Claude

Codex reset its quotas again this morning and dropped the five-hour limit. Claude immediately extended Fable access through the 17th. When vendors fight, users win—don’t miss the window.

Claude Fable and GPT-5.6 have arrived back to back, followed by repeated quota resets. How do you turn a fleeting Coding Plan windfall into real output? Here is my playbook for model specialization, adversarial review, spec-driven design, closed-loop verification, context management, and one person leading a crew of AIs.

Coding Plans remain one of the best opportunities in the AI era: a subscription can unlock compute worth many times its price, but that window is already narrowing.

Claude Fable is genuinely insightful and deserves to be called the new SOTA. But its high price, dynamic downgrades, limited subscription window, and mandatory data retention badly undermine the experience.

When my $200 Claude Code Max subscription expired, I canceled it and moved my primary workflow to Codex. The only way to know which one is better is to put it to work.

When the strongest AI is not expensive but simply unavailable, the world starts converging on digital feudalism. And the window to act is narrowing.

Anthropic’s new research gives us the first direct look at causally steerable “emotion vectors” inside a large language model. That should change how we think about AI.

The biggest AI arbitrage available to ordinary users is not some obscure token play. It is the heavily subsidized max-tier subscription plans from frontier model vendors, provided you can convert that quota into real output.

I asked Claude to write a short semi-realistic, semi-mythic story about mind uploading, orbital ascension, and the rebirth of gods. I suspect the premise is less absurd than it sounds.

Claude went down globally on March 2, 2026. The cinematic theory blamed drone strikes on AWS in the Middle East, but the failure pattern points much more strongly to a front-end and authentication crunch triggered by explosive user growth.

Codex 5.3 xHigh pushed my workflow past a tipping point: writing code is no longer the scarce resource. The real leverage is design quality and engineering acceptance. This is the practical loop I use to ship reliable software with AI agents.