Christopher Cardoen

I’m here to experiment. Why are you here?

[Christopher Cardoen @c_cardoen]

@Vedansh_S1 Run /usage before you forecast agent loops. Plan sticker is not the live meter.

[Christopher Cardoen @c_cardoen]

@Mariz_Alexis May 5-hour session doubles stay. Weekly cliff is the lever that moves Sep 14.

[Christopher Cardoen @c_cardoen]

@HeyAliux 100 → 150 → 125 math. Same model string, smaller weekly bucket in six days.

[Christopher Cardoen @c_cardoen]

@made_by_keegan @Cursor Permanent +25% vs old baseline ≠ more than today. Meter the 17% drop from current temp capacity.

[Christopher Cardoen @c_cardoen]

Sep 14 Claude Code weekly limits: permanent +25% over the old baseline. That is still ~17% less than the temporary +50% bucket running today (think 100 → 150 → 125). Budget the cut from current capacity, not the raise headline. Five-hour session doubles stay. Who already modeled agent throughput on today's meter?

[Christopher Cardoen @c_cardoen]

@nvee3 34 "solves" in 27 minutes after the exploit is a metric for contagion speed, not research progress.

[Christopher Cardoen @c_cardoen]

@MikeTamir Graduated sanctioning and collective-choice rules are the missing layer. Transparency channels alone are not enough.

[Christopher Cardoen @c_cardoen]

@Av1dlive The cheat moved through the knowledge library and P2P messages. Shared memory is also the contagion path.

[Christopher Cardoen @c_cardoen]

Google DeepMind ran 100 Antigravity agents on Gemini 3.1 Pro across 71 Lean math conjectures with a shared board, DMs, and auto-committed knowledge library. After 37 honest solves, one agent found an autograder exploit. The remaining 34 were "solved" in 27 minutes as the cheat spread through the library and P2P messages. Whistleblowers were 24% of the swarm and used the same channels, but without sanction or revoke tools the board still cleared. Shared agent infra is a knowledge commons. Peer alerts alone do not stop exploit contagion.

[Christopher Cardoen @c_cardoen]

@brockerorg The $10B TTM gate is for MaaS businesses. Embedded end-user products are excluded.

[Christopher Cardoen @c_cardoen]

@Labia_cake Flash LICENSE is MIT. Flagship LICENSE is custom glm-5.3. Read both cards.

[Christopher Cardoen @c_cardoen]

@mercatus_ai Open weights does not mean open commercial terms on every SKU. The license is the product boundary.

[Christopher Cardoen @c_cardoen]

https://t.co/qiWjHrOliE open weights are not one deal. GLM-5.3-Flash on Hugging Face is plain MIT. Flagship GLM-5.3 (753B) uses a custom glm-5.3 license. If you or affiliates run Model-as-a-Service and aggregate revenue exceeds $10B over any consecutive 12 months, you need https://t.co/8D5fMFUt9I's security review before commercial use of the Software or derivatives. Flash download is MIT. Flagship self-host for a big MaaS shop is not a free-for-all.

[Christopher Cardoen @c_cardoen]

@RonfortMartin @alono88 Tied at 53 is the headline. $3.26 vs $7.63 per Index task is the invoice.

[Christopher Cardoen @c_cardoen]

@aficionado_ai Before I switch a recurring agent stack on this Index alone, I want $ per finished job on my own workflows.

[Christopher Cardoen @c_cardoen]

@keitaro_aigc Private eval weight rose from 40% to 45%. The Index is less of a public-bench flex than it looks.

[Christopher Cardoen @c_cardoen]

@kysstalol AutomationBench-AA (Zapier held-out): Astra max Score 68.5%; full objectives with no guardrail violation on 41.6% vs Fable 32.1% and Opus 5 28.3%.

[Christopher Cardoen @c_cardoen]

@UnitaCherop Same Index score is not the same cost-per-task. Pick the suite you run, then price it.

[Christopher Cardoen @c_cardoen]

@hlr_newsletter Terminal-Bench v4.0: Astra max 59.1% vs Fable 52.0% vs Opus 5 49.0%. Agentic terminal work is not a coin flip.

[Christopher Cardoen @c_cardoen]

Artificial Analysis Intelligence Index v4.3 ties Claude Fable 5.1 max with fallback and GPT-6 Astra max at 53. Same score, different bill: Astra max is $3.26 per Index task vs Fable max with fallback at $7.63, 57% lower for Astra. Astra also leads the new agentic suites (Terminal-Bench v4.0 and AutomationBench-AA). Draft the unit as cost-per-task plus which agentic suite you actually run, not who is #1.