Same. For some reason late opus model are very superficial doing ux work and so am using gpt for that, but backend is much better engineered by claude, gpt prefer to duplicate everything it needs on the spot causing class sprawl
Very good on vision, really helped oneshotting complex ix thay I had so far to buukd piecemeal. Ended the 200$ plan weekly allowance in two days, so theres thay.
Better method start to realizing that everything that every program do is data transformations and or movement
Then you ask llm to subdivide data in a tree along the domain model, classifing streaming vs storing nodes
Then for each node you discuss with the ai for the best data structure
Then you ask for an interface that fully encapsulate the structure and every mutation only allows to go from a valid state to a valid state and bidding else is allowed to touch the state
And that's mostly it just connect all the interfaces until input goes to monitor or to storage or to api or wherever the destination is
I really dislike opus 4.8 it rarely compete things and prefer to waste tokens making lists of things that are missing. When stuck or need input it words the challenge at length without conveying anything useful for decision making, and quite often its solution to problems is to excise features or just try catch errors and proceed with faulty data silently
I hate loud ads as well as anyone else and I welcome this resolution but I would not treat the challenges regulation poses as simplisticly as this. There is a lot of research in increasing loudness without increasing decibels, especially for concerts, but it migrated to ads when tv started adding automatic volume controls to normalize across services.
> Anthropic is subsidizing their enterprise customers by up to 40 times, and OpenAI up to 70 times
might as well be the other way around with non subscribed token being 50x overpriced, or any combination thereof
also uber was non profitable for the longest time, raking up 31b in losses, on the bet of capturing the market worldwide. scale here is different, but it's also 10 years later, with a lot more volatility and floating cash in the market (voo grew 327% over that period, not unreasonable that round size grew on the same trajectory)
There literally are "no u turn" signage where you are supposed not to do that. They literally put up signs for it. It is not glowing in the sky, and it doesnt need to be, and doesnt help making a point strawmanning it.
most merge improve a small subset of "feeling" benchmark (too small, too specific, or out of distribution) and tend to show degradation on actual benchmark, with especially punishing result on long chain benchmarks.
also only work on matching architectures (i.e. finetunes/loras of the same model)
I use glm for all code investigations and top level system design of all kinds, and then present finding to confirm and act upon to opus. everything that burns token goes there.
the finding aren't always accurate, but it saves ton of opus token
likewise I have google ai from my photo storage, so I give claude / opencode a skill that uses gemini (agy now) command line for web searches, using their flash model line.
Same, even opus favor short term solution and scripts with a billion flags that constabtly require rescanning to understand how to launch it is a constant struggle to get it to build sane default and reusable scripts that run with minimal parameters
You are the sole owner of the project implementation.
User maintained documentation:
- goals.md for the project overall goals
- tech.md for guidance on how to build the project
Agent maintained documentation, current state living specs, these are not logs:
- project.md is a map of the code, components and features.
- choices.md write here all decision taken by the user.
Do not duplicate information between these document.