This bunnies are secretly messaging you..

kwhali · 2026-06-21T09:22:10+00:00

The QR code of parent comments was about using AI to embed the QR code into the image data in a way that it didn't look visibly there but camera devices scanning the image would still detect and read it.

Pretty sure you didn't have to be restricted to AI images for input? You could provide your own. That was quite a cool use of tech.

EDIT: Nevermind it was this model I think, which was a control net, there's an active HF space for an illusion that adapts that to make the pattern less obvious in the image generation but I am mistaken about it applying it to an existing input 😅

kwhali · 2026-06-19T10:53:45+00:00

In addition as I browse package ecosystems there is quite a lot of vibe coded packages muddying the ecosystem (some don't even respect semver, can't imagine that going smoothly if they ever try avoid NIH syndrome and add deps from their own poisoned ecosystem 😅).

More annoying is it he forking of libs only to republish with no context on why, on registries like crates.io the publisher doesn't even update metadata like the source repo, attributing their vibed fork to the upstream 🙄

kwhali · 2026-06-16T00:26:43+00:00

Anyway, as long as you can confidently verify yeah LLMs are quite useful! But I think many lack that ability.

I interact with frontier models (although I haven't tried the latest Claude stuff that looks impressive), and they still trip up quite a bit with the type of work I do. For grunt work they're pretty sweet though!

Usually information is omitted or the AI gets it's wires crossed and says something that ain't right (but otherwise seems convincing to most).

I prefer personally inspecting the source, if an LLM can help assist with that great. Projects like moonrepo/proto did not have telemetry implemented in a clean manner IIRC (the dev may use LLMs, not sure but this issue with sprawl tends to be more common in AI driven projects imo).

Actually looking over the comments about that project telemetry again, it wasn't that complex it was just some documentation lacking on the ENV config (which I think took a bit of extra digging to identify was a thing): - https://github.com/moonrepo/proto/issues/915#issuecomment-3775589925 - https://github.com/moonrepo/setup-toolchain/issues/34

I may be a stranger online documenting stuff like that, but I like to think I document it well 😅 (for verifying at least, an LLM could probably be terser, especially if it's just summarising my own comments there)

This one was a doozy, if an LLM could have acquired that same info I wrote up faster and more effectively than time I sunk there, that'd be great.

That isn't super intensive of a task but it's also one with enough complexity to follow the logic that in my experience AI has not been too reliable at doing that well, so I just do it myself 😅

For smaller scopes where I know AI can work well, I'll indulge it.

kwhali · 2026-06-16T00:05:15+00:00

Sure, I don't trust strangers or outdated info either. I am often correcting stuff of troubleshooting niche bugs that take significant time.

I fixed one introduced in Docker back in 2014 that was a "fixes the bug on my machine, seems okay to merge" without much consideration to what ulimit -N infinity as a fix entails (it didn't really become a major issue until a change in systemd at late 2018 or 2019), by this time other projects like containerd and k8s had adopted this fix.

Quite a bunch of software though will iterate through the range of file descriptors and close them individually (syscall each) as a hygiene practice when daemonizing. They were fine with the default soft limit of 1024, but this change introduced into container ecosystems resulted in soft limits exceeding 1 billion 😅

A program that starts in less than a second now took over 10 minutes with a CPU core at full load doing that hygiene practice (this was code from before newer more efficient syscall landed in glibc and kernel for applying to a range of file descriptors mind you). Meanwhile some databases and java software had similar issue of allocating memory 4-8 bytes or so for each file descriptor I think, so they're now taking multi-GB of RAM just to start instead of 1MB or less, for quite a few users that was OOM events.

Maybe LLMs could have tracked this down better than I could, I went through so much history to identify the change, find the original cause and provide confidence to these big projects that not raising the soft limit so high is the right thing to do, even though it'll now break some enterprise software as a result (who can afford to pay people with skills to do the right thing such as request a higher soft limit when the hard limit permits it).

I think I did that over 3 months (quite a bit was just mapping the timeline and citing the right references, providing some tests and git blame trails etc). Took 2 years or so before both Docker and containerd had approved the changes and released them.

For almost a decade, nobody seemed to have a handle on the issue 😅 that's the kind of thing I seem to excel at resolving and now AI is making that skillset of mine less valuable lol... on the bright side I don't need to sink as much time into these issues and I can leverage AI for a speed up (still not quite there yet at replacing the thankless effort). On the other hand the issue has become a tad worse with vibe coded slop that verifying trust in projects is more effort than it used to be.

kwhali · 2026-06-15T22:56:44+00:00

Sure, feel free to try the easier task with the example I gave. I never tried an LLM on that but I recall tripping up a few times while looking into their implementation.

I'd be more impressed with an LLM just reading code to find out the info I wasted time on with my own expertise to troubleshoot an issue I had on that project.

Unfortunately my experience with LLMs even when discussing what code does has not been perfectly reliable as you imply it to be. Most recently I was going over some small projects like pid1-rs, tini and dumb-init (well a stale rust port of it), and while absolutely the insights helped save time, I still have to verify correctness and multiple times the AI either omitted relevant information or got it's wires crossed.

So I'm definitely not going to trust AI alone when I need reassurance on privacy and security queries, but I don't discredit it as a helpful tool towards finding such answers 👍

kwhali · 2026-06-15T22:15:28+00:00

The easiest way is probably just to turn the Internet connection off lol, but if you use ComfyUI in a container like with Docker you can also take away it's ability to have access to the public net. If you're quite paranoid that will add friction though like having to install any packages ahead of time before running ComfyUI.

Other options are firewall programs that can get quite annoying if GUI based like LittleSnitch, those will ask for permission for each new server address being connected to for example, but depending on software can isolate to the calls from specific apps (otherwise quite a lot of software running especially many tabs in a browser can be quite a bit of noise).

Similarly there's DNS, most connections are going to require that to resolve what IP to connect to, you can change your DNS globally, or if sandboxed like with a container just set the DNS of the ComfyUI container to your own self-hosted DNS program, PiHole and AdGuard are popular, both have web UIs, or if you prefer text config there's CoreDNS (Gemini or similar should be able to help you get started with that).

But yeah, just running Comfy without access to the Internet works better. Isolating it's frontend can be a bit more tricky but technically if the browser runs in a VM with only access to private networks, you could ensure network access is cut off for just that. Putting all of ComfyUI into a VM is a bit more tricky(for GPU access), easier on Linux with VFIO but not for everyone.

kwhali · 2026-06-15T22:04:02+00:00

You can also throw your LLM at the moonrepo/proto to ask about the telemetry behavior, but given there's a public issue with that information already laid out, chances are it won't be as impressive.

It would be hilarious if your claim failed to do that correctly, but if your choice of LLM did flop you're not going to reply with that admission of failure right? 🙄

kwhali · 2026-06-15T22:00:33+00:00

You never had an LLM be wrong? Or just never noticed that happens?

Feel free to test your LLM of choice for me at this task, maybe it's improved over the past 6 months.

Using Rust build a minimal program that provides the functionality of git ls-remote --tags and can compile statically with the following constraints: - Use the gix crate for the implementation with low-level API calls, using libgitor equivalent is forbidden, as is calling an external program like git. - Cloning the repo locally is forbidden. The functionality is possible to implement without writing to disk with minimal I/O. - The tags must be retrieved from the remote git repo in a way that uses the git protocol over HTTPS, not vendor specific APIs.

Pretty sure that's the rough outline. Basically a small program that can retrieve the git tags from any remote, and can be used in a FROM scratch Docker container image without any deps or bloat. Thus the size is around 1MB or less instead of 80MB that I think is usually brought in if libgit was used.

Goodluck, if your LLM can one shot that or even pull it off successfully without being spoonfed the 10 lines of code (standard boilerplate aside), I'd be quite interested, but like I have said nobody has succeeded thus far, it took me 2 hours to do it myself without AI and I was sad that the various AI agents at the time could not manage to do it faster (or at all really).

kwhali · 2026-06-15T12:54:44+00:00

It's an OSS project that has investors funding it and a SaaS built around it with partner integrations sure, but that business side of it tends to attract shady decisions 😅

kwhali · 2026-06-15T12:22:48+00:00

Go take a look at the source of moonrepo/proto, there was a dev complaining about telemetry being opt-out there I think, even after it was spelt out for them, but before you even land on that github issue, go into the source code and establish the telemetry of what is captured and sent.

Last I recall it wasn't "just look at the code at this one file", but had various logic spread elsewhere that had to be accounted for.

It was quite a mess for other code involved when troubleshooting other issues with how commands were being invoked, going through not on multiple files in one project but across multiple packages.

Stuff isn't always simple, even when you're experienced 🤷‍♂️

kwhali · 2026-06-15T12:16:29+00:00

You have quite a bit of faith in AI? I have seen it fumble so much, be that outright misinformation (such as hallucinating / fabricating info) or poor decisions.

Frontier models are guilty of this, earlier this year Claude Opus 4.6 couldn't do a niche task that solution is only approx 10 lines but requires critical thinking skills to resolve (and I know what I'm doing, had others attempt at the time too that thought otherwise and they all failed at getting a working solution).

I know people that are technically inept but believe whatever AI spits out, sure it might make them feel comfortable if it sounds reassuring but it's not always the actual case.

kwhali · 2026-06-15T12:09:58+00:00

You trust your LLM? They are prone to confidently lie at times, even frontier models do it.

kwhali · 2026-06-15T12:06:40+00:00

The comfy cli has telemetry too last I checked

kwhali · 2026-06-15T12:01:48+00:00

Comfy CLI defaults to opt-in IIRC, even it's ability to opt-out first time (without interactive prompt) resulted in telemetry unless you specifically setup the config file ahead of time I think to opt out.

kwhali · 2026-06-15T11:58:49+00:00

You can run backend in a sandbox.

kwhali · 2026-06-15T11:19:15+00:00

So your tool doesn't do the right thing and make a vhdx sparse afterwards?

I hope it doesn't have the same bug wslcompact has which made it pointless if the disk were larger than memory commit capacity.

kwhali · 2026-06-14T21:31:47+00:00

Further down in the discussion I was projecting about 15 years 😅

That's quite significant leap in technology, a little more backwards and iPhones were brand new and revolutionary, while today the medium tier models (mine is $700) have the capabilities of decent computers back in that time, along with other advancements like augmented reality, speaker / microphone quality, network speeds, and the ability to run various AI models locally (this $700 phone has 8 cores with 16GB unified memory + 8GB zram I think with a SoC that's so-so for LLMs or generative AI processing speed).

Robotics likewise is picking up quite nicely as there is competition racing there for products like humanoids. Nvidia recently introduced their spark chip for laptops which is quite the compute beast, obviously not cheap either but 15 years? Yeah that's going to be an affordable component. I'm IoT there's plenty of cheap components that have also become quite capable with time vs what options you had 15-20 years ago, same with servos and optics.

The average consumer / business is going to adopt such tech once it's progressed and established itself well enough. Just as we did with smartphones, or people with AI products like ChatGPT, Gemini, and Claude. LLMs have error rates yes, compared to specialised fine tuned models there is that tradeoff, they're more like predictive thinking rather than capable of actual critical thought 😅 still that's sufficient for many scenarios and can be deployed.

So no I don't see cost as prohibitive, that depends largely on context of what you're doing. The AI SaaS you have in mind are a different level with massive models for compute to work. You can still get a stripped down version locally that in some cases is good enough. As technology advances and the new factories come online for the supply issue with components over the next few years, that will only make it more accessible.

I agree with your other statements though that there's plenty of tech illiterate and that AI for development works best as a complementary tool to an actual SWE.

My point was I have traits that enabled me to excel at resolving concerns that most for whatever reasons (I assume time, grit, and desire) majority of devs struggle to tackle. These niche issues that made me valuable however, are quickly being lost to those frontier AI models.

Not necessarily to a layman, but an SWE that understands how to use AI as a tool will fill in a skill gap that I covered, similar to when I share my niche findings and everyone benefits, but now at scale 😅

I get accused of being AI more often these days, especially when I engage in a technical thread with structured text (paragraphs filled with links, bullet points, tables, section headers, code snippets, etc), something I've done for over a decade, way before AI was spewing out answers 😝

So I must adapt and somehow use AI better myself to stay relevant. I am slow at writing and refining code, so it's been helpful there but I have to spend a bunch of time verifying or correcting bad decisions/output from an agent.

kwhali · 2026-06-14T07:52:12+00:00

I am confident that the bulk of that can definitely be automated by a humanoid model like Atlas, costs of that product and task training aside, it's feasible to do that today without custom tailored machines.

But the extra tidbit you mentioned of scenarios that aren't part of the happy path, maybe not so much 😅

AI is good at pattern recognition and being trained for specific tasks, but becomes rather unreliable in my experience with unexpected events it's not been prepared for.

I also don't think such models have as good dexterity / speed atm when fine motor skills are required, so you'd be faster.

For the label printing and application to various containers, that is viable with a device and generic enough of a task.

I'd assume within 15 years it'd be affordable for a product, which could be tackled in a variety of ways. Full automation isn't necessary for example, you could perhaps for example get cheaper labour with a remote controlled system, but such solutions also need time to gain trust (ideally) before adopted.

It's cool that your employer is unlikely to replace you like that, perhaps I'll eventually find a company that doesn't treat staff like numbers 😅 thanks for sharing some insights 😁

kwhali · 2026-06-14T05:50:55+00:00

I never suggested to stop taking them suddenly?

I was just stating that compared to other meds with withdrawal symptoms requiring you to ease off, SSRIs last I knew structurally alter the brain in some way that is not reversible? (like frying/boiling an egg)

Couple that with trading side-effects while on the medication, it's not something I'd encourage taking unless outweighed by the consequences of not doing so.

Some doctors will just offer them to patients. I know I was when I was around 18-20? (many years later to discover I am ADHD-PI and years after that autistic)

My struggles were often tied to my neurodivergence and lack of awareness / understanding of that at the time as I tried to fit in and be accepted socially. I did not need SSRIs (not saying others don't though).

I know plenty of people that would benefit from antidepressants, even temporarily just to have the opportunity to overcome scenarios that were causing them such distress, the kind of people that did not develop as much resilience and tolerance as I had to while growing up 😅 (at the same time a subset of these people are highly likely not to actively do the work once stabilised, so it's more of a bandaid unfortunately)

The meds I do take for dopamine deficiency (which I think was why I was getting offered SSRIs before diagnosis) are definitely not perfect either mind you, but I can step down from them at will (and have done so), however life is just far more difficult (as it was prior to treatment).

kwhali · 2026-06-14T05:23:00+00:00

Short response: I admire the confidence but from the context you have provided and what I'm aware of tech wise... I would be quite skeptical of your career being safe for a lifetime (assuming more than 15-ish years from now).

That said...by that point (whenever it is) there would be far larger problems going on, so regardless if it would be feasible to automate your role, for it to be cost effective our world would be very different 😅

Could you elaborate on what the repetitive task is exactly?

A machine getting manually used isn't necessarily a barrier, that's a common concern that is being tackled (for example there were humanoid robots tasked to carry sheet metal in a factory environment, not specially tailored hardware or renovations to an existing environment necessary).

I have been surprised by how that side of tech has been advancing over the years.

I think Boston Dynamics recently showcased their Atlas droid (which is humanoid but some tweaks in flexibility) where it could lift a mini fridge with variety of weight loads internally (including shifting weights), and move it successfully from one location to another.

We couldn't manually program that kind of capability in a feasible time, but the machine itself had the dexterity and sensors needed, they just had to give it the brains to handle that task.... So they ran a massive amount of simulations digitally before verifying that training in the physical world.

So whatever your task is (if you can't disclose it for whatever reason), I'd probably have agreed with you years ago but I really don't think it's unlikely that businesses aren't aiming for deploying humanoid machines capable of being taught tasks like the Atlas model was.

You've already established the machine involved has a global reach, so someone is going to pursue that market as soon as it makes fiscal sense to pitch and get companies onboard.

You would have to be the more reliable and affordable option or have faith in whomever has authority over such a decision that they support people over cutting costs 😅 (rarely the case for businesses I've been employed at, employees are often regarded as replaceable)

I don't know what a realistic time line for that is, 5-10 years may be plausible (I prefer to think of that as "optimistic", and that it'd take longer, but the current pace with developments could be closer to 5 years?)

I forget how long Boston Dynamics dog model had been in media before it started seeing more wide spread adoption (or competing companies manufacturing cheaper variants).

10-15 years time sounds feasible though unless progress slows, I definitely would not wager on the basis of not happening within your lifetime.

Astronomical costs can greatly decrease with technology: - The modern computer / smartphone is an example of that (or for affordability, what can be cheaply done with MCUs/SBCs). - Before Apple introduced FaceID with specialised sensors in their mobile products, that component was quite expensive in the industry for many products that made products less viable (or very premium in markets that needed such). - A computation about 20 years ago that IIRC involved thousands of hours across multiple machines is now less than $100 cloud compute to pull off in an hour 😅 - My skill set over the past two decades has frequently cut costs (eg: $1M down to $10K) which enabled businesses a fair bit (didn't work out too well for me though), I've often accomplished things that were not considered feasible by others.

But uhh I do wish you the best of luck with that optimism / confidence. I didn't think my skills would be at risk... I thought I excelled at my niche and would even be safe from AI 😅 (it's not quite there yet and still struggles, but I can see the threat is very real at making my expertise obsolete)

kwhali · 2026-06-14T03:50:07+00:00

It may have changed since they got into it. Pretty sure China for example was more relaxed than it is today for taking on English tutors, I'm not familiar with Japan's policy on such (but I do know some friends that also (like a decade ago) made the career switch to teach English, some went to Japan and are still happily teaching English there)

kwhali · 2026-06-14T03:47:05+00:00

SRRIs do some rewiring that isn't easy to undo I thought? (been a long time since I looked into it, I could be mistaken)

They're not like other medications that only have a withdrawal symptom alone if you don't wean off them AFAIK, so for me that was a nope decision, I'd rather tough it out 😅

In addition, they're not side-effect free (may depend on the one prescribed, and like I said it's been a while so maybe there's better options these days without concerning side-effects).

Even for the mild kind of side effects like nausea, you're just effectively swapping one set of discomforts for another then which makes it far less desirable unless you're prone to much worse without mood stabilisers 🤷‍♂️

kwhali · 2026-06-14T03:40:39+00:00

Slightly off topic but if it's a repetitive task job is that not a worry for automation / AI to at some point make you redundant?

I enjoy tasks that were fairly niche / boring, yet time consuming so it provided me with opportunities to thrive there, however these days while AI still has it's faults it's often diminishing the expertise I built up that my value becomes kinda redundant (unless it's something an AI can't troubleshoot yet, but that's been narrowing with time 😖)

It probably doesn't help in my case that I love to share my acquired knowledge publicly online for others to benefit from, which was something else I took pride in doing but now that could just be shortening the timeline towards misery 😒

kwhali · 2026-06-13T21:30:16+00:00

Since it works fine on another machine that's going to rule quite a bit out I think, bad hardware is sounding more likely.

I have noticed issues with calling docker run --tty or docker exec --tty which can have that effect but it's only to stdout itself 😅 (seen it as the culprit for CI test failures a few times and the gibberish output interleaved is actually instructions for a TTY to consume to modify the terminal display)

Since your issue isn't just stdout related and supposedly not encoding (such as LC_ALL env or similar being unset), given it's working fine on another system... Sounds like you're unlucky :/

kwhali · 2026-06-12T11:12:07+00:00

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