[netcan]

It's just hard to tell the difference between "real" demand and "circular." That's the concern.

PG had an essay about this during the dotcom, when he worked at yahoo. Iirc...Yahoo's share price and other big successes in the space attracted investment into startups. Startups used that money to advertise on yahoo. Yahoo bought some of these the startups.

So... a lot of the revenue used to analyze companies for investment was actually a 2nd order side effect of these investments.

Here the risk is that we have Ai investments servicing Ai investments for other Ai investments.

Google buys Nvidia chips to sell anthropic compute. Anthropic sells coding assist to Ai companies (including Google and Nvidia). They buy anthropic services with investor money that is flowing because of all this hype.

Imo the general risk factor is trying to get ahead of actual worldly use.

The Ai optimists have a sense that Ai produces things that are valuable (like software) at massive scale...that is output.

But... even if true, it will take a lot of time, and lot of software for the Econony to discover this, go through the path dependencies and actually produce value.

The most valuable, known software has already afy been written. The stuff that you could do, but haven't yet is stuff that hasn't made the cut. Value isn't linear.

[jmalicki]

While value isn't linear, prejudgement of value for allocation of resources is very imperfect.

A lot of stuff that doesn't make the cut is the the stuff that does have value. When you're lowering the bar, remember it's a noisy bar - so a lot more good stuff is going to come through as well.

[netcan]

Yes.. I agree.

.. and that entropy can be where all the ultimate value is. That said... considering the point at hand is the context, it's important to start with the diminishing marginal returns.

To give a simple example... Google and FB do not have "invest able software opportunities" at hand. They've been searching everywhere for nails for their "build software" hammer. They are well resourced and risk tolerant.

The diminishing returns curve for "more software" is steep.

Good stuff coming through often starts with $100m markets becoming $1bn markets. That's not even noise at the scale they're thinking about. Long term, sure. Plausibility range is as wide at it has maybe ever been.

But... systemic value is hard to make.

[jmalicki]

Most places I've worked have roadmaps, i.e. investable priorities.

If you can burn through lower priority experiments quickly it's great!

They might be working on all of the super high level things they can think of, but there are always more A/B tests, more features, etc. that are just lower priority, and the chaos of scaling up the org to address them all is super linear whereas the return on going down the list is sub linear.

So you end up with an equilibrium. If the cost shifts, just like in econ 101, the output will change.

[datavirtue]

I'm starting to transition how we build software at our company due to the power of AI. No more: five code monkey contractors under a lead. Two top-notch devs are all that is needed now, unrestrained by sprints and mindless ceremonies. There is going to be a giant sucking sound in India.

I can't continue the current model. The dev that gets AI is done in five hours, the ones that don't are thrashing for the next two weeks. I have to unleash the good AI dev. I have the Product team handing us markdown files now with an overview of the project and all the details and stories built into them. I'm literally transforming how a billion dollar company works right now because of this. I have Codex, Claude and GitHub Copilot enterprise accounts on top of Office 365. Everyone is being trained right now as most devs are behind, even.

[kloop]

> No more: five code monkey contractors under a lead. Two top-notch devs are all that is needed now, unrestrained by sprints and mindless ceremonies.

This doesn't tell me anything. Two devs who cared and didn't have a bunch of pointless meetings could already, and regularly did, scoop the big tech teams.

There were always 2 ways to complete a ticket. One that did what the stakeholder wanted, and one that does what the ticket says.

But devs that care about the product and what the stakeholders need are rare, and finding one of them was already a significant bottleneck on most projects.

AI might be an accelerator, but we've yet to see if it's optimizing the part that was actually the bottleneck yet.

[netcan]

Ok... but extrapolating from this to "whole market" paradigms is speculative.

The (imo) question isn't how you produce software, but what the value of this software is. Are you going to make make/better software such that customers pay more, or buy more? Are those customers getting value of this kind?

The answer may be yes. But... it's not an automatic yes.

Instead of programming think of accounting. Say you experience what you are experiencing, but as an accountant. 6 person team replaced by 2-3 hotshots.

So... Maybe you can sell more/better accounting for a higher price. But... potential is probably pretty limited. Over time, maybe business practices will adjust and find uses for this newly abundant capacity.

Maybe you lower prices. Maybe the two hotshot earn as much as the previous team.

If you are reducing team size, and that's the primary benefit... the fired employees need to find useful emplyment elsewhere in the economy for surplus value to be realized.

Mediating all this is the law of diminishing returns. At any given moment, new marginal resources have less productive value than the current allocation.

[liendolucas]

And the day you don't have that drug what do you do? If anything you are training people to become dependent on one or more subscription services.

[bethekidyouwant]

Like the drug of electricity and Internet, running water grocery stores?

[nocman]

I don't think the likelyhood of "electricity and Internet, running water grocery stores" being pulled out from underneath you (either by long term failure or prohibitive cost changes) is anywhere near as high as it is for subscription-based AI tools (at least not in the US).

[TeMPOraL]

That was a factor with electricity early on as it was first put to use. The flip side of the infamous "does it make the beer taste better?" adage/nonsense is that, per the story, back then you had breweries build their own power plants, because electricity was just that useful. It took a while for the market to start feeling comfortable with reliability of electricity supply and price point.

[throwaway173738]

Solidworks is also a subscription service.

[4ndrewl]

Except the dev that gets AI done in 5 hours will have a poorer mental model of the code. Whether that's important might or might not depend on whether that bites you in the ass at some point.

[nvarsj]

Don’t really agree with this.

That dev is productive with AI precisely _because_ they have a good mental model.

AI like other tools is a multiplier - it doesn’t make bad devs good, but it makes good devs significantly more productive.

[4ndrewl]

Don't agree - the dev is productive because they have a good mental model of the problem space and can cajole the agent into producing code that agrees with the spec. The trend is for devs to become more like product managers (which is why you see some whip-smart product managers able to build products _without_ human devs)

[techlover14159]

I believe these tools change the value of different skill sets in a very profound ways. Being good with rules of a programming language and syntax is no longer as valuable as it used to be.

Understanding the problem space is becoming more valuable. Strength in architecture of a solution is another skill that is becoming very valuable.

We are close to getting to a point where someone with overall general (and perhaps not very detailed) understanding of arch and design and a good understanding of the problem space and having a good taste in usability will be able to create awesome solutinos.

I can't wait to see these solutions being created by one or two person teams.

[gjsman-1000]

But does it matter?

If you write a program in Python or JavaScript, you have a terrible mental model for how that code is actually executed in machine code. It's irrelevant though, you figure it out only when it's a problem.

Even if you don't have a great mental model, now you have AI to identify the problems and generate an explanation of the structure for you.

[4ndrewl]

No, but you have a great mental model of the interface between your problem domain and the code, which is where you can affect change.

Outsourcing that to an AI SaaS might be ok I guess. Given past form there's going to be a rug-pull/bait-and-switch moment and dividends to start paying out.

[groundzeros2015]

The effect of JavaScript or python code is well defined - they have an excellent model of what it will do.

The performance - how that is executed on the machine is what you were referring to. “As if” is the key to optimization

[kibwen]

> It's irrelevant though, you figure it out only when it's a problem.

For the past decade people have been clawing their eyes out over how sluggish their computers have become due to everything becoming a bloated Electron app. It's extremely relevant. Meanwhile, here you are seemingly trying to suggest that not only should everything be a bloated, inefficient mess, it should also be buggy and inscrutable, even moreso than it already is. The entire experience of using a computer is about to descend into a heretofore unimaginable nightmare, but hey, at least Jensen Huang got his bag.

[bluGill]

That is the doom side. However AI has found and fixed a lot of security issues. I have personally used AI to improve my code speed, AI can analyze complex algorithms and figure out how to make them much faster in ways I can do as a developer, but it's a lot of work that I typically wouldn't do. Even just writing various targeted benchmarks to see where the problems really are in my code is something I can do, but would be so tedious I often would not bother. I can tell AI to do it and it will write those.

Only time will tell which version of the future we end up with. It could be good or bad and we will have to see.

[flyinglizard]

In terms of runtime performance of applications, AI is a net win. You can easily remove abstractions like Electron, React, various libraries. Just let the AI write more code. You can even do the unthinkable and write desktop native again.