Because nobody actually wants a "web app". People want food, love, sex or: solutions.

You or your coworker are not a web app. You can do some of the things that web apps can, and many things that a web app can't, but neither is because of the modality.

Coded determinism is hard for many problems and I find it entirely plausible that it could turn out to be the wrong approach in software, that is designed to solve some level of complex problems more generally. Average humans are pretty great at solving a certain class of complex problems that we tried to tackle unsuccessfully with many millions lines of deterministic code, or simply have not had a handle on at all, like (like build a great software CEO).

> Because nobody actually wants a "web app". People want food, love, sex or: solutions.

Okay but when I start my car I want to drive it, not fuck it.

Christine didn’t end well for anyone.

Even if it purred real nice when it started up? (I’m sorry)

Looks like we have a Civic owner xD

Most of us actually drive a car to get somewhere. The car, and the driving, are just a modality. Which is the point.

Yeah but in this case your car is non-deterministic so

Well the need is to arrive where you are going.

If we were in an imagined world and you are headed to work

You either walk out your door and there is a self driving car, or you walk out of your door and there is a train waiting for you or you walk out of your door and there is a helicopter or you walk out of your door and there is a literal worm hole.

Let's say all take the same amount of time, are equally safe, same cost, have the same amenities inside, and "feel the same" - would you care if it were different every day?

I don't think I would.

Maybe the wormhole causes slight nausea ;)

I think it’s pretty obvious but most people would prefer a regular schedule not a random and potentially psychologically jarring transportation event to start the day.

> Well the need is to arrive where you are going.

In order to get to your destination, you need to explain where you want to go. Whatever you call that “imperative language”, in order to actually get the thing you want, you have to explain it. That’s an unavoidable aspect of interacting with anything that responds to commands, computer or not.

If the AI misunderstands those instructions and takes you to a slightly different place than you want to go, that’s a huge problem. But it’s bound to happen if you’re writing machine instructions in a natural language like English and in an environment where the same instructions aren’t consistently or deterministically interpreted. It’s even more likely if the destination or task is particularly difficult/complex to explain at the desired level of detail.

There’s a certain irreducible level of complexity involved in directing and translating a user’s intent into machine output simply and reliably that people keep trying to “solve”, but the issue keeps reasserting itself generation after generation. COBOL was “plain english” and people assumed it would make interacting with computers like giving instructions to another employee over half a century ago.

The primary difficulty is not the language used to articulate intent, the primary difficulty is articulating intent.

this is a weak argument.. i use normal taxis and ask the driver to take me to a place in natural language - a process which is certainly non deterministic.

and the taxi driver has an intelligence that enables them to interpret your destination, even if ambiguous. And even then, mistakes happen (all the time with taxis going to a different place than the passenger intended because the names may have been similar).

Yes so a bit of non determinism doesn’t hurt anyone. Current LLMs are pretty accurate when it comes to these sort of things.

> a process which is certainly non deterministic

The specific events that follow when asking a taxi driver where to go may not be exactly repeatable, but reality enforces physical determinism that is not explicitly understood by probabilistic token predictors. If you drive into a wall you will obey deterministic laws of momentum. If you drive off a cliff you will obey deterministic laws of gravity. These are certainties, not high probabilities. A physical taxi cannot have a catastrophic instant change in implementation and have its wheels or engine disappear when it stops to pick you up. A human taxi driver cannot instantly swap their physical taxi for a submarine, they cannot swap new york with paris, they cannot pass through buildings… the real world has a physically determined option-space that symbolic token predictors don’t understand yet.

And the reason humans are good at interpreting human intent correctly is not just that we’ve had billions of years of training with direct access to physical reality, but because we all share the same basic structure of inbuilt assumptions and “training history”. When interacting with a machine, so many of those basic unstated shared assumptions are absent, which is why it takes more effort to explicitly articulate what it is exactly that you want.

We’re getting much better at inferring intent from plain english, but even if we created a machine which could perfectly interpret our intentions, that still doesn’t solve the issue of needing to explain what you want in enough detail to actually get it for most tasks. Moving from point A to point B is a pretty simple task to describe. Many tasks aren’t like that, and the complexity comes as much from explaining what it is you want as it does from the implementation.

I mean, as long as it works and it is still technically "my car", I would welcome the change.

> your car is non-deterministic

it's not as far as your experience goes - you press pedal, it accelerates. You turn the steering, it goes the way it turns. What the car does is deterministic.

More importantly, it does this every time, and the amount of turning (or accelerating) is the same today as it was yesterday.

If an LLM interpreted those inputs, can you say with confidence, that you will accelerate in a way that you predicted? If that is the case, then i would be fine with an LLM interpreted input to drive. Otherwise, how do you know, for sure, that pressing the brakes will stop the car, before you hit somebody in front of you?

of course, you could argue that the input is no longer your moving the brake pads etc - just name a destination and you get there, and that is suppose to be deterministic, as long as you describe your destination correctly. But is that where LLM is at today? or is that the imagined future of LLMs?

Tesla's "self-driving" cars have been working very hard to change this. That piece of road it has been doing flawlessly for months? You're going straight into the barrier today, just because it feels like it.

Sometimes it doesn't though. Sometimes the engine seizes because a piece of tubing broke and you left your coolant down the road two turns ago. Or you steer off a cliff because there was coolant on the road for some reason. Or the meat sack in front of the wheel just didn't get enough sleep and your response time is degraded and you just can't quite get the thing to feel how you usually do. Ultimately the failure rate is low enough to trust your life on it, but that's just a matter of degree.

The situations you described reflects a System that has changed. And if the System has changed, then a change in output is to be expected.

It's the same as having a function called "factorial" but you change the multiplication operation to addition instead.

all of those situations are the "driver's own fault", because they could've had a check to ensure none of that happened before driving. Not true with an LLM (at least, not as of today).

Most of us actually want to get somewhere to do an activity. The getting there is just a modality.

Most of us actually want to get some where to do an activity to enjoy ourselves. The getting there, and activity, are just modalities.

Most of us actually want to get somewhere to do an activity to then have known we did it for the rest of our lives as if to extract some intangible pleasure from its memory. Why don't we just hallucinate that we did it?

This leads to us asking the deepest question of all: What is the point of our existence. Or as someone suggests lower down, in our current form all needs could ultimately be satisfied if AI just provided us with the right chemicals. (Which drug addicts already understand)

This can be answered though, albeit imperfectly. On a more reductionist level, we are the cosmos experiencing itself. Now there are many ways to approach this. But just providing us with the right chemicals to feel pleasure/satisfaction is a step backwards. All the evolution of a human being, just to end up functionally like an amoeba or a bacteria.

So we need to retrace our steps backwards in this thought process.

I could write a long essay on this.

But, to exist in first place, and to keep existing against all the constraints of the universe, is already pretty fucking amazing.

Whether we do all the things we do, just in order to stay alive and keep existing, or if the point is to be the cosmos “experiencing itself”, is pretty much two sides of the same coin.

>Or as someone suggests lower down, in our current form all needs could ultimately be satisfied if AI just provided us with the right chemicals. (Which drug addicts already understand)

When you suddenly realize walking down the street that the very high fentanyl zombie is having a better day than you are.

Yeah, you can push the button in your brain that says "You won the game." However, all those buttons were there so you would self-replicate energy efficient compute. Your brain runs on 10 watts after all. It's going to take a while for AI to get there, especially without the capability for efficient self-repair.

Indeed - stick me in my pod and inject those experience chemicals into me, what's the difference? But also, what would be the point? What's the point anyway?

In one scenario every atom's trajectory was destined from the creation of time and we're just sitting in the passenger seat watching. In another, if we do have free will then we control the "real world" underneath - the quantum and particle realms - as if through a UI. In the pod scenario, we are just blobs experiencing chemical reactions through some kind of translation device - but aren't we the same in the other scenarios too?

This was actually my point as well. You can follow this thought process all the way up to "make those specific neuron pathways in my brain fire", everything else is just the getting there part.

But I want that somewhere to be deterministic, i.e. I want to arrive to the place I choose. With this kind of non-determinism instead, I have a big chance of getting to the place I choose. But I will also every now and then end up in a different place.

If this was a good answer to mobility, people would prefer the bus over their car. It’s non-deterministic - when will it come? How quick will i get there? Will i get to sit? And it’s operated by an intelligent agent (driver).

Every reason people prefer a car or bike over the bus is a reason non-deterministic agents are a bad interface.

And that analogy works as a glimpse into the future - we’re looking at a fast approaching world where LLMs are the interface to everything for most of us - except for the wealthy, who have access to more deterministic services or actual human agents. How long before the rich person car rental service is the only one with staff at the desk, and the cheaper options are all LLM based agents? Poor people ride the bus, rich people get to drive.

Bus vs car hit home for me as a great example of non vs deterministic.

It has always seemed to me that workflow or processes need to be deterministic and not decided by an LLM.

Here in Switzerland the bus is the deterministic choice. Just saying.

But do you want to drive, or do you want to be wherever you need to be to fuck?

For me personally, the latter, but there's definitely people out there that just love driving.

Either way, these silly reductionist games aren't addressing the point: if I just want to get from A to B then I definitely want the absolute minimum of unpredictability in how I do it.

That would ruin the brain placticity.

I wonder now, if everything is always different and suddenly every day would be the same. How many times as terrifying would that be compared to the opposite?

A form of Alexei Yurchak's hypernormalisation?

Only because you think the driving is what you want. The point is that what you want is determined by our brain chemicals. Many steps could be skipped if we could just give you the chemicals in your brain that you craved.

I feel like this is the point where we start to make jokes about Honda owners.

Go on, what about honda owners? I don't know the meme.

The "Wham Baam" YouTube channels have a running joke about Hondas bumping into other cars with concerning frequency.

...so that you can get to the supermarket for food, to meet someone you love, meet someone you may or may not love, or to solve the problem of how to get to work; etc.

Your ancestors didn't want horses and carts, bicycles, shoes - they wanted the solutions of the day to the same scenarios above.

As much as I love your point, this is where I must ask whether you even want a corporeal form to contain the level of ego you're describing. Would you prefer to be an eternal ghost?

To dismiss the entire universe and its hostilities towards our existence and the workarounds we invent in response as mere means to an end rather than our essence is truly wild.

Most people need to go somewhere (in a hurry) to make money or food etc which most people don't want to do if they didn't have to, so yeah it is mostly a means to an end.

And yet that money is ultimately spent on more means to ends that are just as inconvenient from another perspective?

My point was that there is no true end goal as long as whims continue. The need to craft yet more means is equally endless. The crafting is the primary human experience, not the using. The using of a means inevitably becomes transparent and boring.

It should finalize into introducing satisfaction to the whims directly, so the AI would be directly managing the chemicals in our brains that would trigger feelings of reward and satisfaction.

I think you're just describing drugs

Yes, but current drugs have many issues such as tolerance build up and withdrawals. If AI could figure out how to directly manage chemicals in the brain in such a way that it keeps working, it would be able to attain its goals of making people happy.

Food -> 'basic needs'... so yeah, Shelter, food, etc. That's why most of us drive. You are also correct to separate Philia and Eros ( https://en.wikipedia.org/wiki/Greek_words_for_love ).

A job is better if your coworkers are of a caliber that they become a secondary family.

Sadly, this is not true of a (admittedly very small) number of individuals.

Weird kink

> Average humans are pretty great at solving a certain class of complex problems that we tried to tackle unsuccessfully with many millions lines of deterministic code..

Are you suggesting that an average user would want to precisely describe in detail what they want, every single time, instead of clicking on a link that gives them what they want?

No, but the average user is capable of describing what they want to something trained in interpreting what users want. The average person is incapable of articulating the exact steps necessary to change a car's oil, but they have no issue with saying "change my car's oil" to a mechanic. The implicit assumption with LLM-based backends is that the LLM would be capable of correctly interpreting vague user requests. Otherwise it wouldn't be very useful.

The average mechanic won’t do something completely different to your car because you added some extra filler words to your request though.

The average user may not care exactly what the mechanic does to fix your car, but they do expect things to be repeatable. If car repair LLMs function anything like coding LLMs, one request could result in an oil change, while a similar request could end up with an engine replacement.

I think we're making similar points, but I kind of phrased it weirdly. I agree that current LLMs are sensitive to phrasing and are highly unpredictable and therefore aren't useful in AI-based backends. The point I'm making is that these issues are potentially solvable with better AI and don't philosophically invalidate the idea of a non-programmatic backend.

One could imagine a hypothetical AI model that can do a pretty good job of understanding vague requests, properly refusing irrelevant requests (if you ask a mechanic to bake you a cake he'll likely tell you to go away), and behaving more or less consistently. It is acceptable for an AI-based backend to have a non-zero failure rate. If a mechanic was distracted or misheard you or was just feeling really spiteful, it's not inconceivable that he would replace your engine instead of changing your oil. The critical point is that this happens very, very rarely and 99.99% of the time he will change your oil correctly. Current LLMs have far too high of a failure rate to be useful, but having a failure rate at all is not a non-starter for being useful.

All of that is theoretically possible. I’m doubtful that LLMs will be the thing that gets us to that though.

Even if it is possible, I’m not sure if we will ever have the compute power to run all or even a significant portion of the world’s computations through LLMs.

Mechanics, and humans, are non-deterministic. Every mechanic works differently, because they have different bodies and minds.

LLMs are, of course, bad. Or not good enough, at least. But suppose they are. Suppose they're perfect.

Would I rather use an app or just directly interface with an LLM? The LLM might be quicker and easier. I know, for example, ordering takeout is much faster if I just call and speak to a person.

Old people sometimes call rather than order on the website. They never fail to come up with a query that no amount of hardcoded logic could begin to attack.

> Every mechanic works differently, because they have different bodies and minds.

Yes but the same LLM works very differently on each request. Even ignoring non-determinism, extremely minor differences in wording that a human mechanic wouldn’t even notice will lead to wildly different answers.

> LLMs are, of course, bad. Or not good enough, at least. But suppose they are. Suppose they're perfect.

You’re just talking about magic at that point.

But suppose the do become “perfect”, I’m skeptical we’ll ever have the compute resources to replace a significant fraction of computation with LLMs.

I think they're suggesting that some problems are trivially solvable by humans but extremely hard to do with code - in fact the outcome can seem non-deterministic despite it being deterministic because there are so many confounding variables at play. This is where an LLM or other for of AI could be a valid solution.

There would be bookmarks to prompts and the results of the moment would be cached : both of these are already happening and will get better. We probably will freeze and unfreeze parts of neural nets to just get to that point and even mix them up to quickly mix up different concept you described before and continue from there.

Companies want determinism. And for most things, people want predictability. We've spent a century turning people into robots for customer support, assembly lines, etc. Very few parts of everyday life that still boil down to "make a deal with the person you're talking to."

So even if it would be better to have more flexibility, most business won't want it.

Why sell to a company when you can replace it?

I can speculate about what LLM-first software and businesses might look like and I find some of those speculations more attractive than what's currently on offer from existing companies.

The first one, which is already happening to some degree on large platforms like X, is LLM powered social media. Instead of having a human designed algorithm handle suggestions you hand it over to an LLM to decide but it could go further. It could handle customizing the look of the client app for each user, it could provide goal based suggestions or search so you could tell it what type of posts or accounts you're looking for or a reason you're looking for them e.g. "I want to learn ML and find a job in that field" and it gives you a list of users that are in that field, post frequent and high quality educational material, have demonstrated willingness to mentor and are currently not too busy to do so as well as a list of posts that serve as a good starting point, etc.

The difference in functionality would be similar to the change from static websites to dynamic web apps. It adds even more interactivity to the page and broadens the scope of uses you can find for it.

Sell to? I'm talking about buying from. How are you replacing your grocery store, power company, favorite restaurants, etc, with an LLM? Things like vertical integration and economies of scale are not going anywhere.

When I reach for a hammer I want it to behave like a hammer every time. I don't ever want the head to fly off the handle or for it to do other things. Sometimes I might wish the hammer were slightly different, but most of the time I would want it to be exactly like the hammer I have.

Websites are tools. Tools being non-deterministic can be a really big problem.

So basically you say the future of web would be everyone gets their own Jarvis, and like Tony you just tell Jarvis what you want and it does it for you, theres no need for a preexisting software or to even write a new one, it just does what's needed to fulfill the given request and give you the results you want. This sounds nice but wouldn't it get repetitive and computationally expensive, life imagine instead of Google maps, everyone just asks the AI directly for the things people typically use Google maps for like directions and location reviews etc. A centralized application like maps can be more efficient as it's optimized for commonly needed work and it can be further improved from all the data gathered from users who interact with this app, on the other hand if AI was allowed to do it's own thing, it could keep reinventing the wheel solving the same tasks again and again without the benefit of building on top of prior work, while not getting the improvements that it would get from the network effect of a large number of users interacting with the same app.

You might end up with ai trying to get information from ai, which saves us the frustration..

knows where we’d end up?

On the other hand the logs might be a great read.

But it is still very early days. And if you have the AI generate code for deterministic things and fast execution, but the ai always monitors the code and if the user requires things that don't fit code, it will jump in. It's not one or the other necessarily.

Determinism is the edge these systems have. Granted in theory enough AI power could be just as good. Like 1,000,000 humans could give you the answer of a postgres query. But the postgres gonna be more efficient.

> Because nobody actually wants a "web app". People want food, love, sex or: solutions.

Talk about a nonsensical non-sequitur, but I’ll bite. People want those to be deterministic too, to a large extent.

When people cook a meal with the same ingredients and the same times and processes (like parameters to a function), they expect it to taste about the same, they never expect to cook a pizza and take a salad out of the oven.

When they have sex, people expect to ejaculate and feel good, not have their intercourse morph into a drag race with a clown half-way though.

And when they want a “solution”, they want it to be reliable and trustworthy, not have it shit the bed unpredictably.

Exactly this. The perfect example is Google Assistant for me. It's such a terrible service because it's so indeterministic. One day it happily answers your basic question with a smile, and when you need it most it doesn't even try and only comes up with "Sorry I don't understand".

When products have limitations, those are usually acceptable to me if I know what they are or if I can find out what the breaking point is.

If the breaking point was me speaking a bit unclearly, I'd speak more clearly. If the breaking point was complex questions, I'd ask simpler ones. If the breaking point is truly random, I simply stop using the service because it's unpredictable and frustrating.

Ways to start my morning...reading "When they have sex, people expect to ejaculate and feel good, not have their intercourse morph into a drag race with a clown half-way though."

Stellar description.

This thing of 'look, nobody cares about the details really, they just care about the solution' is a meme that I think will be here forever in software. It was here before LLMs, they're now just the current socially accepted legitimacy vehicle for the meme.

In the end, useful stuff is built by people caring about the details. This will always be true. I think in LLMs and broadly AI people see an escape valve from that where the thinking about the details can be taken off their hands, and that's appealing, but it won't work in exactly the same way that having a human take the details off your hands doesn't usually work that well unless you yourself understand the details to a large extent (not necessarily down to the atoms, but at the point of abstraction where it matters, which in software is mostly about deterministically how do the logic flows of the thing actually work and why).

I think a lot of people just don't intuit this. An illustrative analogy might be something else creative, like music. Imagine the conversation where you're writing a song and discussing some fine point of detail like the lyrics, should I have this or that line in there, and ask someone's opinion, and their answer is 'well listen, I don't really know about lyrics and all of that, but I know all that really matters in the end is the vibe of the song'. That contributes about the same level of usefulness as talking about how software users are ultimately looking for 'solutions' without talking about the details of said software.

Exactly, in the long run it's the people who care the most who win, it's tautological

> When they have sex, people expect to ejaculate and feel good, not have their intercourse morph into a drag race with a clown half-way though.

speak for yourself

We're used to dealing with human failure modes, AI fails in so unfamiliar ways it's hard to deal with.

The issue with not having something deterministic is that when there's regression, you cannot surgically fix the regression. Because you can't know how "Plan A" got morphed into "Modules B, C, D, E, F, G," and so on.

And don't even try to claim there won't ever be any regression: Current LLM-based A.I. will 'happily' lie to you that they passed all tests -- because based on interactions in the past, it has.

Designing a system with deterministic behavior would require the developer to think. Human-Computer Interaction experts agree that a better policy is to "Don't Make Me Think" [1]

[1] https://en.wikipedia.org/wiki/Don%27t_Make_Me_Think

This is such a massive misunderstanding of the book. Have you even read it? The developer needs to think so that the user doesn't have to...

My most charitable interpretation of the perceived misunderstanding is that the intent was to frame developers as "the user."

This project would be the developer tool used to produce interactive tools for end users.

More practically, it just redefines the developer's position; the developer and end-user are both "users". So the developer doesn't need to think AND the user doesn't need to think.

I interpreted it like "why don't we simply eat the orphans"? It kind of works but it's absurd, so it's funny. I didn't think about it too hard though, because I'm on a computer.

That book is talking about user interaction and application design, not development.

We absolutely should want developers to think.

As experiments like TFA become more common, the argument will shift to whether anybody should think about anything at all.

What argument? I see a business model here, not an argument.

I meant "the discourse", "the conversation we are all having", interpreting the experiment in TFA as an entry in that discourse.

..is this an AI comment?

No, I wouldn’t say that my hypothesis is that non-deterministic behavior is good. It’s an undesirable side effect and illustrates the gap we have between now and the coming post-code world.

AI wouldn't be intelligent though if it was deterministic. It would just be information retrieval

It already is "just" information retrieval, just with stochastic threads refining the geometry of the information.

Haha u mean it isn't AGI? /s

Web apps kind of already do that with most companies shipping constant UX redesigns, A/B tests, new features, etc.

For a typical user today’s software isn’t particularly deterministic. Auto updates mean your software is constantly changing under you.

I don't think that is what the original commenter was getting at. In your case, the company is actively choosing to make changes. Whether its for a good reason, or leads to a good outcome, is beside the point.

LLMs being inherently non-deterministic means using this technology as the foundation of your UI will mean your UI is also non-deterministic. The changes that stem from that are NOT from any active participation of the authors/providers.

This opens a can of worms where there will always be a potential for the LLM to spit out extremely undesirable changes without anyone knowing. Maybe your bank app one day doesn't let you access your money. This is a danger inherent and fundamental to LLMs.

Right I get tha. The point I’m making is that from a users perspective it’s functionally very similar. A non deterministic llm or a non deterministic company full of designers and engineers.

Regardless of what changes the bank makes, it’s not going to let you access someone else’s money. This llm very well might.

Well, software has been known to have vulnerabilities...

Consider this: the bank teller is non-deterministic, too. They could give you 500 dollars of someone else's money. But they don't, generally.

Bank tellers are deterministic though. They have a set protocol for each cases and escalate unknown cases to a more deterministic point of contact.

It will be difficult to incorporate relative access or restrictions to features with respect to users current/known state or actions. Might as well write the entire web app at that point.

I think the bank teller's systems and processes are deterministic, but the teller itself is not. They could even rob the bank, if they wanted to. They could shoot the customers. They don't, generally, but they can.

I think, if we can efficiently capture a way to "make" LLMs conform to a set of processes, you can cut out the app and just let the LLM do it. I don't think this makes any sense for maybe the next decade, but perhaps at some point it will. And, in such time, software engineering will no longer exist.

The actual app is the set of processes.

The rate of change is so different it seems absurd to compare the two in that way.

The LLM example gives you a completely different UI on _every_ page load.

That’s very different from companies moving around buttons occasionally and rarely doing full redesigns

And most end users hate it.

> who wants web apps to behave differently every time you interact with them?

Technically everyone, we stopped using static pages a while ago.

Imagine pages that can now show you e.g. infinitely customizable UI; or, more likely, extremely personalized ads.

No.

When I go to the dmv website to renew my license, I want it to renew my license every single time

> infinitely customizable UI; or, more likely, extremely personalized ads

Yeah, NO.

Ah, sure; that's why everyone got Adblock and UBo in first place. Even more under phones.

Small anecdote. We were releasing UI changes every 2 weeks making app better more user friendly etc.

Product owners were happy.

Until users came for us with pitchforks as they didn’t want stuff to change constantly.

We backed out to releasing on monthly cadence.

Like, for sure you can ask the AI to save it's "settings" or "context" to a local file in a format of its own choosing, and then bring that back in the next prompt ; couple this with temperature 0 and you should get to a fixed-point deterministic app immediately

There still maybe some variance at temperature 0. The outputted code could still have errors. LLMs are still bounded by the undecidable problems in computational theory like Rices theorem.

> couple this with temperature 0

Not quite the case. Temperature 0 is not the same as random seed. Also there are downsides to lowering temperature (always choosing the most probable next token).

Why wouldn't the llm codify that "context" into code so it doesn't have to rethink through it over and over? Just like humans would. Imagine if you were manually operating a website and every time a request came in you had come up with sql queries (without remembering how you did it last time) and manually type the responses. You wouldn't last long before you started automating.

I think it's actually conceptually pretty different. LLMs today are usually constrained to:

1. Outputting text (or, sometimes, images).

2. No long term storage except, rarely, closed-source "memory" implementations that just paste stuff into context without much user or LLM control.

This is a really neat glimpse of a future where LLMs can have much richer output and storage. I don't think this is interesting because you can recreate existing apps without coding... But I think it's really interesting as a view of a future with much richer, app-like responses from LLMs, and richer interactions — e.g. rather than needing to format everything as a question, the LLM could generate links that you click on to drill into more information on a subject, which end up querying the LLM itself! And similarly it can ad-hoc manage databases for memory+storage, etc etc.

Or, maybe, just not use LLMs?

LLM is just one model used in A.I. It's not a panacea.

For generating deterministic output, probably a combination of Neural Networks and Genetic Programming will be better. And probably also much more efficient, energy-wise.

For some things you absolutely want deterministic behaviour. For other things, behaviour that adapts to usage and the context provided by the data the user provides sounds like it could potentially be very exciting. I'm glade people are exploring this. The hard part will be figuring out where the line goes, and when and how to "freeze" certain behaviours that the user seems happy with vs. continuing to adapt to data.

Every time you need a rarely used functionality it might be better to wait 60s for an LLM with MCP tools to do its work than to update an app. It only makes sense to optimize and maintain app functionalities when they are reused.

Llms are easily made deterministic by choosing the selection strategy. More than being deterministic they are also fully analayzable and you don't run into issues like the halting problem if you constrain the output appropriately.

Why do good thing consistently when we can do great thing that only works sometimes??? :(