everforward

> Note, at 5% productivity boost, humans are not just in the loop, they are the loop. AGI or large-scale replacement of humans is not even needed, but the financial opportunity is already immense, and it scales with how much human productivity can be improved (i.e. how much work can be offloaded to LLMs.)

The studies I've seen recently (at least in the software space) put it at something like a 10% increase in coding speed, which for me would probably translate to something like a 3% increase in productivity. I spend a lot more time on things like getting agreement between teams, documenting approaches to things that don't exist on the wiki, etc, that LLMs are significantly less effective at. Or just can't do; no one will be happy if I send an LLM instead of me to meetings.

I suspect a lot of roles are like that. They give a 10-30% boost to the core role function, but that core role is still only 30-50% of what you do.

> that is ~1.5 - 2.5T in value annually

That seems really large, but it's ~2-3x Walmart's yearly revenue, and OpenAI and Anthropic both have estimated valuations that compare to Walmart's market cap. And this is before we consider that they need to do it for cheaper or why would anyone bother. Realistically, potential revenue is probably half that at best.

It's also before cutthroat pricing really kicks in. People are willing to pay for Claude right now; I still suspect that as time goes on people will start looking towards Deepseek/GLM/etc models that provide 95% of the performance at 10% of the price. That'll cut the market even further.

The question is how much demand for knowledge work swells as prices fall, and whether that's a soft landing or a crash.

There’s no way to justify their valuations if they get downgraded to a pair programming tool. They need fully agentic stuff to work and replace human engineers to even come close.

Offhand, I’m not even certain whether a model like that could justify the constant retraining we’re doing on the agentic models.

It doesn’t make a lot of sense to spend millions or billions on training to reduce hallucinations by 0.3% if your model assumes a human is in the loop to course-correct them.

> normal people who think expediting the interdiction of stolen vehicles (which are vectors of violent crime) is a perfectly reasonable thing for a city to invest in.

The effectiveness is dramatically oversold. This has literally happened to me. Called 911 midway through the theft, cops pulled it up on Flock, the best they could tell me was "they went towards the highway" (no shit, Sherlock).

I saw the parts on marketplace a week later (definitely mine, unique staining), 2 hours after they were listed and called it in. The PD where the parts are wouldn't do anything unless my PD called, my PD said the officer in charge was on vacation so they can't do anything until he's back.

Take a wild guess who hasn't heard anything back. This should be their ideal situation; they got called mid-robbery, and someone else located the parts afterwards. If they can't solve that with Flock, lack of information is not the holdup here.

> It would be so easy, to generate subconcious addds with an LLM. Like weave a slogan reminder into the conversation...

Probably not without changing the underlying response and tanking the benchmark ratings. Like I ask it to generate code, it tries to add a slogan reminder, now the comments on my code have Tide's slogan in them and the variables are all named "bleach".

Probably less humorous than that, but the underlying point stands. People will be extremely upset about their prompts being tinkered with, and any perceived degradation in quality will be quickly attributed to them. The hidden nature of them will probably cause speculation that they do the same on the higher tier plans.

That's not a lawsuit by a gun manufacturer, those are regular private citizens and the "California Rifle and Pistol Association". So far as I can tell, that's not an industry lobby group, it's a private interest group although I'm sure the manufacturers like them.

That changes the above quote. It's not a gun manufacturer claiming they can't find anyone to microstamp their guns (though not dispositive of the same), it's a citizen saying that commercially no one sells microstamped guns.

If you expand out your quote, it neatly explains what I would wager is the reason why no one sells microstamped guns:

"AB 2847 also imposes an additional amendment to the UHA: for every semiautomatic handgun that satisfies the new one location microstamping requirement (in addition to havingCLI and MDM) and is therefore added to the Roster, the State must remove three (3) grandfathered semiautomatic handguns from the Roster, in reverse order of addition. However, this has not yet occurred because microstamping technology does not actually exist in any commercially available application on a handgun."

In other words, if a manufacturer decides to make a new microstamped model then 3 models that are likely still in production will become illegal. It's a losing proposition for the manufacturers. There's no money to be made by creating a new production line to build microstamped pistols if it's going to shut down an existing line; it's a bunch of money to re-tool factories to sell to the same people the shut down line was already selling to.

Without getting too into the weeds of politics, it's exacerbated by it being California. Whether you agree or disagree with the goals of the policies, they do change the requirements for guns very frequently relative to other places. I can understand manufacturers being reticent to set up new production lines to comply with policies that will probably change again in the next 5 or 10 years.

My reading of the lawsuit is that they think this was the intended end state of the bill. Require new guns to implement a feature, ensure that implementing that feature will generate financial losses, and now no new guns get made but you can point at gun manufacturers and say you didn't ban them the manufacturers just won't comply. I'm not totally sold on that, but it is a remarkably poorly written bill when the incentives the bill sets up run exactly counter to the intended goals.

> * there is LangChain and LangGraph - used a lot, but framework bloat is hated as well

I've used them a fair bit, and I'm not a huge fan. Only self-hosted, I can't comment on their cloud-SaaS agent runner thing. The observability looks neat, though.

LangChain is nice enough, I appreciate having a unified API across providers. LangGraph is... just not all that much? As in the DAG is too much for a simple agent, but when I start thinking about a large agent and dealing with that flow in their their DAG DSL my head starts to hurt. "Go To Definition" isn't going to help navigate that very well, the state is going to be a lot of Optional's with not a lot of info on when they have a real value at which stages in the DAG.

I had substantial issues with branches in my DAG because the state has to include all possible fields for every step. It gets hard to mentally track all the combinations of fields that will be present or missing depending on the path taken upstream of this node. Do I have RAG results? Not sure, it depends on whether the query includes X, but then later it also depends on whether a tool returns a particular result, in which case it can either be missing, have a single value or have 2 values. Yada yada, in a sufficiently large DAG it gets hard to track those. Things are much cleaner in function world where you can declare "this functions require X and Y, and can optionally provide Z".

I mostly go directly to the API these days, but I'm fairly settled on Ollama. I might use LangChain if I think I'll want another backend, but I also might use OpenRouter. I haven't yet, but it seems cool.

One is a specific pattern, with specific distances, colors, etc.

The other is a human-invented category of objects that lacks consistency in size, shape and design.

“Don’t print this specific pattern” is a much more closed loop than “figure out if this could be part of a firearm, bearing in mind that guns share a ton of parts with perfectly legal things”. Especially since the things that are most indicative of being a firearm are usually bought instead of printed.

Eg a “3D printed AR-15” usually means a 3D printed lower and the rest of it is bought off the shelf of a gun store (the rest isn’t regulated, you don’t need a background check to buy a barrel or upper or etc). So it’s really just a grip, the slot for the magazine, and some holes for pins in the right spot.

That’s super hard to identify. Grips come in a variety of shapes and sizes and have a bunch of legal uses (nerf guns, slingshots, Wii remote holders) and are hard to detect. The mag well is just a rectangular hole? Probably some slots for springs, but you have to assemble it afterwards so the printer doesn’t see that.

The pin holes are probably the best indicator, although they’d be trivial to drill or melt afterwards, or print them as a separate piece and screw it on top of the lower.

It’s just an almost impossible problem. I don’t even think humans could do it reliably with the info the machine gets. Whether it’s an AR lower or a prop/nerf gun/airsoft/cosplay/accessibility attachment (pistol grips have some nice ergonomics) gets into the nitty gritty of the interior and whether they support real linkages or not. I just don’t think we can do it with any degree of accuracy.

That’s without getting into the more avant-garde 3D printed guns that are made either out of hardware store parts rather than gun store parts (common in Europe, barrels and what not are regulated there), or are made out of an amalgamation of parts from other guns (trigger from a Glock, barrel from an AR-15, mags from something else, etc).

Generalizing an algorithm that can detect “things that aren’t a gun I recognize but could be used as a gun” is going to be fraught with false positives. You don’t 3D print the linkages, so it’s just a frame, and there an awful lot of things that could conceivably be part of a gun. Anything vaguely semi-circular could be a trigger, anything with a tube could be a barrel, anything hollow and rectangular could be a magazine.

I don’t see a way that either a) it only blocks current designs and the community quickly adapts around it and continues, or b) it tries to block anything gun-like and false positives spiral out of control.

It feels sort of moot anyways. Phillip Luty wrote a whole book about assembling a fully-automatic submachine gun out of parts from the hardware store all the way back in the 90s. It does require familiarity with hand tools and access to more tools than most people have at home (drill press comes to mind), but you don’t have to be an expert machinist to do it even without 3D printers.

This is all besides the fact that it’s so easy to obtain a real gun in the US that 3D printing guns is a niche hobby. I’ve looked at them and watched some of their competitions, they’re still pretty crap. The fully 3D printed ones still jam constantly and I believe still use off the shelf magazines because those are surprisingly hard to make well. The partially 3D printed ones (eg lower only) tend to be substantially less durable than market alternatives. Unsurprisingly, a plastic 3D printed lower is more likely to shatter while firing or dropping it than a milled steel/aluminum one.

They don’t claim it doesn’t exist, they claim it bears a cost significant to the overall cost of the firearm and is unlikely to meaningfully accomplish its stated goals. Ie prices will go up by 10% or whatever for basically nothing.

It’s a useless place to put an identifier. It can be filed off easily, and checking whether it’s present involves a microscope and/or disassembling the firearm (depending on the gun and firing pin setup).

You can even just straight up replace it with hand tools at the range. More insidiously, if this passes, you’ll probably be able to buy firing pins that are stamped with someone else’s identifier. I have little doubt a market will spring up for falsely marked firing pins.

Or go super low tech and just throw a brass catcher on the receiver to catch the shells. In a pinch, duct tape and a shopping bag will prevent leaving brass behind.

This is just a money grab by the folks that invented the tech. We don’t even do a good job of keeping stuff like select fire switches for Glocks off Facebook, this is unlikely to do anything but raise the base price of a gun.

New stuff does, but most of my peripherals aren't new. A couple are a decade old and probably pre-date USB-C being standardized.

I am semi-frequently annoyed that my laptop has 0 USB-A ports. At least give me one.

> Net neutrality is about a natural monopoly - there can only be so many cell towers, satellites and fibre optic cables.

This is a misinterpretation, we could support an absolute ton more physical infrastructure than we have in the wired space (cell towers and probably satellites are limited by spectrum, but still not the physical footprint of the devices).

Fiber cables are tiny relative to their bandwidth. Ignoring cost, if we made water mains sized fiber runs under the sidewalks we could probably get hundreds of 10Gbps fiber runs to every house. And I think there’s still a ton of space to fill with cabling if we wanted to for whatever reason.

The two most significant factors at the physical level are

1: it’s a natural monopoly not because of space, but because building that infrastructure is so expensive it’s unlikely any competitors could emerge. Think about where you are and where the closest peering point is. That run alone is probably millions of dollars and a decade of lawsuits to get easements on the intervening properties to even be able to run it.

2: it’s incredibly wasteful to run parallel lines when each house will only realistically have one set of them active at a time. Few people pay for more than one ISP, it’s basically setting resources on fire.

AI companies are frankly far more limited. GPUs are scarce, I wouldn’t be surprised if we’re already building faster than GPUs get produced. Power is scarce, so far there’s been a lot of hand waving about how we’re going to double our power production. Land is fairly scarce when you scope it down to “land that has enough power access, and usable roads for trucking in materials, and access to water for cooling, and is far enough away that the noise won’t make people riot”.

There’s few implementations of the engine, but many implementations of rules for that engine.

I think OPs point is that many of those rule sets probably don’t do what the author intended.

I would second that, because CORS questions are common and “turn on the allow all pattern” is almost always in the top 3 suggestions.

Semi-related tangent, it annoys the hell out of me that create-react-app (and the newer incarnation) don’t come with an “allow all” CORS rule. Don’t force me to figure out which arcane setting configures CORS headers, I’m the one writing the code, I’m okay with wherever the HTTP requests are going, I’ll set up real CORS headers on nginx for prod.

It’s not what they do, and it’s a crowded market where they don’t really have an edge. If you want well-vetted products, don’t go to Craigslist. They’re just digital classifieds, the tradition is basically “anyone can list them, no one checks them, caveat emptor”.

It’s weird to me they even carry real estate listings, because I’m surprised anyone would trust them with that kind of money on a good you can’t easily self-validate. I wouldn’t spend more than $100 on something from Craigslist if I wasn’t confident that I can judge the quality of it myself.

I would disagree, purely because the utility of a programming language doesn’t hinge on how many speak it.

The goal of programming languages is to execute instructions on the machine. Brainfuck still executes machine code the same whether 2 people write it or it becomes the lingua Franca of AI. There’s fewer libraries, but C FFI bridges a lot of that.

Learning Klingon is odd because human languages are meant for communication, so a language with no speakers is largely pointless (barring cultural value, which Klingon largely lacks because it’s a fictitious language and too modern to have that niche coolness).

Not really, precisely because it’s decentralized. You can’t audit whether a user accessed one of the hidden files, or really even who can access it once you accept the reality of the risk that some team will put a key on S3 or a shared drive or whatever.

It’s fine for things that you want devs to be able to see without the Git host being able to see them, it’s less good at RBAC because there’s no real “identity” component at read-time.

I suspect these won't be as sticky as the contracts you're thinking of. Oracle and Microsoft can run on that because their products aren't compatible with anything else so migrating is a huge pain.

Cursor doesn't really have that. We've got it at $DAYJOB but it's not even the only one, I can also use Zed or Codex or Claude or probably a half dozen other things I don't even know about.

I suspect a lot of companies have that right now because the market for AI is so volatile, and in the near future will trim that down to a couple of tools and Cursor doesn't have much to keep them at the top of the list imo.

I also wouldn't pay 60 billion for a bunch of enterprise contracts that have to compete against Microsoft. No one is dropping Microsoft as a vendor, and they have the ability to up the prices for stuff people need like Office and use that to make Copilot free. If times get tough and companies need to cut costs, it's a lot easier to part ways with Cursor than Microsoft.

The dual risks of either a) accidentally pushing a foreign competitor into the lead and losing dominant status, or b) pushing the underlying companies hard enough that they decide to relocate.

a) is specifically the risk that the export controls push companies in other countries to prefer non-US models due to the lowered risk of getting cut off from a model. The increase in revenue for non-US AI providers combined with the drop in revenue for US AI providers allows non-US providers to double down on training and reach parity or exceed US SOTA models.

b) is sort of self-explanatory. Same model as above, but when the US AI providers start seeing the revenue drop they decide to relocate internationally instead. The US would probably try to stop that, no idea how successful they would be.

> The hit you take on returns might be worth it to you as a hedge against disastrous market conditions.

Ahh, that does make more sense.

I do 100% believe there's an economy of scale there. Even just being large enough to employ an in-house repair person would probably be a huge savings. There's a lot of stuff anyone that can swing a hammer could fix that you end up hiring expensive tradesmen to do when you're not local.

> they're not defrauding the population.

Ehh, I think it's a lot more grey than "definitely not". It's hard to ignore that their claims that their model is so dangerous they can't widely release it is tantamount to declaring that they're in a league of their own and have to be treated with white gloves to prevent the sheer power of their model from shattering global prosperity.

This isn't the first time, and nothing bad has happened with the prior models. Every time it gets a little harder to believe that they believe in the threat, and makes it feel a little more like it's just to build hype. There's only so many times you can say "this model is a threat to the world", have it turn out to be nothing, and avoid people accusing you of lying to pump stock prices.

An illustrative example I've seen a lot is creating Jira tickets in projects with custom fields marked as mandatory. It tries to create the ticket without the field and the tool call fails. The LLM needs access to the full context so that it can generate text to put in the "Why couldn't this meeting be an email?" field.

You have to apply (and they presumably need to approve).

It's probably indicative of a less predatory model, but CF got a ton of mindshare by offering their free tier. I do basically nothing in the frontend space, but I default to CF because I'm used to using it due to using the free tier for personal projects.

> If Fable is "delegating" tasks, then there's actually an agent front end of whatever you think the API is.

I would say behind (I believe you use the API just like you do Opus), but yeah. I'm not claiming it's a property of the LLM itself, I also presume this is some variety of tool calling agent harness.

> We have a local instance of Qwen-3.6 which is more than adequate for running agents. You can mix and match local and cloud-hosted models.

I'm presuming OP meant local as in the models run locally as well. I do know you can do subagents in Pi (probably others too), but the vast majority of people are going to hit hardware limitations trying to run them in parallel on local hardware.

I'm doubtful Fable's harness is unique in some way that you can't replicate with Pi. I'm mostly doubtful there are more than a handful of people with hardware sitting in their house that can execute more than one meaningfully smart model at a time.

If you're on local hardware, Deepseek v4 Flash is in the ballpark of 180GB of VRAM alone. Even on smaller models, Qwen + a dumber agent to execute is probably in the realm of 60GB of VRAM.

I do suspect you could get Deepseek to do Fable level things with a good harness (or a bunch of models really, I'm fairly convinced the magic of Fable is in the harness rather than the model).

While I disagree with OP about removing stuff from the model, there’s a valid question about tradeoffs between intelligence and price.

Deepseek Flash is almost certainly wrong more often than Opus or Fable. It also costs like 5% as much.

The question becomes if I run Deepseek in a loop to fix the mistakes it made that Opus/Fable didn’t, can it fix its own bugs in few enough tokens that it’s still cheaper?

So far, the answer seems to be “yes, by a significant margin”. A lot of tasks are simple enough that both Deepseek and Opus or Sonnet can one-shot it, which is a huge cost win for Deepseek. Even on the long tail, it’s usually like 4x the tokens on Deepseek which is still way cheaper than Opus.

There are things that Opus can do that Deepseek just won’t ever really nail, but it happens so infrequently that I just don’t worry. Like most people, most of what I do is the same sort of “3 tier app with a React frontend” that doesn’t take a rocket scientist to work out.

Fable can delegate tasks to Opus or Sonnet, so it has some agentic properties and I believe it does them in parallel.

The parallelism is where this starts to fall apart on a local PC. Like I can run some Qwen quants, but I can’t run a decent Qwen model while also running another model smart enough to actually implement it. I’d have to do them in series, and given how long Fable seems to take even with parallelism, I’d probably be waiting days for an answer.

It’s really hard to translate minutes to tokens, it depends on how you’re using it.

The best answer would be to pull session stats from your harness and compare that against the limits. I think Anthropic publishes the limits of each plan.

If you’re using a pretty stock harness and not doing crazy multi-agent stuff with it, you’re probably fine.

My girlfriend built a whole (but simple) React app with it and only hit the limits of the $20 plan once. In fairness, she was trying to get it to clean up a bunch of 800ish line React files at once with a vague “make it look nice” prompt that she ran a few times. I think it was just churning for like half an hour straight before she burned all her credits.

It’s probably enough if you’re not on a fully agentic development strategy, it’s plenty to have it write tests and do comments and stuff, just not enough to continually have it doing giant refactoring passes.

No, this is an agent-level thing, not a feature of the model (ish, unsure for Fable).

You talk to a smart, heavy model to build a plan composed of smaller steps. Then you have the heavy model spin up smaller, cheaper LLMs to actually implement the tasks.

The heavy model is basically read-only in that mode. It can read files, execute tests, etc, but it can’t write code. It just tracks what needs to be done, offloads the work to dumber LLMs, validates the task is done, and moves on to the next step.

It sort of pushes humans up the stack. Instead of having a human sitting there prompting the LLM to start the next task, you have another LLM do that loop.

It’s been on my list to try out.

The returns just don’t really make sense for me, but I’m not a CPA.

The returns don’t seem substantially better than an index fund, it’s a headache to deal with, and if housing actually becomes affordable then you’re upside down (and the govt might air drop cash on upside down mortgages, probably not if you’re already paid off).

Not my forte though and I hand-waved the hell out of that math, maybe I’m way off. Just feels like a ton of capital to tie up for mediocre returns.

A beach house makes some more sense because you get the utility of being able to use it, which is worth something if you like to vacation to the same place.

This is a nice way to do it if you’re already stuck with a solution (print to PDF would probably also, if you can script it).

In a green field world, I have a personal requirement that technical documentation systems are capable of bulk exporting to a human-readable format on disk. I’m pretty flexible on what that is, though. Markdown is preferred, but I’m also fine with static, dependency-free HTML and I could accept PDFs if the rest of it is super nice.

It’s an integral part of DR, and most places want their docs on-premise, so DR effectively requires offline documentation. Everywhere I’ve worked either a) writes documentation in something that works offline (eg git repo with tarballs somewhere), or b) has invested a bunch of time in trying to scrape their own wiki into something legible during DR.

I guess it’s a long-winded way of saying “that’s using a tool to fix a self-inflicted problem that shouldn’t exist”.

I tried this once and it wasn’t great. It was a single home, and in a college neighborhood (house was cheap, ergo rent was low).

The rent paid the mortgage, but that was about it. Repairs were more or less out of pocket.

I gave it up because I didn’t live locally and got raked over the coals on repairs a couple times. I finally quit because the property managers had an “emergency repairs” clause where they could do repairs without my approval and bill me.

One of the renters clogged the toilet at 11pm on a Saturday, moron decided to call the property management because I guess plungers are confusing, they decided that was an emergency, and I got a $700 bill to send a plumber out at midnight to plunge a toilet. Like not even a roto rooter or something, just a generic grocery store plunger.

Became clear I was either a) going to have to be much more involved, or b) accept that the returns are basically just equity in the house on a 15 year mortgage, minus overpriced repairs.

Trump has made some concerning moves around freedom of speech and freedom of elections, but none of it is concrete yet. Maybe it never will be, either because the threat was overstated or because he’s just not competent enough to pull it off.

China does worse on those fronts, but they do so predictably. I don’t agree with many of their goals, but you can generally rely on them pursuing those goals in a manner consistent with their values. Ie I’m not often taken aback by how they respond, it’s within the realm of things I’d expect.

The US is concerning because their behavior is wildly unpredictable, which makes them unreliable even if their values align better with mine (purportedly, anyways). I have no idea when or if Fable will be back, or what kind of modifications the government will demand, or if this will apply to other models, and whether any of that is going to impact Anthropics or OpenAIs ability to release models.

I was already wary of Claude Code and Codex because I don’t like being tied to a provider-specific tool (I don’t trust they won’t cut off swapping the API URL), and now that’s even worse because I’m not even sure either will stay at the front of the pack. I’m sure as hell not using a vendor locked tool tied to the 5th best model provider (if they fall).

If we’re talking about models that people actually use, there’s really only Chinese models and American models. I haven’t heard anything about Mistral in ages.

From that lens, criticism of one is practically implicit support of the other. If I tell you that you can buy from salesman A or B, but B is a bad person, that implies A is not a bad person. Otherwise I would have said “they’re both bad people”.

“But Chinese models are controlled by the government” makes it sound an awful lot like the US ones aren’t, because it wouldn’t be a meaningful criticism if that were true of both.