Is this LLM psychosis? So much tending and conversing with the matmuls but what was the outcome? Are people who get this into it more successful somehow? It reminds me of people who take drugs and get "revelations" but then are not particularly over represented in the group of successful people for all of their deep insights.
> It reminds me of people who take drugs and get "revelations" but then are not particularly over represented in the group of successful people for all of their deep insights.
This depends on where you're looking for "successful" people.
I generally agree with you - of those people who might report "revelations" through hallucinogenic drugs, the majority may misinterpret their drug-induced experience and hence be more confused / lost than before.
On the other hand, it can still be true that among those who eventually do have genuine spiritual insight, having used hallucinogenic substances is overrepresented compared to the general population.
Quoting from [1], where the author tried to find spiritually advanced individuals:
> Approximately 52% of
participants had used hallucinogenic drugs at
some point; none reported these as the trigger
that led to PNSE.
PNSE = Persistent Non-Symbolic Experience.
My point is: while there are certainly people who go way overboard with the LLM stuff, that is not at odds with skillful use of LLMs being overrepresented in successful people.
I see now that you didn't make that point, but I already typed this all out and I'm gonna leave it.
LLMs vs psychedelics are an interesting comparison: psychedelics lower the threshold for the epiphany sensation, arguably LLMs do the same through agreement (‘sycophancy’).
With psychedelics you see the upsides in engineers who come to work the next day with designs informed by massive insights, and the downsides in people whose ‘massive insights’ result in socially abnormal behaviours.
LLMs seemingly provide validation and support, something very lacking in most lives. The distance between thinking loosely about, say, an app and getting positive feedback and absurd market predictions triggers similar ‘revelations’ in people with no meaningful context, and plays on the hopes of those who do. Much like with psychedelics, though, there is a self-supported self-validated cycle going on, prone to flights of excess.
Coming out publicly about doing drugs is just not something that smart people usually do.
There's a lot of stigma about it and a lot of opinionated people who don't know anything about them and still have a lot of judgements.
Then there are these people calling psychedelics hallucinogens. The former can give spiritual revelations and the latter gives vividly realistic, usually nightmarish, hallucinations.
There are also people putting an equal sign between crack cocaine and psylocibine mushrooms. But I don't think an addict will rob a petrol station with a screwdriver just to get another dose of magic mushrooms.
In such surroundings, it's just not a good idea to publicly say anything about drugs, unless you're so rich or known for your expertise, that you can shoulder some negative judgement and it's implications.
Psychosis would be a mental illness with symptoms like losing track of reality. I think there might actually be a bit of an anti-AI psychosis where individuals are projecting their fear and paranoia onto others and seeking confirmation bias. The need to dismiss the success others are having with AI could be triggered by personal insecurities. And of course deep paranoia is one of the classical symptoms of an actual psychosis. Just holding up a mirror here.
BTW. I have friends and relatives that have dealt with an actual psychosis. Not fun to experience up close. So, I don't want to take this metaphor too far. But if we're using big words like psychosis here, you might want to examine your motives, insecurities and reasoning a bit.
I've played with agentic AIs for coding and other use cases and have had some successes and failures. I'm fairly impressed with some stuff that is possible now and I use technology pragmatically. As I always have throughout my 30 year career.
For any new thing, there are always early adopters and those who really don't get it. And most other people let the early adopters figure things out and then end up copying what works some months/years later. And you always have some stragglers that can't or won't adapt that can't be helped.
Most of what this person describes in the article is very reasonable. Codex might not be the best model. But in terms of UX, OpenAI is getting a few things right that starting to make a difference. It's only a few months ago that their desktop app launched. It has gone through a pretty rapid evolution. As of a few weeks ago (it's that recent) you can install skills to connect your gmail, canva, google drive, work with ppt files, etc. In other words, it's now suitable for things other than programming. Before that, Claude CoWork was a few weeks earlier. So, this is all very new and fresh. I've tried some of this stuff and it mostly works as advertised.
The big picture here is that last year was about programmers discovering agentic AIs. This year, the business world is following. And there will be a lot of drama of people over doing it, making mistakes, etc. And lots of people whining about how they need to change and insisting that they shouldn't have to. Etc. But this stuff is clearly happening if you look through the noise a bit.
You are absolutely right!
Kidding, but the analogy sits comfortably with me.
I wonder though if this kind of behavior is potentially harmful, most likely less than drugs but nonetheless...
I'm trying to get out of this. I'm a blind person. No one in tech goes to bed thinking about us, as it were. So, as a non-programmer, vibe coding accessibility fixes was an outlet to the daily million papercuts of using operating systems built by people who cannot understand me.
Well, I have barely anything to show for months of this. I made Termux more accessible on Android, made an MUD client for Emacs, fixed up some Emacspeak stuff because it's been abandonned going on 3 years now, and Emacs packages wait for no one, and tried added Grade 2 Braille entry support to BRLTTY. That failed because depression sucks and who would even use this vibe coded junk anyway.
The more open nature of Android made it rather easier. How far behind in features TalkBack is compared to VoiceOver, besides AI image description, made it feel like trying to heal a broken arm with pain pills. So I'm trying to tell myself that I can't fix everything, and that it's not my fault if other people, and companies, choose to not consider accessibility. I mean I can't help Google if they choose to not be helped.
Ah well, Global Accessibility Awareness Day is this Thursday. Maybe Apple will finally announce LLM image descriptions, and hopefully my iPhone 16 will be good enough for them because I can't afford to upgrade in this economy.
This sounds like a good amount to show, given it's done while pushing through some daily million paper-cuts and the macro-cut of depression. I don't know as much about the former, but can attest the latter is non-trivial.
Do you post somewhere where I could follow what you're working on?
same author who's idea of constraint decoding for structured outputs was to run an schema-begging-API call in a loop 10 times & then throw an exception on failure.
OpenAI per employee valuation is $150M+ (almost 100x of per employee valuation of our company). I think it may make sense to ponder a bit why a $150M engineer would have such an idea. May it be it is the preferred way of doing things in the new AI world, a paradigm shift.
We all know the most highly valued people in the world are the smartest. In fact, the more money you're being paid, the more value you add, the more your opinion is worth, and the more skill you have. The amount of money you're worth is actually directly proportional to your worth as a human being
I hope I never have to work with people like this. Actual nightmare fuel to live your entire life through LLMs. "I trained Claude to love my wife so I can focus on prompting" vibes.
I worry that in the not too distant future, the vast majority of people even semi interested in CS will be too dependent on LLM's. Like Assembly is not as common a toolchain, but people using LLM's as a replacement for every abstracted level of life is not a good idea.
Give each Codex an AgentName and ask them to mark their PR/issue/comments with those. Have one or two "managers" that manage PRs and overall project direction. I write the project directions and make long lasting issues. Each Codex session has an almost unachievable `/goal` but they are asked to achieve the goal by landing changes in `main` via PRs
I am running about 14 Codex sessions on 4 machines right now for about two weeks since OpenAI 10x'ed my 20x account and I simply can not run out of tokens fast enough.
Side note: I have multiple Claude accounts too but the new Claude Code `/goal` command is seriously broken. It waits long pauses between iterations and sometimes prematurely stops.
Yes I'm aware of that. Perry is a different project. Folks at Oxi tools are also doing something similar (a ts checker) but that's also not 100% compatible with tsc. My goal with tsz is a superset of tsc that's stricter (for now it's called Sound Mode). But matching more than a decade of work that TypeScript has put in has been a long journey already. None of the existing TypeScript rewrites are matching the original tsc yet. tsgo is the closest but that also has bugs that needs to be addressed before TS 7 is released.
I think my architecture can be faster than tsgo albeit a much more painful codebase to work on. But I'm not claiming any sort of achievement yet.
Ultimately users have to decide and I have to show a very strong case that someone should use a nonofficial rewrite over Microsoft's own code.
Will tsz be a success? I am not sure. Am I learning and having fun? for sure!
Yeah I didn't mean subsuming one project into another, just that maybe both could be integrated so that a user can type check strongly and soundly with tsz and then compile with Perry. Turning TypeScript into a true sound statically typed language with AOT compilation would be amazing.
Still not useful enough for me and I really want this feature!
The problem I encounter is the inability of the LLM to look stuff up and respond to me. "What's that name of that database table?" "What are all the services that call this endpoint?" "Are there any open PRs for this repo right now?"
Once information can flow in both directions not just one it will be a gamechanger for me.
Or do you want it to speak to you too? I think this would have to be TTS on your phone. You can have ChatGPT speak to you but I don't see that feature in Codex.
Sure I speak to ChatGPT all the time and I've used the feature you've linked but it can't do the things I described. It won't be like, "hey let me go look into that" and then come back in 3 minutes with an answer. It's essentially a dictation feature.
I hear a lot of praises. Can you explain? If I can type as fast as I speak, does that still matter in such case? Does it make use of intonation or is it pure speech to text?
For me it's because I've been walking 10-20k steps per day on a walking pad at my standing desk while working.
I can still type while doing it but it's so nice to just hold a button (or double tap to lock recording) and just brain dump what I need.
I type very fast but I feel like the unaltered speech to text allows me to express more quickly any uncertainty or doubt that I have or when I don't know exactly how to best ask for what I want.
I also like to play dumb with agents and ask it for the best option for something that I already know the answer to, just to see if it's gonna be correct, it helps get a sense of the limits of each model. That's also quicker on voice.
I don't think it makes use of intonation for the built in one, I use Hex on mac for speech to text
These cloud LLMs are not the tool for you then I suppose. There are local models too, unless your point is why use LLMs, in which case, you don't need to.
> Last week I tried to migrate the Python Rich library into Rust. Because the original project already had a large unit test suite, I could set a goal like: migrate Rich into Rust, but it must pass all the unit tests from the original library.
At what point do we stop calling this development ? It's nothing even close to the process of development or engineering. "I tried to migrate X". No you didn't, you tried to ask an LLM and hoped for the best.
I mean, honestly at what point would you bother, there's no learning happening, there's no creativity happening, just talking to a literal text generator to request your refund while you go for a shower, novelty, maybe even convenient but absolutely not development.
> Every 30 minutes, check Slack and Gmail for unanswered messages that need my attention...
> When I come back to Slack, replies are often already sitting in drafts. I still decide what gets sent, but the expensive part of gathering context is done.
This just feels so dystopian to me. I hope that I never work with you or someone else doing this.
I personally do use LLMs for work messaging but I'm extremely careful to state clearly like "here's a draft for that quotation request that Claude wrote:" or something like that. I would never present that as my own words.
If the other people in the org are using LLMs to a similar degree, any question to which an LLM can provide a good answer to will never get sent. How useful are the draft replies then?
I guess the point might not be to be useful, but to pingpong responsibility back to somebody else. "There, sent a response, not it's their problem again."
But seriously: It's a game. If that kind of "productivity" is seen as a positive measure of their worth, then in this game they're rewarded for optimizing it.
And the game is simply fucked up.
And that's not new. Ye olde corpo rat race has always often revolved not around maximizing the things that are useful, but instead around maximizing the things that the boss-man perceives to be valuable.
Here in 2026, if the boss-man is himself boss-maxxing by using a bot to evaluate performance, this kind of automated charade would probably work very well. Champagne would fall from the heavens. Doors would open. Velvet ropes would part.
This game is quite clearly not sustainable and must ultimately collapse, but it's still a game with winners and losers. Historically, lots of unsustainable games have left winners standing around when the the games ultimately collapses.
(And, to be frank: It's perfectly OK to hate the game. It's also OK to hate the players and the mediators.)
An interesting piece of context with this guy is he writes about a serious hand injury that prevents him from typing much anymore. He says that adopting LLM workflows saved his hands (beyond just dictating everything).
I lost about 50% functionality in my hands in 2018-2019 and couldn't type more than an hour or so per day, what really saved me was dictation via Dragon NaturallySpeaking, and for coding I used dragonfly to create programming grammars. I'm happy for this guy for finding a solution but LLMs (in this shape) were late to the party.
Were you as fast dictating code (not just outputting it, but navigating, editing, refactoring etc.) as you were before needing it? If it was slower, then LLM assistance is significant in making such disability no longer an impairment for the job.
Once you get into it it's not any slower than typing; if anything I think you can actually be faster with a good enough grammar, and it's precise too.
The problem I had eventually was that dictating all day is itself something that wears you out, so you get hoarse and honestly a bit more tired from it when you do it too much.
But no, overall a good Dragonfly grammar should be something that keeps you at least up to par with your typing speed.
If I've researched something and it's my thoughts, it's from me. If I've Google for 30 seconds and copied over the top result, then I generally say it.
Or rather, I generally don't even send that message because I try to my messages have actual substance.
"Every 30 minutes, check Slack and Gmail for unanswered messages that need my attention.
Help me prioritize what matters most.
If someone asks me a question, research the answer as deeply as you can and draft a reply for me, but do not send it."
This is a very dangerous road to go down. You may feel like you are getting more done but end up living your life on autopilot, without any introspection or applying your own taste.
inb4 "I got prompt injected and they stole my stuff". Now real talk, there are some viable usages of codex here but nothing novel its the same "old": "MEMORY,VAULT,BG TASKS" that everyone is doing.
And about voice mode, I thought it was a good idea but I seriously don't know how you guys use it, my thoughts whenever I use voice are "aaaaaaaaahhhhhh, uhmmm" and then cancel it so that I can type and organize my thoughts. I don't really think those "brain dumps" are useful when you are thinking out loud like "We should really do X oh wait but actually Y is in the way and we have to take into consideration Z, but wait Y was actually done" and so on, and it turns out that your assumptions are wrong, it becomes a mess. I am in favor of the LLM to work with facts and always verify it. To me this post is basically selling Codex app and that's it, nothing new inside.
something is happening with `codex`, at tamarillo.ai we did a [little experiment](https://research.tamarillo.ai/coding-harness-inspection/), with 400K repos that have AI harnesses configured and very interesting behavior is observed
- growing fast as fuck
- overepresentation on starred repos (even though stars mean less these days, it is definitely something to look at)
The diff-as-review point is the one I keep coming back to.
The cost of memory-as-files isn't writing them. It's that the agent will cheerfully claim it updated something and not actually do it, or write a one-line stub that satisfies the spec but loses the original signal. Without a verification layer, the vault accumulates plausible-looking entries that quietly drift from reality.
What ended up working for me was treating the agent's self-reported summary as a wish, not a fact. A separate process diffs the actual file system against the claimed changes and flags mismatches.
After a few cycles, the agent gets calibrated and stops claiming things that don't survive a file check. That has the side benefit of making the diff review itself much higher signal: most of what shows up is real.
The split I'd make early is per-agent instructions vs. cross-thread shared notes.
They sound like the same artifact, but “what this agent should always do” and “what sibling work just learned” age very differently. Mixing them means the wisdom gets stale together.
Is this LLM psychosis? So much tending and conversing with the matmuls but what was the outcome? Are people who get this into it more successful somehow? It reminds me of people who take drugs and get "revelations" but then are not particularly over represented in the group of successful people for all of their deep insights.
> It reminds me of people who take drugs and get "revelations" but then are not particularly over represented in the group of successful people for all of their deep insights.
This depends on where you're looking for "successful" people.
I generally agree with you - of those people who might report "revelations" through hallucinogenic drugs, the majority may misinterpret their drug-induced experience and hence be more confused / lost than before.
On the other hand, it can still be true that among those who eventually do have genuine spiritual insight, having used hallucinogenic substances is overrepresented compared to the general population.
Quoting from [1], where the author tried to find spiritually advanced individuals:
> Approximately 52% of participants had used hallucinogenic drugs at some point; none reported these as the trigger that led to PNSE.
PNSE = Persistent Non-Symbolic Experience.
My point is: while there are certainly people who go way overboard with the LLM stuff, that is not at odds with skillful use of LLMs being overrepresented in successful people.
I see now that you didn't make that point, but I already typed this all out and I'm gonna leave it.
[1] https://digitalcommons.ciis.edu/cgi/viewcontent.cgi?article=...
LLMs vs psychedelics are an interesting comparison: psychedelics lower the threshold for the epiphany sensation, arguably LLMs do the same through agreement (‘sycophancy’).
With psychedelics you see the upsides in engineers who come to work the next day with designs informed by massive insights, and the downsides in people whose ‘massive insights’ result in socially abnormal behaviours.
LLMs seemingly provide validation and support, something very lacking in most lives. The distance between thinking loosely about, say, an app and getting positive feedback and absurd market predictions triggers similar ‘revelations’ in people with no meaningful context, and plays on the hopes of those who do. Much like with psychedelics, though, there is a self-supported self-validated cycle going on, prone to flights of excess.
Coming out publicly about doing drugs is just not something that smart people usually do.
There's a lot of stigma about it and a lot of opinionated people who don't know anything about them and still have a lot of judgements.
Then there are these people calling psychedelics hallucinogens. The former can give spiritual revelations and the latter gives vividly realistic, usually nightmarish, hallucinations.
There are also people putting an equal sign between crack cocaine and psylocibine mushrooms. But I don't think an addict will rob a petrol station with a screwdriver just to get another dose of magic mushrooms.
In such surroundings, it's just not a good idea to publicly say anything about drugs, unless you're so rich or known for your expertise, that you can shoulder some negative judgement and it's implications.
Psychosis would be a mental illness with symptoms like losing track of reality. I think there might actually be a bit of an anti-AI psychosis where individuals are projecting their fear and paranoia onto others and seeking confirmation bias. The need to dismiss the success others are having with AI could be triggered by personal insecurities. And of course deep paranoia is one of the classical symptoms of an actual psychosis. Just holding up a mirror here.
BTW. I have friends and relatives that have dealt with an actual psychosis. Not fun to experience up close. So, I don't want to take this metaphor too far. But if we're using big words like psychosis here, you might want to examine your motives, insecurities and reasoning a bit.
I've played with agentic AIs for coding and other use cases and have had some successes and failures. I'm fairly impressed with some stuff that is possible now and I use technology pragmatically. As I always have throughout my 30 year career.
For any new thing, there are always early adopters and those who really don't get it. And most other people let the early adopters figure things out and then end up copying what works some months/years later. And you always have some stragglers that can't or won't adapt that can't be helped.
Most of what this person describes in the article is very reasonable. Codex might not be the best model. But in terms of UX, OpenAI is getting a few things right that starting to make a difference. It's only a few months ago that their desktop app launched. It has gone through a pretty rapid evolution. As of a few weeks ago (it's that recent) you can install skills to connect your gmail, canva, google drive, work with ppt files, etc. In other words, it's now suitable for things other than programming. Before that, Claude CoWork was a few weeks earlier. So, this is all very new and fresh. I've tried some of this stuff and it mostly works as advertised.
The big picture here is that last year was about programmers discovering agentic AIs. This year, the business world is following. And there will be a lot of drama of people over doing it, making mistakes, etc. And lots of people whining about how they need to change and insisting that they shouldn't have to. Etc. But this stuff is clearly happening if you look through the noise a bit.
That last part is also true without the drugs. Forbidden knowledge does not make one popular at parties.
You are absolutely right! Kidding, but the analogy sits comfortably with me. I wonder though if this kind of behavior is potentially harmful, most likely less than drugs but nonetheless...
triggered me with that first sentence
Calling something emergent a matmul is like calling a human an axon discharge.
More like money psychosis. If enough people buy into this vision, he gets to be a billionaire.
I'm trying to get out of this. I'm a blind person. No one in tech goes to bed thinking about us, as it were. So, as a non-programmer, vibe coding accessibility fixes was an outlet to the daily million papercuts of using operating systems built by people who cannot understand me.
Well, I have barely anything to show for months of this. I made Termux more accessible on Android, made an MUD client for Emacs, fixed up some Emacspeak stuff because it's been abandonned going on 3 years now, and Emacs packages wait for no one, and tried added Grade 2 Braille entry support to BRLTTY. That failed because depression sucks and who would even use this vibe coded junk anyway.
The more open nature of Android made it rather easier. How far behind in features TalkBack is compared to VoiceOver, besides AI image description, made it feel like trying to heal a broken arm with pain pills. So I'm trying to tell myself that I can't fix everything, and that it's not my fault if other people, and companies, choose to not consider accessibility. I mean I can't help Google if they choose to not be helped.
Ah well, Global Accessibility Awareness Day is this Thursday. Maybe Apple will finally announce LLM image descriptions, and hopefully my iPhone 16 will be good enough for them because I can't afford to upgrade in this economy.
This sounds like a good amount to show, given it's done while pushing through some daily million paper-cuts and the macro-cut of depression. I don't know as much about the former, but can attest the latter is non-trivial.
Do you post somewhere where I could follow what you're working on?
Sounds like you're contributing to the solution.
How does a blind person read and write code? Serious question. I’m imagining braille screens (is that a thing?)
You might be interested to learn exactly how fast some listen to screen readers, and how many overlapping sounds can be successfully navigated
screen readers
The author of this post works at OpenAI on the Codex team.
same author who's idea of constraint decoding for structured outputs was to run an schema-begging-API call in a loop 10 times & then throw an exception on failure.
this is so funny because it's true. it was a handy library but a lot of the shine wore off when I realize how it actually worked.
source?
https://github.com/567-labs/instructor/blob/main/instructor/...
[dead]
OpenAI per employee valuation is $150M+ (almost 100x of per employee valuation of our company). I think it may make sense to ponder a bit why a $150M engineer would have such an idea. May it be it is the preferred way of doing things in the new AI world, a paradigm shift.
Madoff had good numbers too.
We all know the most highly valued people in the world are the smartest. In fact, the more money you're being paid, the more value you add, the more your opinion is worth, and the more skill you have. The amount of money you're worth is actually directly proportional to your worth as a human being
(/s)
Reminds me of this dialogue between a money manager and MIT economist Paul Cootner:
- "If you’re so smart, why aren’t you rich?"
- "If you’re so rich, why aren’t you smart?"
[flagged]
All the AI stuff lately is just like Unix Porn reddit but posted to places where the people don’t care about it.
Hacker News is the /r/unixporn equivalent for AI. Ground zero. They all are here.
The further away you go, the more sensible takes you find.
It's LinkedIn. HN is just for the cosplayers.
I feel that we're about ready for someone to start something like Uber, but for file-like objects
"Rsync as a service with surge pricing" now where do I sign my series A?
Anything with “maxxing” in the name is most likely not good for you
I came to understand it as "optimizing well past the point of diminishing returns".
I've understood it as obsessive optimization to the point that it's a mental health problem. Case in point, looksmaxxing.
Ever since it's breached the mainstream, I think you can just append it to anything to make things sound funnier. It has mostly lost its meaning.
"I'm breakfastmaxxing. I'm a cerealpilled bowlcel in my milk era. I'm a slicemoded breadchad." etc.
"cerealpilled bowlcel" send me to another dimension.
*-maxxing is the new make-*-great-again.
SNL Weekend Update: Chad Maxxington on the Art of Looksmaxxing:
https://www.youtube.com/watch?v=4XMPLdiXB1k
I hope I never have to work with people like this. Actual nightmare fuel to live your entire life through LLMs. "I trained Claude to love my wife so I can focus on prompting" vibes.
I worry that in the not too distant future, the vast majority of people even semi interested in CS will be too dependent on LLM's. Like Assembly is not as common a toolchain, but people using LLM's as a replacement for every abstracted level of life is not a good idea.
> Thariq has a very good post about preferring HTML over Markdown as an output format. I think that instinct is right
I bet you do, working at OpenAI you get paid for more token use.
in tsz (https://tsz.dev) I am Codex-Maxxing with this:
Give each Codex an AgentName and ask them to mark their PR/issue/comments with those. Have one or two "managers" that manage PRs and overall project direction. I write the project directions and make long lasting issues. Each Codex session has an almost unachievable `/goal` but they are asked to achieve the goal by landing changes in `main` via PRs
I am running about 14 Codex sessions on 4 machines right now for about two weeks since OpenAI 10x'ed my 20x account and I simply can not run out of tokens fast enough.
Side note: I have multiple Claude accounts too but the new Claude Code `/goal` command is seriously broken. It waits long pauses between iterations and sometimes prematurely stops.
Do you know about Perry, a TypeScript to native binary compiler also in Rust? That might be interesting to collaborate on.
https://old.reddit.com/r/typescript/comments/1rjxo8z/what_if...
https://perryts.com/
Yes I'm aware of that. Perry is a different project. Folks at Oxi tools are also doing something similar (a ts checker) but that's also not 100% compatible with tsc. My goal with tsz is a superset of tsc that's stricter (for now it's called Sound Mode). But matching more than a decade of work that TypeScript has put in has been a long journey already. None of the existing TypeScript rewrites are matching the original tsc yet. tsgo is the closest but that also has bugs that needs to be addressed before TS 7 is released.
I think my architecture can be faster than tsgo albeit a much more painful codebase to work on. But I'm not claiming any sort of achievement yet.
Ultimately users have to decide and I have to show a very strong case that someone should use a nonofficial rewrite over Microsoft's own code.
Will tsz be a success? I am not sure. Am I learning and having fun? for sure!
Yeah I didn't mean subsuming one project into another, just that maybe both could be integrated so that a user can type check strongly and soundly with tsz and then compile with Perry. Turning TypeScript into a true sound statically typed language with AOT compilation would be amazing.
I haven't run into /goal pausing or prematurely stopping, though I haven't used it more than a handful of times.
Codex lags when chats become too long. Barely takes a day before loading certain chats freezes the UI and causes all sorts of issues
Hey they added heartbeats? Wasn't that the killer feature OpenClaw had? I haven't used it in a while, but imagine they'd be pretty similar now.
Main difference would be just in how they're used (general purpose assistant vs "coding assistant") but the actual capabilities seem to be identical.
Most people I know underutilize voice mode. Such a game changer for making brain dumps the LLM can just gobble up
Still not useful enough for me and I really want this feature!
The problem I encounter is the inability of the LLM to look stuff up and respond to me. "What's that name of that database table?" "What are all the services that call this endpoint?" "Are there any open PRs for this repo right now?"
Once information can flow in both directions not just one it will be a gamechanger for me.
This works today right? What part of this are you missing?
Not as far as I know. Can you walk me through the process?
I have my phone, I'm going for a walk, what app am I opening?
For Codex, that is ChatGPT? https://openai.com/index/work-with-codex-from-anywhere/
Or do you want it to speak to you too? I think this would have to be TTS on your phone. You can have ChatGPT speak to you but I don't see that feature in Codex.
Sure I speak to ChatGPT all the time and I've used the feature you've linked but it can't do the things I described. It won't be like, "hey let me go look into that" and then come back in 3 minutes with an answer. It's essentially a dictation feature.
I am lost. Codex can't look up stuff for you in your codebase? GitHub Copilot can't look up PRs for you?
I hear a lot of praises. Can you explain? If I can type as fast as I speak, does that still matter in such case? Does it make use of intonation or is it pure speech to text?
For me it's because I've been walking 10-20k steps per day on a walking pad at my standing desk while working.
I can still type while doing it but it's so nice to just hold a button (or double tap to lock recording) and just brain dump what I need.
I type very fast but I feel like the unaltered speech to text allows me to express more quickly any uncertainty or doubt that I have or when I don't know exactly how to best ask for what I want.
I also like to play dumb with agents and ask it for the best option for something that I already know the answer to, just to see if it's gonna be correct, it helps get a sense of the limits of each model. That's also quicker on voice.
I don't think it makes use of intonation for the built in one, I use Hex on mac for speech to text
By this pretty cool dude -> https://github.com/kitlangton/Hex
Why would I want OpenAI to gobble up my brain dumps?
These cloud LLMs are not the tool for you then I suppose. There are local models too, unless your point is why use LLMs, in which case, you don't need to.
No I do use them, for specific, targetted jobs, with 'well' defined specs.
I don’t like that they don’t have realtime output. Would prefer Parakeet for that.
> When I come back to Slack, replies are often already sitting in drafts.
He must be a pleasure to work with
> Last week I tried to migrate the Python Rich library into Rust. Because the original project already had a large unit test suite, I could set a goal like: migrate Rich into Rust, but it must pass all the unit tests from the original library.
At what point do we stop calling this development ? It's nothing even close to the process of development or engineering. "I tried to migrate X". No you didn't, you tried to ask an LLM and hoped for the best.
I mean, honestly at what point would you bother, there's no learning happening, there's no creativity happening, just talking to a literal text generator to request your refund while you go for a shower, novelty, maybe even convenient but absolutely not development.
> Every 30 minutes, check Slack and Gmail for unanswered messages that need my attention...
> When I come back to Slack, replies are often already sitting in drafts. I still decide what gets sent, but the expensive part of gathering context is done.
This just feels so dystopian to me. I hope that I never work with you or someone else doing this.
I personally do use LLMs for work messaging but I'm extremely careful to state clearly like "here's a draft for that quotation request that Claude wrote:" or something like that. I would never present that as my own words.
If the other people in the org are using LLMs to a similar degree, any question to which an LLM can provide a good answer to will never get sent. How useful are the draft replies then?
I guess the point might not be to be useful, but to pingpong responsibility back to somebody else. "There, sent a response, not it's their problem again."
You pretend that you did the work. It is not about achieving the result, it is about appearing productive.
^^^ this guy productivity-maxxes
But seriously: It's a game. If that kind of "productivity" is seen as a positive measure of their worth, then in this game they're rewarded for optimizing it.
And the game is simply fucked up.
And that's not new. Ye olde corpo rat race has always often revolved not around maximizing the things that are useful, but instead around maximizing the things that the boss-man perceives to be valuable.
Here in 2026, if the boss-man is himself boss-maxxing by using a bot to evaluate performance, this kind of automated charade would probably work very well. Champagne would fall from the heavens. Doors would open. Velvet ropes would part.
This game is quite clearly not sustainable and must ultimately collapse, but it's still a game with winners and losers. Historically, lots of unsustainable games have left winners standing around when the the games ultimately collapses.
(And, to be frank: It's perfectly OK to hate the game. It's also OK to hate the players and the mediators.)
An interesting piece of context with this guy is he writes about a serious hand injury that prevents him from typing much anymore. He says that adopting LLM workflows saved his hands (beyond just dictating everything).
I lost about 50% functionality in my hands in 2018-2019 and couldn't type more than an hour or so per day, what really saved me was dictation via Dragon NaturallySpeaking, and for coding I used dragonfly to create programming grammars. I'm happy for this guy for finding a solution but LLMs (in this shape) were late to the party.
Were you as fast dictating code (not just outputting it, but navigating, editing, refactoring etc.) as you were before needing it? If it was slower, then LLM assistance is significant in making such disability no longer an impairment for the job.
Once you get into it it's not any slower than typing; if anything I think you can actually be faster with a good enough grammar, and it's precise too.
The problem I had eventually was that dictating all day is itself something that wears you out, so you get hoarse and honestly a bit more tired from it when you do it too much.
But no, overall a good Dragonfly grammar should be something that keeps you at least up to par with your typing speed.
Sounds more like CYA.
If instead of LLM you googled do you also say "Here are the CPU architectures pytorch supports, that Google search returned"
You've never said "I found this on Google"?
I mean, up to a point, yes.
If I've researched something and it's my thoughts, it's from me. If I've Google for 30 seconds and copied over the top result, then I generally say it.
Or rather, I generally don't even send that message because I try to my messages have actual substance.
"Every 30 minutes, check Slack and Gmail for unanswered messages that need my attention.
Help me prioritize what matters most.
If someone asks me a question, research the answer as deeply as you can and draft a reply for me, but do not send it."
This is a very dangerous road to go down. You may feel like you are getting more done but end up living your life on autopilot, without any introspection or applying your own taste.
inb4 "I got prompt injected and they stole my stuff". Now real talk, there are some viable usages of codex here but nothing novel its the same "old": "MEMORY,VAULT,BG TASKS" that everyone is doing.
And about voice mode, I thought it was a good idea but I seriously don't know how you guys use it, my thoughts whenever I use voice are "aaaaaaaaahhhhhh, uhmmm" and then cancel it so that I can type and organize my thoughts. I don't really think those "brain dumps" are useful when you are thinking out loud like "We should really do X oh wait but actually Y is in the way and we have to take into consideration Z, but wait Y was actually done" and so on, and it turns out that your assumptions are wrong, it becomes a mess. I am in favor of the LLM to work with facts and always verify it. To me this post is basically selling Codex app and that's it, nothing new inside.
something is happening with `codex`, at tamarillo.ai we did a [little experiment](https://research.tamarillo.ai/coding-harness-inspection/), with 400K repos that have AI harnesses configured and very interesting behavior is observed
- growing fast as fuck
- overepresentation on starred repos (even though stars mean less these days, it is definitely something to look at)
- overepresentation in `rust`
- in terms of aliveness, codex is first
lol why is this on the front page of hacker news?
Slop
[flagged]
[flagged]
The diff-as-review point is the one I keep coming back to.
The cost of memory-as-files isn't writing them. It's that the agent will cheerfully claim it updated something and not actually do it, or write a one-line stub that satisfies the spec but loses the original signal. Without a verification layer, the vault accumulates plausible-looking entries that quietly drift from reality.
What ended up working for me was treating the agent's self-reported summary as a wish, not a fact. A separate process diffs the actual file system against the claimed changes and flags mismatches.
After a few cycles, the agent gets calibrated and stops claiming things that don't survive a file check. That has the side benefit of making the diff review itself much higher signal: most of what shows up is real.
The split I'd make early is per-agent instructions vs. cross-thread shared notes.
They sound like the same artifact, but “what this agent should always do” and “what sibling work just learned” age very differently. Mixing them means the wisdom gets stale together.