First, we currently have 4 frontier labs, and a bunch of 2nd tier ones following. The fact that we don't have just oAI or just Anthropic or just Google is good in the general sense, I would say. The 4 labs racing each other and trading SotA status for ~a few weeks is good for the end consumer. They keep each other honest and keep the prices down. Imagine if Anthropic could charge 60$ /MTok or oAI could charge 120$ /MTok for their gpt4 style models. They can't in good part because of the competition.

Second, there's a bunch of labs / companies that have released and are continuing to release open mdoels. That's as close to "intelligence on tap" as you can get. And those models are ~6-12 months behind the SotA models, depending on your usecase. Even though the labs have largely different incentives to do so, a lot of them are still releasing open models. Hopefully that continues to hold. So not all control will be in the hands of big tech, even if the "best" will still be theirs. At some point "good enough" is fine.

There's also the thing about geopolitics being involved in this. So far we've seen the EU jumping the gun on regulation, and we're kinda sorta paying for it. Everyone is still confused about what can or cannot be done in the EU. The US seems to be waiting to see what happens, and China will do whatever they do. The worst thing that can happen is that at some point the big players (Anthropic is the main driver) push for regulatory capture. That would really suck. Thankfully atm there's this lingering thinking that "if we do it, the others won't so we'll be on the back foot". Hopefully this holds, at least until the "good enough" from above is out :)

Copyright law, education, just the sheer scale of things changing because of LLMs are some things off the top of my head why "power tools vs carpentry" is a bad analogy.

I beg to differ. There are a whole lot of folks with astonishingly incomplete understanding about all the facts here who are going to continue to make things very, very complicated. Disagreement is meaningless when the relevant parties are not working from the same assumption of basic knowledge.

"Anti-LLM sentiment" within software development is nearly non-existent. The biggest kind of push-back to LLMs that we see on HN and elsewhere, is effectively just pragmatic skepticism around the effectiveness/utility/ROI of LLMs when employed for specific use-cases. Which isn't "anti-LLM sentiment" any more than skepticism around the ability of junior programmers to complete complex projects is "anti-junior-programmer sentiment."

The difference between the perspectives you find in the creative professions vs in software dev, don't come down to "not getting" or "not understanding"; they really are a question of relative exposure to these pro-LLM vs anti-LLM ideas. Software dev and the creative professions are acting as entirely separate filter-bubbles of conversation here. You can end up entirely on the outside of one or the other of them by accident, and so end up entirely without exposure to one or the other set of ideas/beliefs/memes.

(If you're curious, my own SO actually has this filter-bubble effect from the opposite end, so I can describe what that looks like. She only hears the negative sentiment coming from the creatives she follows, while also having to dodge endless AI slop flooding all the marketplaces and recommendation feeds she previously used to discover new media to consume. And her job is one you do with your hands and specialized domain knowledge; so none of her coworkers use AI for literally anything. [Industry magazines in her field say "AI is revolutionizing her industry" — but they mean ML, not generative AI.] She has no questions that ChatGPT could answer for her. She doesn't have any friends who are productively co-working with AI. She is 100% out-of-touch with pro-LLM sentiment.)

But if you do want to use LLMs for coding now, not using the best models just doesn't make sense.

I think you (and others) might be misunderstanding his statement a bit. He's not saying that using an old model is harmful in the sense that it outputs bad code -- he's saying it's harmful because some of the lessons you learn will be out of date and not apply to the latest models.

So yes, if you use current frontier models, you'll need to recalibrate and unlearn a few things when the next generation comes out. But in the meantime, you will have gotten 8 months (or however long it takes) of value out of the current generation.

Using agents that interact with APIs represents people being able to own their user experience more. Why not craft a frontend that behaves exactly the the way YOU want it to, tailor made for YOUR work, abstracting the set of products you are using and focusing only on the actual relevant bits of the work you are doing? Maybe a downside might be that there is more explicit metering of use in these products instead of the per-user licensing that is common today. But the upside is there is so much less scope for engagement-hacking, dark patterns, useless upselling, and so on.

You can enjoy it while it lasts, OpenAI is being very liberal with their limits because of CC eating their lunch rn.

We have built two of them now, and clearly the state of the art here can be improved. But it is hard to push too much on this while the models keep improving.

  ┌────────────────────────────┐
  │           User             │
  └──────────────┬─────────────┘
                 │
                 ▼
  ┌────────────────────────────┐
  │       Agent Harness        │
  │   (software interface)     │
  └──────┬──────────────┬──────┘
         │              │
         ▼              ▼
  ┌────────────┐ ┌────────────┐
  │   Models   │ │   Tools    │
  └────────────┘ └────────────┘

(1) Tooling to enable better evaluation of generated code and its adherence to conventions and norms (2) Process to impose requirements on the creation/exposure of PRDs/prompts/traces (3) Management to guide devs in the use of the above and to implement concrete rewards and consequences

Some organizations will be exposed as being deficient in some or all of these areas, and they will struggle. Better organizations will adapt.

While the idea of programmers working two hours a day and spending the rest of it with their family seems sunny, that's absolutely not how business is going to treat it.

Thought experiment... CEO has a team of 8 engineers. They do some experiments with AI, and they discover that their engineers are 2x more effective on average . What does the CEO do?

a) Change the workweek to 4 hours a day so that all the engineers have better work/life balance since the same amount of work is being done.

b) Fire half the engineers, make the 4 remaining guys pick up the slack, rinse and repeat until there's one guy left?

Like, come on. There's pushback on this stuff not because the technology is bad, (although it's overhyped), but because the no sane person trusts our current economic system to provide anything resembling humane treatment of workers. The super rich are perfectly fine seeing half the population become unemployed, as far as I can tell, as long as their stock numbers go up.