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Comment by sreekanth850 | Hacker News Reader

Anthropic had really screwed up after 4.6. i don't know if they work to satisfy their ego or for releasing a better model for tasks.

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After using Fable more extensively, I've found that it often is lazy or lies or tries to take shortcuts. For a company so sanctimonious about alignment, they seem to be the ones doing the worst at it.

Availability aside they've really made me appreciate OpenAI and cheer for other competitors in the marketplace even if I have mixed feelings about using Chinese models.

> I've found that it often is lazy or lies or tries to take shortcuts.

It's funny how Fable reflects the company that produced it.

There are whole sections of code work that 4.7+ can't do simply because it is both over fit and stubborn.

God save you if you have a company with narrow but correct technical tradeoffs, because you operate at scale.

Opus from 4.7 one will wreck your code and argue for hours with your engineers.

Certain parts of our company have had to mandate 4.6 and a training doc to explain why our current choice is both the cost efficient and performant one and shouldn't just be ripped out.

Newer models will re-litigate the same bad, known failed architectures over and over again.

Can you give some specific technical examples where 4.7+ are making the wrong architectural decisions?

This is exactly when I left claude and started using codex during April mid or so. It once argued with me and ran for 30 minutes with a half baked buggy fix.

Just recently went back to ChatGPT after abandoning it for Claude. I must say I was stunned at how good it had become and also how they introduced new product features that I really liked.

I wonder if from now on we have to switch providers every six months or so.

Every 3 months*

I've been bouncing between the two for years now with great success. It's easy for me because I don't use any of the skills, agent.md, or sort of custom instructions.

When it comes to most companies, there is no reward for loyalty.

skills and agent.md are very portable though? I figure at most, as the models get better, the only maintenance you need to do is pare them down to remove unnecessary context.

I mean, I wouldn't know how portable they are between models because I don't use them. I don't use them because, well, I don't need them. I mainly use LLMs as a StackOverflow replacement via the Web chatbots.

I only use CC or Codex for a quick MVP once every few months or so.

Clearly ego, you can always tell how full of themselves they are based on their media personalities going on the podcast circuit before product releases.

Agree. Opus 4.6 was the peak and after that they introduced the effort parameter and it was a downhill since then

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