Getting the UX to work well enough is a major challenge. I’m redesigning that currently, as I got negative feedback from early testers on my initial experimental UX. There’s a balance to be struck between giving users a low latency response, giving the models time to work together and call tools, and not overloading the user with too much information.

Many conflicting ideas are harder for models to follow than one large unified idea.

[0]: https://jeremyberman.substack.com/p/how-i-got-a-record-536-o...

For more up-to-date thoughts on thermodynamics I'd start here: https://writings.stephenwolfram.com/2023/02/computational-fo...

Slack integration, automatically pushing to CI, etc., are relatively low-value compared to the questions of “does it write better code than alternatives?”, “can I depend on it to solve hard problems?”, “will I still need a Cursor and/or ChatGPT Pro subscription to debug Devin’s mistakes?”

In my own experience using Cursor with Claude 3.5 Sonnet (new) and o1-preview, Claude is sufficient for most things, but there are times when Claude gets stumped. Invariably that means I asked it to do too much. But sometimes, maybe 10-20% of the time, o1-preview is able to do what Claude couldn’t.

I haven’t signed up for o1 Pro because going from Cursor to copy/pasting from ChatGPT is a big DevX downgrade. But from what I’ve heard o1 Pro can solve harder coding problems that would stump Claude or o1-preview.

My solution is just to split the problem into smaller chunks that make it tractable for Claude. I assume this is what Devin’s doing. Or is Devin using custom models or an early version of the o1 (full or pro) API?

After about an hour with Windsurf, I find myself frustrated with how it deals with context. If you add a directory to your Cascade, it's reluctant to actually read all the files in the directory.

I understand that they don't want to pay for a ton of long-context queries, but please, let users control the context, and pass the costs to the user.

It's very annoying to have the LLM try to create a file that already exists, it just didn't know about it.

Also, comments on the terminal management reflect a real issue. One solution is to expose the Cascade terminal to the user, letting the user configure the terminal in a working state, so that it has access to the correct dependencies and the PATH is properly sourced.

Envy is insidious. Focusing on how other people have unfair advantages eats away at your principles, motivation, creativity, and presence of mind to capture the opportunities available to you.

As a founder myself, I appreciate the fact that it's so easy (for some people) to raise money. It means that the competition is softer than it seems.

Since the launch of Claude 3 Opus, and then Claude 3.5 Sonnet, they have been significantly behind Anthropic in terms of the general intelligence of their models. And instead of deploying something on par or better, they are making demos of video generation (Sora) or audio-to-audio models, not releasing anything.

GPT-4o is quite bad at coding, often getting stuck in a loop, and “fixing” buggy code by rewriting it without any changes.

GPT-4o is speculated to be a distillation of a larger model, and now GPT-4o-mini is an even dumber smaller model. But what’s the point?

Who is actually using small/fast/cheap/dumb models in production apps? Most real apps require higher reliability than even the biggest/slowest/priciest/smartest models can provide today. For the use case of transformers that has taken off, aiding students and knowledge workers in one-off tasks like writing code and prose, most users want smarter, more reliable outputs, even at the expense of speed and cost.

GPT-4o-mini seems like a move to increase margins, not make customers happier. That, like demoing products without launching them, is what big old slow corporations do, not how world-leading startups operate.

This conflict does not exist to nearly the same degree in families without wealth to inherit, and in cultures that respect the wisdom of one’s elders; rejection of one’s elders/youth worship is one value that millennial Americans inherited from Baby Boomers.

As to the emails, Clegg was right when he said this:

> For Millennials, authenticity, agency, autonomy, idealism, altruism etc all seem to be top of their list of desirable virtues – for better or worse, they are difficult to reconcile with Silicon Valley these days.

Well, it’s worse, not better.

Anyway, this kind of self-conscious persona-construction is opposite to what millennials vibe with. No matter how much Zuck styles himself like a rapper or athlete, he only appeals to boomer or at best Gen X sensibilities. This is great for META stock price, but doesn’t make Zuck appealing to millennials.

When I stopped taking creatine, I did lose a few reps in all my lifts; it does work.

Eg trading, investing, entrepreneurship, working as an in-house economist bound by NDAs.

I don't care if the model can tell me which page in the book or which code file has a particular concept. RAG already does this. I want the model to notice how a concept is distributed throughout a text, and be able to connect, compare, contrast, synthesize, and understand all the ways that a book touches on a theme, or to rewrite multiple code files in one pass, without introducing bugs.

How does Gemini 1.5's reasoning compare to GPT-4? GPT-4 already has superhuman memory; its bottleneck is its relatively weak reasoning.

Quora has long been a world leader of SEO and dark UX patterns — it was never as valuable to users as its Google ranking would indicate — so it’s hard to mourn its demise. But yes, it does stink to see the quality of information going down while the quantity grows at an ever-increasing exponential rate.

The GPT-4 API costs significantly more than the $20/mo ChatGPT Plus subscription, but it does have benefits. Namely, 128k tokens of context with the latest GPT-4-turbo model, so you can put a whole (small) software project or a short book into your prompt.