors fail
- #126: Semantic Scholar search request fix
- #128: persist daily briefing on dashboard
- #130: compute daily findings
- #131: rank findings by learning value
- #132: URL and filter fixes (issues 123, 129)
- #133: attribute largest funnel drop
- #135: retain eligible records
- #136: name evidence in daily findings
- #138: GPT radar insight
- #139: OpenAI rate limit handling
- #140: token budget fitting
- #141: briefing output truncation fix
- #142: briefing evidence links
- #143: collapse briefing evidence details
Day eleven: KW-Bench capability layer and community launch.