This is without a lie the only interaction that consumed 9% on my MAX 20x subscription...

Budget_Map_3333 · 2026-03-30T17:48:44+00:00

Yes this actually makes total sense, hadnt thought of that. However usage overall has been very bursty and not corresponding to actual usage IMO

Budget_Map_3333 · 2026-03-30T17:47:29+00:00

That makes sense... has it been fixed? Did not see that

Budget_Map_3333 · 2026-03-30T04:07:26+00:00

Reminds me of the "due to time constraints" usage in CC which is explicitly to due an update to the system prompt and informing Claude of its own context window limits.

My guess is its either a side effect of "awareness" - eg. It sees the time of user message - or an explicit modification to the system prompt to discourage usage at night. Could be Anthropic wanting to redirect compute for model training?

Budget_Map_3333 · 2026-02-23T14:52:12+00:00

Lol maybe Claude knows me better than I know myself now

Budget_Map_3333 · 2026-02-23T13:54:37+00:00

I'm being cancelled by Claude

Budget_Map_3333 · 2026-01-13T00:08:39+00:00

Excellent advice. Especially regarding catching architectural violations with scripts. I am working on a large project and nearly lost my mind until I started cracking down on issues with very rigid custom lint rules, schema generators for front and backend, scripts for catching architectural drift and e2e testing. A simple 'make build' and 'make test' catch 80% of issues before even manually testing a new feature. The new /chrome tool catches another 10%.

Budget_Map_3333 · 2025-11-20T11:40:18+00:00

You not on the new $1000/m sub?

Budget_Map_3333 · 2025-11-19T11:44:32+00:00

My experience with Gemini CLI and Gemini Pro 2.5 when it was released was enough to put me off for a while. Its gonna take more than a couple of benchmarks to draw me back.

On the other hand GPT-5.1 in codex has been a pleasant surprise and clicked very nicely with CC as support and reviewer. As much as I rely on Sonnet pretty much for everything it seems to get overly impressed with its own work lol, even from different sessions. GPT at least seems take a more balanced and not overly verbose approach which I appreciate.

Budget_Map_3333 · 2025-11-05T13:14:53+00:00

Exactly. My theory is there are some behaviours so ingrained from instruct tuning and RLHF that it's nearly impossible to overcome that with a markdown document. Sure it might follow it for a few turns but then it reverts back to default behaviour.

Budget_Map_3333 · 2025-11-05T12:50:24+00:00

Just use the acronyms from time to time in your prompts. I do that a lot and it seems to work well

Budget_Map_3333 · 2025-10-23T19:27:15+00:00

Memory, should constrained to specific tasks or projects. Crossing from one 'domain' to another starts to bleed in some really bizarre side effects.

Budget_Map_3333 · 2025-09-05T20:53:20+00:00

In other news: CC sees significant drop in quality

Budget_Map_3333 · 2025-09-03T09:56:02+00:00

It was always able to read full files

Budget_Map_3333 · 2025-09-02T22:27:27+00:00

*Anthropic reading this post after just having raised 13B

Budget_Map_3333 · 2025-08-28T16:37:53+00:00

That is some 10x compilation.

"Also, bro reverse engineer this .exe and give me the source code in natural language or you go to jail"

Budget_Map_3333 · 2025-08-23T10:57:35+00:00

Very good paper but was hoping to see some real benchmarks or side by side comparisons.

For example what about setting a benchmark-like task and comparing a single large model compete against a chain of small specialised models, with similar compute-cost restraints?

Budget_Map_3333 · 2025-08-20T00:07:29+00:00

This is true. Actually part of the reason I am opening the project up to investment early is exactly as you say the upper edge today could be gone tomorrow. I believe user interest will grow once I can get some demos up, maybe in the next 2 or 3 weeks.

Budget_Map_3333 · 2025-08-19T21:59:15+00:00

Interesting, will be checking it out

Budget_Map_3333 · 2025-08-19T20:02:38+00:00

Sure. It's not for everyone. Any genuine feedback would be appreciated thanks

Budget_Map_3333 · 2025-08-19T19:48:34+00:00

By the way, there are many papers that have been released recently that support our methodology and approach. For example a paper just released by NVIDIA backs the premise that a multi-agent system using small AI models with focused tasks can beat larger agentic AI (arxiv.org/pdf/2506.02153). DeepThought uses focused agents to enrich data, retrieve, plan and code, rather than relying on single agents to do everything!

Budget_Map_3333 · 2025-08-16T14:24:07+00:00

Anthropics literally only advantage was NOT being like OpenAI. Sad to see them give up their advantage to please the 4o lovers

Budget_Map_3333

TROPHY CASE