151–160 of 212 posts
Why is this post published in November 2025 talking about GPT-4? I'm suspicious of their methodology: > Open DevTools (F12), go to the Network tab, and interact with their AI feature. If you see: api.openai.com, api.anthropic.com, api.cohere.ai You’re looking at a wrapper. They might have middleware, but the AI isn’t theirs. But... everyone knows that you shouldn't make requests directly to those hosts from your web…
A long time ago a mentor of mine said, "In tech, often an expert is someone that know one or two things more than everyone else. When things are new, sometimes that's all it takes." It's no surprise it's just prompt engineering. Every new tech goes that way - mainly because innovation is often adding one or two things more the the existing stack.
I'm always more interested in the 'less is more' strategy, taking things away from the already hyper-complicated stack, reviewing first principles and simplifying for the same effectiveness. This is ever more rare.
But ... what else should they be doing? What's the expectation here? For example, in the 90's, a startup that offered a nice UI for a legacy console based system, would have been a great idea. What's wrong with that?
IMO nothing wrong with it. Just misleading to call yourself an AI company when you actually make a CRUD app. I think if these companies were honest about what they’re doing nobody would be upset. There’s an obvious deliberate attempt to give an impression of technical complexity/competence that isn’t there. I assume it works because the ecosystem is, as you say, so new. Non-technical observers have trouble distinguis…
But ... what else should they be doing? What's the expectation here? For example, in the 90's, a startup that offered a nice UI for a legacy console based system, would have been a great idea. What's wrong with that?
But ... what else should they be doing? What's the expectation here? For example, in the 90's, a startup that offered a nice UI for a legacy console based system, would have been a great idea. What's wrong with that?
IMO nothing wrong with it. Just misleading to call yourself an AI company when you actually make a CRUD app. I think if these companies were honest about what they’re doing nobody would be upset. There’s an obvious deliberate attempt to give an impression of technical complexity/competence that isn’t there. I assume it works because the ecosystem is, as you say, so new. Non-technical observers have trouble distinguis…
The thing that annoys me is when clearly non-AI companies try to brand themselves as AI: like how Long Island Iced Tea tried to brand themselves as a blockchain company or WeWork tried to brand themselves as a tech company.
If we’re complaining about AI startups not building their own in house LLMs, that really just seems like people who are not in the arena criticizing those who are.
Earlier quoted context omitted.
> Yeah, TBH my BS detector is going off because this article never explains how he is able to intercept these calls. You mean, except for explaining what he's doing 4-5 times? He was literally repeating himself restating it. Half the article is about the various indicators he used. THERE'S EXAMPLES OF THEM. There's this bit: > Monitored their network traffic for 60-second sessions > Decompiled and analyzed their Java…
> Monitored their network traffic for 60-second sessions How can he monitor what's going on between a startup's backend and OpenAI's server? > The truth is just an F12 away That's just not how this works. You can see the network traffic between your browser and some service. In 12 cases that was OpenAI or similar. Fine. But that's not 73%. What about the rest? He literally has a diagram claiming that the startups con…
Presumably OpenAI didn't add that for fun, either, so there must be non-zero demand for it.
For me, 2023 was an entire year of weekly demos that now looking back at were basically a "Look at this dank prompt I wrote" followed by thunderous applause from the audience (which was mostly, but not exclusively, upper management) Hell man, I attended a session at an AWS event last year that was entirely the presenter opening Claud and writing random prompts to help with AWS stuff... Like thanks dude... That was a…
When you press them on this, they have all sorts of ideas like a judge LLM that takes the outputs, comes up with modified SOPs and feeds those into the prompts of the mixture-of-experts LLMs. But I don't think that works, I've tried closing that loop and all I got was LLMs flailing around.
Prompt engineering and using an expensive general model in order to prove your market, and then putting in the resources to develop a smaller(cheaper) specialized model seems like a good idea?
Are people down to have a bunch of specialized models? The expectation set by OpenAI and everyone else has set is that you will have one model that can do everything for you. It’s like how we’ve seen basically all gadgets meld into the smart phone. People don’t have Garmin’s and beepers and clock radios anymore (or dedicated phones!). It’s all on the screen that fits in your pocket. Any would-be gadget is now just an…
Earlier quoted context omitted.
If tekens aren't profitable then prices per token are likely to go up. If that's all these businesses are, they're all very sensitive to token prices.
Not with open weight models you can deploy yourself. Different economics but not venerable to price increases.
Burning VC money isn't a long term business model and unless your business is somehow both profitable on Llama 8b (or some such low power model) _and_ your secret sauce can't be easily duplicated, you're in for a rough ride.
The only barrier between AI startups at this point is access to the best models, and that's dependent on being able to run unprofitable models that spend someone else's money.
Investing in a startup that's basically just a clever prompt is gambling on the first mover's advantage because that's the only advantage they can have.
LLMs is the new AJAX. AJAX made pages dynamic, LLMs make pages interactive.