It's really disappointing to see social media dismissing gemini so easily.

I think the worst thing we can do is have loyalty towards models. I used to be loyal towards Claude, and my viewpoint changed dramatically when I used codex.

I highly recommend that if you are someone who only used one model so far, that you really give another model a shot and see how it goes. It's very eye opening and gives you a more holistic perspective.

Vendor locking is a big problem when it comes to models, and I hope the software world doesn't do this blindly.

It feels like people are comparing Uber the brand in their own country and applying that to other countries

* People assume that Uber is a big brand in Nigeria and Uganda, this might not be true

* People assume that Uber is popular in these countries, this might also not be true

I started using llm's on a $20 claude license, then it became a $100 license.

Then all the mythos warnings happened, then the fable access issues started.

At that point, I just wanted to try something else because I didn't want to feel vendor locked by anthropic.

Then I tried codex on the $100 plan. I've never been happier. It does everything claude can do, without any token limit issues or anything for me.

I don't see myself going back to claude anytime soon. I also highly recommend folks to not vendor lock yourself to a model. You need to try multiple models for yourself and see what's possible. There should be zero loyalty to any frontier lab because of how fast things change and how volatile model access, uptime and customer experience can be with these things.

> LLMs aren’t lazy. They don’t cut corners because a simpler solution feels good enough. If they know how to solve something thoroughly, they will.

This is a severe misunderstanding in how LLMs work..

I don't know how this got on my front page....

I'm more interested in the business impact of this

So you spend billions of dollars training the model, only for it to be used in the US.

Then interesting to see where most of anthropic revenue comes from. If it's the US then they're fine but if it's global then they'll see a drop in revenue?

Then add to this decision, companies are going to significantly reduce their token spend.

So what does all of this mean for their IPO?

How can a LLM be assigned an emotion as being "proactive". This is highly misleading to anyone that scans just the headlines.

What actually happened is that the user started a prompt, and Claude took $12 worth of tokens to resolve the issue. How it did so was basically looping until it got to the answer

How is this proactive? It's literally being token greedy and maximising revenue for the LLM owner. People really need to be putting on business hats at this stage, because we are being lead to believe that "more tokens = better". It is not, there are efficient ways to solve a problem and there are inefficient ways to do so too.

Each problem solved incurs a cost, and is expected to yield an ROI at some point. This is how we should be viewing things now.

Is proactivity an emotion? Surely its a behaviour?

I've definitely never heard proactivity described as being an emotion. Doesn't really make any sense

Compared to other models that halt the loop on intermediate steps, or to ask further clarification, even if it's not the human equivalent of proactive, you see the similarity, right?

run haiku or sonnet under pi.dev. the halt comes from the harness/observer. even better, gemma 26b will just go forever.

Proactive is a word literally describing actions, not emotions.

> How can a LLM be assigned an emotion as being "proactive"

I can't edit my post, this is wrong. "Proactive" is defined as a behaviour instead of an emotion.

Thanks to everyone pointing it out!

I was trying to capture the idea that Claude Fable will act a whole lot more aggressively in pursuit of the goals that you set it than other models I've worked with.

The case I described is a good example of this. I told it to fix a scroll bar, and it built test HTML pages and a throwaway Python server and tried several ways of testing in a browser before settling on a weird Frankenstein mechanism because it identified that Playwright WebKit wasn't suffering from the bug but macOS Safari was.

... and it spent $12 of tokens to get there.

I think "proactive" is a good and relatively non-anthropomorphic term for this. I also considered "plucky" and "keen", which I think are more emotional words than "proactive".

> People really need to be putting on business hats at this stage, because we are being lead to believe that "more tokens = better".

I didn't intend my post to imply that spending $12 of tokens to fix a two lines CSS bug was "better".

Super appreciate you replying to my comment.

I think I understand where you're coming from now. What confused me is that the post is written in a way that it seemed like what Fable was doing was actually better. Maybe I should've looked at post as an exploratory post on Fable instead.

I don't think calling a model "relentlessly proactive" is positive anthropomorphism.

Spinning up 50 unnecessary subagents is exactly what I'd expect from a "relentlessly proactive" model.

> It's not being aggressive, it's just trying throwing shit at problems until it sticks... or doesn't.

The vast majority of the work the agent did was to reproduce the issue using the limited tooling it had access to. I don't see how that qualifies as "just trying throwing shit at problems until it sticks"

For me it depends on who you listen to

If you're following a bunch of people who are from LLM labs, you're going to be more incentivised to tokenmaxx because it's in the Lab's best interest tonget you to behave that way.

Practically, many companies aren't labs with endless runway. Companies hopefully follow a PnL model. And when you look at things with that lens, many of the times the LLM use case falls apart.

You're seeing a bunch of companies starting to realise that tokenmaxing yields very little ROI.

Even the LLM labs, the guy that spent $1+mil tokens has nothing to show for it in terms of revenue to the company. And you have to keep sinking that much into AI for ... "features".

There are some good use cases for AI. I ended up with a positive ROI on a greenfield project myself, albeit on a small scale.

The way that AI has been making people have totally irrational decisions on executive, pure business and technical standpoints is simply mindblowing. I don't understand how people can't take a step back and see what's actually happening from a macro perspective.

Gambling. Crypto. Tulips. Ponzi Schemes. Easy money always nets the suckers. You see it enough times and you just sigh.

This to shall pass. After enough bullshit people will become fed up and enforcement of existing laws will start breaking up the most egregious items. New laws will pass. People will make and lose fortunes, and we will live on.

Human systems are not good at rapidly adapting to change.

AI could be absolutely perfect and we'd still struggle to deploy it in a value generating way simply because it will exceed our ability to adapt.

So tokenmaxxing might be the wrong thing to do, but only because it's focussing on the wrong problem rather than because it doesn't actually work.

I'll take the contrary position and say that I think the "tokenmaxxing" we've previously seen was useful (but shouldn't continue indefinitely). My TLDR position is that TokenMaxxing was a way to force discovery of Product Market Fit.

The push by companies to incorporate AI into everything is (depending on the company) either hype and cargo-culting or it was an attempt by management to (1) try and discover if/what new workflows or tools could use it and (2) force the haters to use as it got better.

Where I work, there is an obvious split between people who have been willing to use AI, and those that hated it from day 1 and mocked the "stochastic parrots". Senior folks were disproportionately haters, and generally didn't see much productivity lift from early AI stuff. They strongly resisted the mandates to use AI, and completely missed the "agentic" inflection point that other colleagues experienced. The more willing users saw Claude Code/agents and were able to experience this as the genuine benefit it can be. Now that the more senior folks are using agentic programming, they're genuinely able to maintain code quality and see meaningful speed improvements in coding tasks.

Today, tokenmaxxing doesn't make sense because we found the product-market-fit of agentic coding. Now that most (?) employees are onboard with using it, the industry can shift focus to cost-effective usage and positive-ROI usage. For example, Uber shifting to a fixed per-employee token budget.

> The push by companies to incorporate AI into everything is (depending on the company) either hype and cargo-culting or it was an attempt by management to (1) try and discover if/what new workflows or tools could use it and (2) force the haters to use as it got better.

"we need to figure out if we can replace you with AI, or if it just extends your abilities"

Usually it’s the seller whose responsibility it is to find PMF, not the buyer.

Most tech companies are buyers of AI, many are also sellers of AI in their own products, and a few are also building it.

Sure. But the ones who are “tokenmaxxing” (I hate that term) are generally maximizing their usage as consumers.

“Try and discover if/what new workflows or tools could use it” is something that’s supposed to be done by the companies selling a product so they can then convince people to buy and use it — not something that the buyers are supposed to do.

it's a net positive for robinhood, not the trader necessarily

Product market fit and profitability are two different things.

Arguably product market fit was fond last November already. I don't think agents were the turning point that caused this.

Profitability, not yet. For me, it depends on whether companies are seeing a positive ROI from their ai investments. This website is skewed more towards big tech companies, but everyone that's not big tech needs to see positive ROI with using ai tools. Short term might see a profit, but medium to long term we still need to wait a bit.

So the article doesn't mention how the individual should prepare, but rather that government should prepare. Are individuals just that powerless against these perceived outcomes with AI?

My opinion is that AI can be a force for good, but why is everything so aggressively framed as a class war? Why must such a path be taken?

I wonder if this is how things were during the industrial revolution as well

1. Because it’s fairly clear that AI is trending to the most winner takes all dynamic that has ever existed. That will create a monopoly on intelligence.

Monopoly is the end state of unregulated competition and capitalism. A monopoly destroys the value of capitalism by undermining the power of competition to set efficient prices.

Individuals lack the bargaining power to overcome monopoly power.

2.AI will make broad categories of knowledge work so easy to create that the value will approach $0. Hard to make a living as a marketer, developer, payroll processor when it’s $0 to do that work. Saying “get a job loser” when monopolistic firms aren’t hiring is a bit insane.

If you look at real world examples of tech making jobs redundant, say Amazon and internet shopping closing down a lot of high street retail, then mostly what happened is the people who worked in that moved to something else. Individuals looking after themselves was the thing, government attempts to stop it not much use.

Then they say become an elecrician or hvac worker. Which will then just crash those markets too. And who is going to own property to hire you at some point without middle class knowledge work jobs.

After multiple generations of telling people blue collar jobs were a dead end and creating social stigma around them. Oh and gutting trade schools and apprenticeships.

There’s always a class war, its simply a question of whether you’ve realized where you are in it.

And yes every technology revolution displaced workers with a promise of better material and labor conditions by whatever form of domination was en vogue.

Those better conditions never materialized from the firm owner, only through direct action like the haymarket affair and others did modern labor practices start changing.

The anti-cooperative propaganda in the U.S. has been so effective since WWII that *any* sense of cooperative organizing is seen as unrealistic and childish at best, or evil perversion of the righteousness of domination at worst.

So if you don’t care about individual liberty then yeah everything is just fine provided you’re in the bourgeoisie.

I do actually think this time is different because all and I mean ALL of the infrastructure for revolt has been eradicated through consumption.

Good luck having a secret meeting of a few hundred revolutionaries or organizing an action deliberately.