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> I know I could be eating my words, but there is basically no evidence to suggest it ever becomes as exceptional as the kingmakers are hoping.

??? It has already become exceptional. In 2.5 years (since chatgpt launched) we went from "oh, look how cute this is, it writes poems and the code almost looks like python" to "hey, this thing basically wrote a full programming language[1] with genz keywords, and it mostly works, still has some bugs".

I think the goalpost moving is at play here, and we quickly forget how 1 year makes a huge difference (last year you needed tons of glue and handwritten harnesses to do anything - see aider) and today you can give them a spec and get a mostly working project (albeit with some bugs), 50$ later.

[1] - https://github.com/ghuntley/cursed



I don't disagree with you on the technology, but mostly my comment is about what the market is expecting. With such a huge capex expenditure it is expecting a huge returns. Given AI has not proven consistent ROI generally for other enterprises (as far as I know), they are hoping for something better than what is right now and they are hoping for it to happen before the money runs out.

I am not saying it's impossible, but there is no evidence that the leap in technology to reach wild profitability (replacing general labour) such investment desires is just around the corner either.


After 3 years, I would like to see pathways.

Let say we found a company that already realized 5-10% of savings in the first step. Now, based on this we might be able to map out the path to 25-30% savings in 5% steps for example.

I personally haven’t seen this, but I might have missed it as well.


Three years? One year ago I tried using LLMs for coding and found it to be more trouble than it was worth, no benifit in time spent or effort made. It's only within the past several months that this gas changed, IMHO.


To phrase this another way, using old terms: We seem to be approaching the uncanny valley for LLMs, at which point the market overall will probably hit the trough of disillusionment.


It doesn't really matter what the market is expecting at this point, the president views AI supremacy as non-negotiable. AI is too big to fail.


It’s true, but not just the presidency. The whole political class is convinced that this is the path out of all their problems.


...Is it the whole political class?

Or is it the whole political party?


I am not from the US, but your administration could still fumble the AI bust even if it wants to avoid it. Who knows maybe they are hoping to short it.


That there is a bubble is absolutely certain. If for no other reason, than because investors don't understand the technology and don't know which companies are for real and which are essentially scams, they dump money into anything with the veneer of AI and hope some of it sticks. We're replaying the dotcom bubble, a lot of people are going to get burned, a lot of companies will turn out to be crap. But at the end of the dotcom crash we had some survivors standing above the rest and the whole internet thing turned out to have considerable staying power. I think the same will happen with AI, particularly agentic coding tools. The technology is real and will stick with us, even after the bubble and crash.


I feel like the invention of MCP was a lot more instrumental to that than model upgrades proper. But look at it as a good thing, if you will: it shows that even if models are plateauing, there's a lot of value to unlock through the tooling.


> it shows that even if models are plateauing,

The models aren't plateauing (see below).

> invention of MCP was a lot more instrumental [...] than model upgrades proper

Not clear. The folks at hf showed that a minimal "agentic loop" in 100 LoC [1] that gives the agent "just bash access" still got very close to SotA with all the bells and whistles (and surpassed last year models w/ handcrafted harnesses).

[1] - https://github.com/SWE-agent/mini-swe-agent


Small focused (local) model + tooling is the future, not online LLMs with monthly costs. Your coding model doesn't need all of the information in the world built in, it needs to know code and have tools available to get any information it needs to complete its tasks. We have treesitter, MCPs, LSPs, etc - use them.

The problem is that all the billions (trillions?) of VC money go to the online models because they're printing money at this point.

There's no money to be made in creating models people can run locally for free.


I mean, that's still proving the point that tooling matters. I don't think his point was "MCP as a technology is extraordinary" because it's not.


MCP is a marketing ploy, not an “invention”.


It is an actual invention that has concrete function, whether or not it was part of a marketing push.


I didn't realize generating the gen-z programming language was a goalpost in the first place




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