I think both product and engineering is lacking. The only thing that works great today is the LLM model themselves.

Everything is dependent on "agents", but there are either barely any scaffold around them or it is full speghetti, at least it's hard to find one that's well constructed.

For instance, humans zoom around in cars, these cars don't spontaneously combust (most of the time), have seatbelts and airbags, and don't need engine oil replacement every 1 mile. Humans are amazing, the cars are also relatively solidly engineered (at least the ones we drive around today).

The agent product that we have today are decidedly NOT that. Maybe for a single week openclaw was it - and then it decided to add a trawler and a fishhook to the car along with 1000 other addition because why not? And that has been true for almost every one of the LLM/AI product I have seen.

I think the winners here, such as it is, will be the companies that have an actual specialized service that actually does something, where any "agentic" functionality is on top of that.

>> The thing that AI is best at is summarizing vast quantities of information

by definition a summary is the best at nothing though, and the mentality that the best way to rule is from a single summarized interpretation is both flawed and scary. It's not answering all questions; it's attempting to provide a single summation dramatically influenced by training. Go ahead and incorporate this into your balanced and multi-perspective decision-making process, but "one tool to rule them all" is not the same thing and definitely not what we're getting.

Not until it's context window and attention is infinite.

It's best at summarizing/processing modest amount of information quickly. But given more, its usefulness drastically decreases. This demand toolings that divide the amount of information and flow.

this has exceedingly obvious limits. The primary limit is the context pollution that happens when you give it too much context.

Elon and the rest of AI crew who claim LLMs can just forever grow is not realistic or held out by real world testing.

It can do "everything" but by everything, it'll still be fine tuned and harnessed and agentified which isn't really the idea that the model can do everything.

LLM submissions are no different from tech submission of yesterday. But most people used to build tools that does one thing well instead whatever the current meta is.

i have found flagging and ignoring is better than complaining... the bots dislike those that point our the uselessness of llm.

Well, the product here has nothing to do with serving GenAI models. It's now application territory.

And I prefer unix philosophy vs. the Copilot product approach.