OpenAI engineer Tibo told Astra users they fixed quality regressions: prior-model skills firing too often, an opt-in context-management experiment causing early stops/old-message replies (~4–5k users; now disabled), and badly configured engines hurting a long tail of traffic. Follow-through and latest-message tracking should feel better, with a reset landing by midnight.

Key Takeaways

  • ✓Fixed prior-model skills misfiring and blocking self-checks.
  • ✓Disabled opt-in context-management experiment (~4–5k users hit by early stops/old replies).
  • ✓Removed bad engines; better follow-through/latest-message tracking; reset by midnight.
⚡

Key Decision Metrics at a Glance

TL;DR Verdict
🏆 Benchmark RankRank
See how it ranks on the leaderboard
Full Leaderboard→
💰 Cost & PlansCompare
GPT-6 Astra · in: $10 / out: $50
Compare Plans↗
🛠️ Ecosystem & IDERules
Astra · GPT-6 · Quality
Setup IDE Rules↗
🧭

Turn your technical choice into a development budget

Compare 40 dev plans & simulate token costs vs $20/mo subscriptions

⚔️ Compare Model→💰 Compare plans & limits↗
Action HubReady to adopt this in production?

Benchmark side-by-side against alternatives, or calculate monthly token cost vs subscription break-even.

⚔️ Launch VS Compare→💳 View Plans↗
Up NextOpenAI: get more from GPT-6 Astra by rethinking skills, AGENTS.md, and task prompts
Read Now→