My guess is they do something like "Hey dingus, make my app send emails" and then Claude or GPT just goes off and does a thing that makes it look superficially like it sends emails but it really only sends email exactly on Tuesdays and if the subject line is "send email to user". And there's no tests, so who knows if the next LLM can fix the bugs without introducing new ones.
For the last several years (since GPT 4o) I have written several apps in use by people, making money, entirely with AI/LLMs (me neither writing nor reviewing the code in any meaningful fashion - other than high level architecture, schemas, etc.) and - yes, in a few hours it can do things that would take a normal human weeks (if ever!). But left unconstrained, it will just pile more and more garbage on the pile.
Fable MAX is the thing that gets me much closer to "just send emails" but even then it doesn't look in my specs directory for the spec, it just goes off and does a Jurassic Park-style "It's a Ruby-on-Rails system! I know this!" and disregards all the other ways we send email and writes its own thing. And often I'll go "Where's the button to do X" and it will say "You're right! Nobody asked for it, so this page is an orphan!"
I happen to use Superpower's (https://github.com/obra/superpowers) "brainstorm -> spec -> plan" workflow in e.g. Fable MAX (for anything non-trivial) then I have Fable send to GPT 5.6 Sol XHIGH for execution, with Fable (either the original, or a separate one, depending on the criticality of the task and the blast radius) being the critical reviewer.
Even then, though, I need to continually guide it against the norms and conventions of the codebase/app, because it makes a ton of assumptions.
It doesn't surprise me that if people don't take a fairly rigorous approach to AI-software development then they'll end up with a mess. Even if you buy into "just re-write it" (I happen to think that's where we're ending up) - we aren't there yet and without e.g. a strong test suite, re-writing it is just as likely to create more bugs than it is to fix the existing ones.
Back in the olden days (2015-ish?) KLM was having a really, really cheap business fare sale JFK-AMS; I snagged it with Delta miles (if I recall correctly) - and flew there and back in their 747 in the upper deck (just to take the flight; didn't have anything to do in AMS). It was really quite nice; it was the first and apparently last time I've taken the 744. I'm really glad I was able to do it.
We have some broad shapes - it’s a finite set of “things that are interesting to us” and the dataset is bounded. It’s not “Google Image Search”. But it is kinda like “we have a giant pile of PDFs, pictures, etc and the user wishes to run an arbitrary query on them and extract the information they want.
Ex: “I need the to know $something about the data embedded in the corpus, that look like excel data with line charts describing some particular class of metric that are to the left of gray dogs and are about $something_else earlier in the document”
Gemini has a very specific mode where it has been trained on making boxes normalized to a 1000x1000 grid (https://docs.cloud.google.com/gemini-enterprise-agent-platfo...) and in our experience this “just works” AND is very fast on 3.5 and 3.1 models without needing much thinking (so it is not terrifically expensive).
(BTW A+++ gold star triple thumbs up give this person a bonus to whomever did that magic it basically made this task for us tractable. When we first found it nobody else had anything like it - it’s worked so well I haven’t felt any need to look. )
So we say, “Hey Gemini draw box_2d […] around #{things we are interested in}” and then it is pretty easy to then go - ok if this is here and that is there, let’s slice the image in this particular way, making sure to overlap by some amount because the boxes are fuzzy, then send the chunks to a thing that turns it into JSON, then we use something like edge detection to reconstruct the whole from the parts. (Squint and it looks like whole genome shotgun sequencing)
I calculate* the appropriate overlap and the slicer overlaps a certain amount of the previous slice. There is some post-processing assembly required, but it's trivial.
[*] SWAG line height, trial and error to figure out the right amount of overlap given LLM error rates, etc.
I do OCR of images, and that's exactly what I do. I take one big image and slice it into many smaller ones, and send those to the LLM. Perfect every time, unlike using the whole image which resulted in hot garbage.
I'm not saying they are not trying - I'm saying we're inventing new problems faster than any Lab can:
1) Identify the gaps
2) Determine how to fix them
3) Implement a fix (especially if that fix is: identify and find experts)
4) And judge the result
How do they know [person] is an expert in [some field]? How do they find that person? How many experts are necessary to give the right information? How do we evaluate the results, especially if it's novel?
You can find a lot of people who disagree on many topics, and those turtles go all the way down.
I'm not in disagreement that your work will help reduce hallucinations and improve model performance! It is.
I predict (I hope I'm wrong!) that we're going to hit some asymptote that is not at 0% hallucinations (and I would even put a substantial nonzero probability that "overall" hallucination rate bottoms out at some minimum and then slowly grows because we just can't keep up with the new garbage we throw at it).
I'd have to imagine there are wildly diminishing marginal returns to additional SFT/post-training passes.
There are a bounded number of (useful) derivations/combinations of Duff's device.
If Frontier Labs wish to reduce hallucinations on factual things, they will have to hire people (or the data providers will need to) to do fundamental research above and beyond what is available in extant literature and the web. IE if the LLMs want to lower precision error, they need to go out and actually find more expertise. If the wikipedia page for Pompey lacks data, where are they going to get it from? How would they even _identify_ that the page has holes?
Yes, they can digitize more books but that is untrustworthy data - if there were enough eyeballs on a particular work, it would be in the internet. If it's not, they'd need to hire the experts themselves. They need expert reviewers in virtually every interesting topic, which fundamentally is an intractable problem, especially since things change all the time. Maybe even uninteresting topics, too?
I dunno, it doesn't seem to me "more data" is the magic bullet here. Yeah, it will "help" but we're already on the flat part of the S shaped curve.
My take from trying to understand this stuff is some sort of algorithmic improvement is necessary to get another step change in how well LLMs perform in this area. I could be wrong!
Yes, for fun I tried to make a Mahjong solver and NONE of the SOTA frontier models could understand what they were looking at to determine tile occlusion/geometry to build the DAG.
I had to spoon feed it an algorithm - here's how you determine if a tile is on top of another one, etc. etc.
Anything that involves, well, "3d space" they don't seem to do very well on it at all (which makes sense, of course)
Agreed, my vibes tell me 4.6 is a better coder than 4.7. 4.7 is a much better strategic thinker and maintains overall "better architecture" than 5.5. 5.5 is way better than either at coding, but more expensive. So I have 4.7 do the planning/architecture, 4.6 does the coding, then 5.5 critiques and fixes it.
The other thing I suspect is that "Just give me True/False" cuts off a large amount of the search space a modern-day LLM uses to help it answer questions (you can see it in reasoning traces but the act of writing the explanation helps guide it toward a better answer and gives it better likelihood it backtracks on a bad decision).
If you let it spew out an explanation along with the answer, I'm curious if the accuracy will improve (I suspect it will).
Also, this is why investors and CEOs are so in love with "LLMs are the route to AGI!"
When some rich/powerful person says "I have to go to Davos, figure it out" their workers know so much context that no LLM is going to ever be able to incorporate, because it isn't written down and is idiosyncratic. (Really, though, the assistant will just say "you're going to Davos next week, the helicopter will pick you up at 3p on Friday" but you know..)
The rich person's assistant knows who else is on the corporate jet, and that X doesn't like Y, and so they should take a different plane. Or get a different accommodation. Oh, Person X doesn't like to fly on an empty stomach, so they should eat first, and that changes all sorts of other downstream implications. Oh, your best friend lives in this city, and I know you love to see them, so I'm going to send you a day or two early so you can meet up with them. etc. etc. etc.
The investor dream of "AGI" is modeled off of the army of employees that make investors/ceos/etc lives easier, and there is a nearly insurmountable gap between what LLMs can do, context they can get, and the availability of all of that information. (To me, the magnitude of this investor <> fundamental reality gap is the entirety of the "bubble". I love AI coding, but it's never gonna do the things investors think it can, to justify the crazy valuations)
Thank you; you’re right - context matters and now more than ever there are a ton of folks looking involuntarily. Grace is always needed, but now especially.
Yes! It reminds me of the tabs vs spaces argument. Yeah, you have your preference, but as long as everyone on your team uses the same convention it doesn’t matter
The Rails apps I’ve programmed with LLMs seem to work a LOT better than arbitrary python or ruby or JavaScript apps. I chalk that up to “there are a gazillion examples of omiauth in Rails that the LLM can’t really stray off the path. It just works.”
That means I let the agent do things the way it wants to, not because I have a preference. So we’re using turbo and Hotwire and whatever it is it’s doing. And I’m using React for some other problems. Not because I know React, but because the LLM does.
In golf it is said to “let the club do the work”. Over control leads to disaster. Same with LLMs. Not saying let it do whatever but if there are widely baked in conventions you’ll be far better off letting those do the work.
This… was a mistake on both you and the interviewer.
All interview questions - unless it’s impossible to twist your answer to fit this - is scoped to “… at work”. Nobody who asks “tell me about yourself” is asking you to talk about how you met your partner, how many cats you have, or that experience you had, that one time, at band camp. It would be redundant and awkward to literally say “… at work” at the end of every question. It’s totally 100% the intent of the interviewer.
This is interviewing 101 and unless this is your first ever interview I would find it odd, and stop you immediately and say “I meant, worst day at work”. They should’ve done that.
Unless they explicitly and unambiguously say “tell me about the day your mom and dog died in the same day when you found out you had cancer” they mean “tell me about your worst day _at work_.” And even if they ask about the time your dog died (they won’t), they are not asking you “tell me about the worst day you’ve had in your life”. They are asking “tell me about a time you experienced adversity and overcame it, exhibiting problem solving, resilience, and grit AT WORK. (Or - if you are operating in executive mode or you like to live dangerously - some non-work context that maps obviously and unambiguously to a work context).”
You failed the “knows how to interact with people in a professional setting” part of the interview. Or the “this person knows how to interview” part (which generally, but not always, correlates with experience and emotional maturity). Or the “read between the lines” part.
Yeah, inartfully asked questions - but also totally flubbed the answers.
Sorry, chalk it up to you had a bad interview or day or whatever, and never, ever forget the entire thing is scoped to “…. at work”.
People keep confusing single player vs. multiplayer and forgetting "jobs to be done".
Photoshop files are the lingua franca of the design world. If you're working with designers, they'll likely give you a PSD (replace PSD with other examples in other domains, etc.)
Sure, I could vibe code "make a tool that lets me create multi-layered canvasses etc." but if I want to use it with anyone other than me, I have to make sure that it's binary compatible, bit for bit, with PSDs (or whatever's required to open it in Photoshop and maintain the layers).
This makes no sense to do this unless I'm targeting Photoshop specifically and plenty of tools already do this.
Other than a way to burn money, I am completely unsurprised such a thing isn't widely available (I'm sure someone, somewhere is/has tried this).
For most people, single-player Photoshop is a means to an end. If I have sufficiently advanced AI I can just describe what I want and get the end result (a button, image, whatever). Or even just point it at an image and say "add gaussian blur here".
I would never try and vibe-code a new editor just to make images.
“I intentionally wrote the example code the way a beginner might. More experienced users would probably reach for solutions like:
Updating and checking the balance in a single UPDATE Using [check constraints]to ensure an account balance can never be negative.”
Not the author but presumably ALTER TABLE foo ‘ADD CONSTRAINT BalanceCantBeNegative CHECK( balance >= 0 )’
The major limitation is that macOS apps do not have to use the API and so there will always need to be a fallback to something like screen scraping for controls that don’t use it.
Zoom Desktop app is a prime example of this. Many of the windows (join a meeting, settings etc) are normal macOS ones, and those use AX buttons, but many are poorly / weirdly labeled (if at all).
But once the Zoom meeting appears, that’s all (?) custom, and so the best you can do is whatever Zoom decided to offer. The dreaded “this meeting is being recorded” pop up is a custom control and so doesn’t have AX at all; I have automation that basically looks for an appearing window and if it has “OK” just blindly click it and hope for the best.
Back in December the iOS app had a bug ( https://status.claude.com/incidents/6rrnsb1y0kbn) in which buying a subscription thru the Apple App Store would not register with the backend, so you’d be charged but not receive the plan entitlement.
I discovered this because I wanted to upgrade from free plan to the regular plan. I was charged, but remained in the free tier. Thinking it was a temporary bug, I tried buying the max plan. Same result.
I tried cancelling the plan and restarting but I when I went to buy the regular plan again, I was forever tagged as an “Apple” user and so could only manage the billing plan on the iOS app. I tried one more time, same result.
I tried interacting with the support bot and although it agreed that there was a bug and that it should be fixed and I should get a refund, my account never was able to get unstuck nor refunded. I lodged a refund request with Apple, which was relatively quickly refunded. The Bot never did escalate to a human as promised.
Even though the bug was ostensibly fixed, my account (personal email) remains in permanent limbo, unable to upgrade from Free to anything else (I tried again recently and same result - paid but stuck on free plan). I had to create a new gmail just to pay for Anthropic / Claude.
I find it interesting that all the trend lines start going negative around 2001. I wonder why that's not remarked upon? 9/11 itself was - obviously - epically terrible, but the impact of the event was recoverable.
Our response to it (Iraq war, forever wars, etc.) combined with the realization that the USA are be "the baddies" and we've been lied to since forever, probably might have been the thing that set all the dominos up.
COVID was the straw that broke the camel's back. Had we _not_ had the disastrous response to 9/11, I suspect we could've weathered COVID better (like the rest of the world has.)
http://www.mattrogish.com & https://www.twitter.com/mattrogish
Founder of https://www.ReactiveOps.com