/goal is a gimmick where you run a "parent" agent on top that runs the agent on a loop until the it decides to stop, just prompting it "nope, not done yet, continue".

But openai's chance of a moat on model quality is dropping as we go, not increasing

Github is struggling because of compute, which comes from everyone vibecoding and triggering actions 10x more.

I can vibecode an alternative, but once i have users, who is going to secure this amount of compute? Compute+talent to manage it(devops isnt vibecoded *yet) is a moat

Joking, but its a very good idea. Synchronization between the physical world information and digital has been a very hard problem for decades and im sure an agentic approach can 10x the value.

How granular can you get the source data attribution? Down to individual let's say Wikipedia topics? Probably not urls?

Would be interested to see this scale to 30/70b

Even this is hard. Most people don't know what they want, and/or they don't know how to describe it/imagine it. They don't even know what a trend graph is.

They just want someone else to do the mental effort of creating a nice product. Hence iOS > android for most people. They don't want to customise basically anything other than colours.

That's why i predict Lovable/replit etc will not go mainstream. And why chatgpt will just offer you their UIs mainly. Artifacts weren't a big hit

Agree, and it's a nice reflection of the individual companie's goals. OpenAI is about AGI, and they have insane pressure from investors to show that that is still the goal, hence codex when works they could say look it worked for 5 hours! Discarding that 90% of the time it's just pure trash.

While Anthropic/Boris is more about value now, more grounded/realistic, providing more consistent hence trustable/intuitive experience that you can steer. (Even if Dario says the opposite). The ceiling/best case scenario of a claude code session is a bit lower than Codex maybe, but less variance.

> Zebra-Llama is a family of hybrid large language models (LLMs) proposed by AMD that...

Hmmm

But, assuming you are trying to be in between lovable and google, how are you not going to be steamrolled by google or perplexity etc the moment you get solid traction? Like, if your insight for v3 was that the model should make its own tools, so even less hardcoded, then i just dont see a moat or any vertical direction. What really is the difference?

Additionally, depending on round, they also have multiples, like 2x meaning they get at least 2x their investment before anyone else gets anything

On the application layer, connecting with sandboxes/VM's is one of the biggest shifts. (Cloudfares codemode etc). Giving an llm a sandbox unlocks on the fly computation, calculations, RPA, anything really.

MCP's, or rather standardized function calling is another one.

Also, local llm's are becoming almost viable because of better and better distillation, relying on quick web search for facts etc.

Comments URL: https://news.ycombinator.com/item?id=45946626

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