i_have_an_idea

ArtificialAnalysis are famous Anthropic fanboys.

You just discovered the SaaSpocalypse that began around January this year.

I am currently working with a non-dev startup CEO that's fully embraced Claude Code and vibe coding.

90% of my work is to run code review workflows and steer his CLAUDE.md into the correct architecture choices and away from past mistakes.

So far it's working pretty well -- I'm able to unslopify the code and maintain the agent's performance. And the CEO is happy, he's able to develop his product pretty fast and not hit any walls.

In my experience, the delta in agent performance is substantial if the codebase is littered with dead code, redundant code, unreachable fallbacks, leaking abstractions and half-baked design patterns vs if the code is well-organized, with clear data flow, with good encapsulation and clean architecture. Like, I've seen all the frontier models have to do several rounds of code review / QA and fix when the code is bad vs just getting it right at the 1st/2nd attempt.

This is like what you can setup with Hermes or OpenClaw within a few minutes with your ChatGPT subscription or an open weights model, except they handle the Slack setup for you and bill you at API rates.

Just because it is performing rather poorly by comparison, it doesn’t mean it isn’t benchmaxxed. It can still be worse than it appears.

Is it a frontier player though, or perhaps a new benchmaxxed model? People were saying similar things about Grok but it ultimately amounted to little.

maybe it was coded by Claude

so, at a 8% discount at current prices.

What if you substituted "steel" with "asbestos" in your argument.

Dude, the agent didn't 'confess' anything. It doesn't understand anything, it's just fancy autocomplete. It's a math function we've armed with tools.

Yes that can be very useful, and can speed you up a lot. But someone must check the output.

If you let it operate on a prod system and it messed up, it's on you.

vim

That's true, but a lot of these people are also competitors. I can't imagine it'll be attractive going to the OpenAI media channel to talk about Gemini or Grok.

To be honest, until a month ago, I hadn't even heard of TBPN or seen any of their content. But, seemingly, out of nowhere, they managed to get all the leaders in AI to appear in their programming.

The core of the information they present isn't much different than what you'd hear on Dwarkesh or other industry podcasts, the presentation is some weird mix of ESPN and Mad Money that I personally don't get, but maybe makes sense to a US audience.

I don't see why that is interesting to OpenAI, but maybe I'm missing something.

will all my custom Wordpress themes and plugins run on EmDash?

For what is worth, Codex would be able to fix that. Claude is pretty bad at backend / architecture.

I thought about it for a moment, but the real reason I got the new M5 Pro with 64GB is to be able to run several large projects concurrently in Docker envs.

I didn't go for a Max chip because I value the better battery life on the Pro more than I value the additional GPU cores.

Personally, I think until the LLMs start to plateau, it will always be more valuable to run a frontier LLM vs just a very capable local LLM. I have no idea when that will happen, so I simply decided to not overbuy the hardware now.

> i just gave my favorite LLM a screenshot of one of those components and it recreated it perfectly. i paid $0.

Because it's most likely in the training data. I.e., it stole it for you.

this seems like a crazy idea as the cli client has nothing to do with how many tokens per second the api streams

if the quality of search results today is anything to go buy -- clearly no

> I've consistently found Gemini to be better than ChatGPT [ because ] Google has crawled the internet so they have more data to work with.

This commonly expressed non-sequitur needs to die.

First of all, all of the big AI labs have crawled the internet. That's not a special advantage to Google.

Second, that's not even how modern LLMs are trained. That stopped with GPT-4. Now a lot more attention is paid to the quality of the training data. Intuitively, this makes sense. If you train the model on a lot of garbage examples, it will generate output of similar quality.

So, no, Google's crawling prowess has little to do with how good Gemini can be.

To be honest, no. It would just disappoint me as a customer and make me switch to a much cheaper Android.

My biggest issue with iOS 26 is not the UI (it’s subpar compared to prior work), but the fact that it drains my battery 2x faster than before and I’m with an iPhone 16 Pro. That’s unacceptable performance degradation on a 1-year old phone.

Sounds nice, in theory, but in practice I want to iterate on one, perhaps, two tasks at a time, and keep a good understanding of what the agent is doing, so that I can prevent it from going off the rails, making bad decisions and then building on them even further.

Worktrees and parallel agents do nothing to help me with that. It's just additional cognitive load.

While this is cool, can anything be done about the speed of inference?

At least for my use, 200K context is fine, but I’d like to see a lot faster task completion. I feel like more people would be OK with the smaller context if the agent acts quickly (vs waiting 2-3 mins per prompt).

This sounds like the programmer equivalent of astrology.

> Build context for the work you're doing. Put lots of your codebase into the context window.

If you don’t say that, what do you think happens as the agent works on your codebase.

> But honestly what are the examples of people losing their jobs to software ?

Bank tellers

Travel agents

Cashiers

Bookkeeping clerks

Typists

Most recently, AI helped me salvage and refactor a giant and completely mismanaged outsourced rewrite of a popular niche site.

Without it, the site would suffer a slow and painful death in the SERPs and would lead to about 10MM annual loss for the company.

Starting from scratch with a proper, qualified team was not possible for political reasons.

So, being able to do it as a single person, with heavy AI assistance, is a huge win.

Sadly, I don't think this astroturfing is limited to announcement threads. It seems it is becoming increasingly hard to source real human opinions online, even on specialized forums like this or Reddit communities.

I hope that I am wrong, but, if I am not, then these companies are doing real and substantial damage to the internet. The loss of trust will be very hard to undo.

The most alarming to me thing is that it seems to be happening at scale. This is one of dozens similar posts I've seen all over the programming communities with similar characteristics (high praise, new-ish accounts, little if any other activity).