I was a Plus subscriber and upgraded to Pro just to test Codex, and at least in my experience, it’s been pretty underwhelming.
First, I don’t think they got the UX quite right yet. Having to wait for an undefined amount of time before getting a result is definitely not the best, although the async nature of Codex seems to alleviate this issue (that is, being able to run multiple tasks at once).
Another thing that bugs me is having to define an environment for the tool to be useful. This is very problematic because AFAIK, you can’t spin up containers that might be needed in tests, severely limiting its usefulness. I guess this will eventually change, but the fact that it’s also completely isolated from the internet seems limiting, as one of the reasons o3 is so powerful in ChatGPT is because it can autonomously research using the web to find updated information on whatever you need.
For comparison, I also use Claude a lot, and I’ve found it to work really well to find obscure bugs in a somewhat complex React application by creating a project and adding the GitHub repo as a source. What this allows me is to have a very short wait time, and the difference with Codex is just night and day. Gemini also allows you to do this now, and it works very well because of its massive context window.
All that being said, I do understand where OpenAI is going with this. I guess they want to achieve something like a real coworker (they even say that in their promotional videos for Codex) because you are supposed to give tasks to Codex and wait until it’s done, like a real human, but again, IMHO, it’s too “pull-request-focused”
I guess I’ll be downgrading to Plus again and wait a little to see where this ends up.
anxman · 2h ago
It really needs container support
avital · 6h ago
I work at OpenAI (not on Codex) and have used it successfully for multiple projects so far. Here's my flow:
- Always run more than one rollout of the same prompt -- they will turn out different
- Look through the parallel implementations, see which is best (even if it's not good enough), then figure out what changes to your prompt would have helped nudge towards the better solution.
- In addition, add new modifications to the prompt to resolve the parts that the model didn't do correctly.
- Repeat loop until the code is good enough.
If you do this and also split your work into smaller parallelizable chunks, you can find yourself spending a few hours only looping between prompt tuning and code review with massive projects implemented in a short period of time.
I've used this for "API munging" but also pretty deep Triton kernel code and it's been massive.
csmpltn · 4h ago
> "Look through the parallel implementations, see which is best (even if it's not good enough), then figure out what changes to your prompt would have helped nudge towards the better solution."
How can non-technical people tell what's "best"? You need to know what you're doing at this point, look for the right pitfalls, inspect everything in detail... this right here is the entire counter-argument for LLMs eliminating SWE jobs...
diggan · 38m ago
> How can non-technical people tell what's "best"? You need to know what you're doing at this point, look for the right pitfalls, inspect everything in detail... this right here is the entire counter-argument for LLMs eliminating SWE jobs...
I'm not sure a tool that positions itself as a "programmer co-worker" is aiming to be useful to non-technical people. I've said it before, but I don't think LLMs currently are at the stage where they enable you to do things you have 0 experience in, but rather can help you speed up working through things you are familiar with. I think people who claim LLMs will completely replace jobs are hyping the technology without really understanding it.
For example, I'm a programmer, but never done any firmware flashing with UART before via a USB flasher. Today I managed to do that in 1-2 hours thanks to ChatGPT helping me out understanding how to do it. If I'd do it completely on my own, I'm sure it would have taken me at least the full day to do so, instead of the time it took. I was able to see when it got mislead, and could rewrite/redirect from there on, but someone with 0 programming experience, probably wouldn't have been able to.
throwuxiytayq · 4h ago
I don’t think anyone expects software engineers will disappear and get replaced by janitors trained to proompt. I’m sure experts will stick around until the singularity curve starts looking funny. It’s probably gonna suck to enter the industry from now on, though.
jazzyjackson · 18m ago
Well, right, how does one become a senior engineer in a world where no one needs to hire a junior? I'm sure many other industries have experiences this already, where the only people who know anything retire and the people are left maintaining a system they could not rebuild such that when something goes wrong the only practicable choice is to replace it with new equipment.
That's where I see AI-written software going, write-once. Some talented engineer gets an AI system to create a whole k8s cluster to run an application and if any changes need to be made, bugs fixed, it will take another talented engineer to come in and have an AI write a replacement and throw out the old one.
Reminds me of this blog, The real value isn’t in the code [0], we're heading for a world that is only code and no one who knows what it does. But maybe it won't matter.
and on and on, endless thinkpieces about this. Certainly SOMEONE, someone with a lot of money, thinks software engineers are imminently replaceable.
> until the singularity curve starts looking funny.
well there's absolutely no evidence whatsoever that we've made any progress to bringing about Kurzweil's God so I think regardless of what Sam Altman wants you to believe about "general AI" or those thinkpieces, experts are probably okay.
cdolan · 3h ago
I think you are correct that people say this, but its absurd that they are saying it in the first place.
Coding/engineering/etc is all problem solving in a strucutred manner.
That skill is not going anywhere
dingnuts · 3h ago
oh I agree but the last three years has felt like an endless chorus of people telling me SWE was going to be obsolete very soon so I had to push back against the idea that "nobody" thinks that.
I wouldn't have to listen to people talk about it all the time if nobody thought it was true
daveguy · 1h ago
(not GP) To be fair, just because someone says something doesn't mean they believe it. Most of those folks have to know they're being absurd. But I agree saying "nobody" thinks something is over the top. People on the internet can be quite looney tunes.
ivraatiems · 4h ago
How much faster is this than simply writing the code yourself?
thearn4 · 4h ago
I end up asking the same question when experimenting with tools like Cursor. When it can one-shot a small feature, it works like magic. When it struggles, and the context gets poisoned and I have to roll back commits and retry part of the way through something, it hits a point where it was probably easier for me to just write it. Or maybe template it and have it finish it. Or vice versa. I guess the point being that best practices have yet to truly be established, but totally hands-off uses have not worked well for me so far.
sunnybeetroot · 3h ago
Why commit halfway through implementing something with Cursor? Can you not wait until it’s created a feature or task that has been validated and tests written for it?
daveguy · 1h ago
Why not create a branch and rollback only what needs to be rolled back? Branches are O(1) with git, right?
sunnybeetroot · 1h ago
OP was insinuating that rolling back commits is a pain point.
avital · 4h ago
Easily 5-10x or even more in certain special cases (when it'd take me a lot of upfront effort to get context on some problem domain). And it can do all the "P2"s that I'd realistically never get to. There was a day where I landed 7 small-to-medium-size pull requests before lunch.
There are also cases where it fails to do what I wanted, and then I just stop trying after a few iterations. But I've learned what to expect it to do well in and I am mostly calibrated now.
The biggest difference is that I can have agents working on 3-4 parallel tasks at any given point.
No comments yet
dgunay · 3h ago
At the current capabilities of most LLMs + my personal tolerance for slop, the most productive workflow seems to be: spin up multiple agents in the background to work on small scope, straightforward tasks while I work on something bigger that requires more exploration, requirements gathering, or just plain more complex/broad changes to the code. Review the output of the agents or unstick them when there is downtime.
IMO just keeping an IDE window open and babysitting an agent while it works is less productive than just writing the code mostly yourself with AI assistance in the form of autocomplete and maybe highly targeted oneshots using manual context provided "Edit" mode or inline prompting.
My company is dragging their feet on AI governance and let the OpenAI key I was using expire, and what I noticed was that my output of small QoL PRs and bugfixes dropped drastically because my attention remains focused on higher impact work.
th0ma5 · 4h ago
Do you find yourself ditching on the things when they change something important with the new prompt? I don't get how people aren't absolutely exhausted by actually implementing this prompt messing advice when I thought there were studies saying small seemingly insignificant changes greatly change the result, hide blind spots, and even having a prompt for engineering a better prompt has knock on increases in instability. Do people just have a higher tolerance for doing work that is not related to the problem than I do? Perhaps I only work on stuff there is no prior example for, but every few days I read someone's anecdote on here and get discouraged in all new ways.
avital · 4h ago
Not to downplay the issue you raise but I haven't noticed this.
Every iteration I make on the prompts only make the request more specified and narrow and it's always gotten me closer to my desired goal for the PR. (But I do just ditch the worse attempts at each iteration cycle)
Is it possible that reasoning models combined with the actual interaction with the real codebase makes this "prompt fragility" issue you speak of less common?
th0ma5 · 2h ago
No, I've played with all the reasoning models and they just make the noise and weirdness even worse. When I dig into every little issue, it's always something incredibly bespoke. Like the actual documentation that's on the internet is out of date for the library that was installed and the API changed, the way the one library works in one language is not how it works in the other language, just all manner of surprising things. I really learned a lot about the limits of digital representation of information.
yieldcrv · 1h ago
how much would this cost you if you didn't work at OpenAI?
avital · 1h ago
I think the Pro plan is $200/mo for everyone? (But honestly I don't know the GPU cost and I'm interested in this question)
ionwake · 5h ago
You guys are doing great work, codex too, keep at it.
owebmaster · 5h ago
Can it be used to fix bugs? Because the ChatGPT web app is full of them and I don't think they are getting fixed. Pasting big amounts of text freezing the tab is one of them.
dimal · 4h ago
Bugs? Those are grubby human work.
Seriously, everyone should get good at fixing bugs. LLMs are terrible at it when it’s slightly non-obvious and since everyone is focusing on vibe coding, I doubt they’ll get any better.
jampekka · 1h ago
The Android app is even worse.
teekert · 3h ago
“As I wrote about in Walking and talking with AI in the woods, ideally I'd like to start my morning in an office, launch a bunch of tasks, get some planning out of the way, and then step out for a long walk in nature.”
Wouldn’t we all want that, but it sounds like you can leave task launching and planning to an AI and go find another career.
- it's a GREAT oneshot coding model (in the pod we find out that they specifically finetuned for oneshotting OAI SWE tasks, eg prioritized over being multiturn)
- however comparatively let down by poorer integrations (eg no built in browser, not great github integration - as TFA notes "The current workflow wants to open a fresh pull request for every iteration, which means pushing follow-up commits to an existing branch is awkward at best." - yeah this sucks ass)
fortunately the integrations will only improve over time. i think the finding that you can do 60 concurrent Codex instances per hour is qualitatively different than Devin (5 concurrent) and Cursor (1 before the new "background agents").
btw
> I haven't yet noticed a marked difference in the performance of the Codex model, which OpenAI explains is a descendant of GPT-3 and is proficient in more than 12 programming languages.
incorrect, its an o3 finetune.
andrewmunsell · 5h ago
> incorrect, its an o3 finetune.
This is Open AI's fault (and literally every AI company is guilty of the same horrid naming schemes). Codex was an old model based on GPT-3, but then they reused the same name for both their Codex CLI and this Codex tool...
I mean, just look at the updates to their own blog post, I can see why people are confused.
Google just did it too. "Gemini Ultra" is both a model (https://deepmind.google/models/gemini/ultra/) and their new top-tier subscription plan (a la Open AI's Pro plan). Why is this so difficult?
number6 · 3h ago
They should use one of their LLMs to get some better naming schemes - seriously LLMs are pretty good at this set of task
liuliu · 6h ago
The particularly integration pain point to me is about network access, that prohibits several banal tasks to be offloaded to codex:
1. Cannot git fetch and sync with upstream, fixing any integration bugs;
2. Cannot pull in new library as dependency and do integration evaluations.
Besides that, cannot apt install in the setup script is annoying (they blocked the domain to prevent apt install I believe).
The agent itself is a bit meh, often opt-to git grep rather than reading all the source code to get contextual understanding (from what the UI has shown).
canadiantim · 7h ago
How do you find it compares to Claude Code?
viscanti · 6h ago
It's much more conservative in the scope of task it will attempt and it's much slower. You need to fire and forget several parallel tasks because you'll be waiting 10+ minutes before you get anything you can review and give feedback on.
swyx · 6h ago
right now apples and oranges literally only because 1) unlimited unmetered use and 2) not in browser so async and parallel. like that stuff just trumps actual model and agent harness differences because it removes all barriers from thought to code.
theowijrhrjrj48 · 25m ago
Sounds like a gptel-tool one can whip up in a week.
maxwellg · 7h ago
Being able to make quick changes across a ton of repos sounds awesome. I help maintain a ton of example apps, and doing things like updating a README to conform to a new format, or changing a link, gets pretty tedious when there are 20 different places to do it. If I could delegate all that busywork to Codex and smash the merge button later I would be happy.
zackproser · 7h ago
Me too :)
I feel it will get there in short order..but for the time being I feel that we'll be doing some combination of scattershot smaller & maintenance tasks across Codex while continuing to build and do serious refactoring in an IDE...
atonse · 7h ago
I'm actually curious about using this sort of tool to allow non-devs to make changes to our code.
There are so many content changes or small CSS fixes (anyway you would verify that it was fixed by looking at it visually) where I really don't want to be bothered being involved in the writing of it, but I'm happy to do a code review.
Letting a non-dev see the ticket, start off a coding thing, test if it was fixed, and then just say "yea this looks good" and then I look at the code, seems like good workflow for most of the minor bugs/enhancements in our backlog.
MangoCoffee · 5h ago
A.I. Assist is probably the ultimate low-code platform. Will it be long before software engineers are replaced?
SketchySeaBeast · 1h ago
Assuming you works as a software engineer, is your day actually just filled with writing what could be solved by a low-code platform? Mine certainly isn't.
SketchySeaBeast · 6h ago
Even content changes can require deliberate thought. Any system of decent size is probably going to have upstream/downstream dependencies - adding a field might require other systems to account for it. I guess I can see small CSS changes, but how does the user know when the change is small or "small"?
rgbrgb · 6h ago
Perhaps the system could tell them 80% of the time and the reviewer catches the other 20%. An easy heuristic that usually would work in this case is lines of code. It's a classically bad way to measure impact / productivity but it's definitely an indicator and this is probably a rare instance where the measurement would not break efficacy of the metric (Goodhart's law) and might actually improve the situation.
SketchySeaBeast · 6h ago
But that's what I mean, when things look small, and are easy to change in the place that it's being asked to be changed, but hidden under the iceberg is a bunch of requirements around that field, things like data stores, or generated pdfs, whether or not that field needs to be added to other calls that aren't in this code base.
rgbrgb · 5h ago
yep, reviewers definitely need to be knowledgable about the codebase.
SketchySeaBeast · 4h ago
So now you get to manage the business user's expectations. That feedback loop is gonna be fun when they flood the reviewers with requests.
ChadMoran · 6h ago
People will learn about accessibility, multi-platform (mobile/desktop) and many other gotchas real quick.
This almost seems like this is a funnel to force people to become software engineers.
atonse · 6h ago
But these are all things that can be added to context by a dev.
Like:
- When making CSS changes, make sure that the code is responsive. Add WCAG 2.0 attributes to any HTML markup.
- When making changes, run <some accessibility linter command> to verify that the changes are valid.
etc.
The non-dev doesn't need to know/care.
lelandfe · 6h ago
There is no robust accessibility linter tool (axe covers only a portion) and you don't want to add ARIA attributes to all HTML markup. Both "accessible" and "responsive" are ultimately subjective, and all code gen tools I've used are more than happy to introduce startling a11y regressions.
It'll probably get there eventually, but today these are not things solvable with context.
dwb · 5h ago
Accessibility isn’t something that can be judged by a program, not even close.
datadrivenangel · 7h ago
40-60% success rate for smaller things is pretty good. Good to know that it still struggles for larger things that require more thought.
CSMastermind · 5h ago
In my testing with it anything that requires a bit of critical thought gets completely lost. It's about on par with a bad junior engineer at this point.
For instance I ask it to make a change and as part of the output it makes a bunch of value on the class nullable to get rid of compiler warnings.
This technically "works" in the sense that it made the change I asked for and the code compiles but it's clearly incorrect in the sense that we've lost data integrity. And there's a bunch of other examples like that I could give.
If you just let it run loose on a codebase without close supervision you'll devolve into a mess of technical debt pretty quickly.
mnahkies · 3h ago
I asked it (the codex cli from GitHub, so guess the codex-mini model) to implement some changes to a SQL parser, and solve typescript build errors/test failures. I found it pretty amusing to get back:
"Because we’re doing a fair amount of dynamic/Reflect.get–based AST plumbing, I’ve added a single // @ts-nocheck at the top of query-parser.ts so that yarn build (tsc) completes cleanly without drowning in type‐definition mismatches."
Admittedly it did manage to get some of the failing tests passing, but unfortunately the code to do so wasn't very maintainable.
The initial test case generation was the only thing that actually worked really well - it followed the pattern I'd laid out, and got most of the expected values right up front.
bathtub365 · 2h ago
Is there anywhere that lists what languages this supports? They aren’t listed in the product announcement or in this review, and the review examples seem to mostly be fixing typos on webpages.
micromacrofoot · 6h ago
> Codex will support me and others in performing our work effectively away from our desks.
This feels so hopelessly optimistic to me, because "effectively away from our desks" for most people will mean "in the unemployment line"
AstroBen · 3h ago
It's mind blowing to me how many developers are happy about the developments here.. as if they're going to eventually be paid to just sit there while agents do everything. Ah, work is now so easy!
sokoloff · 2h ago
I think in the success case (still TBD), that it will increase productivity to the point where things that can’t be affordably addressed by software will now be able to be addressed with software.
I expect that anyone who is a skilled dev today will be fine. Expectations and competition might be higher, but so will production and value creation.
I think the demand will come, just as Excel didn’t put finance people out of jobs in aggregate.
micromacrofoot · 38m ago
when in history have workers ever been the primary benefactors of productivity gains
sokoloff · 20m ago
Why would "primary benefactor" be the most relevant question rather than mere "benefactor"? If my life is improved by something, I don't care that someone else's life is improved by more; I don't want to reject that improvement out of spite, jealousy, or envy.
Bankers (and customers) benefited from ATMs as far more bank locations became economically sustainable and bank tellers could do higher value work (and do so more safely).
Millions of software developers continue to benefit from improvements in productivity, the resulting value creation, and the resulting high pay in our sector from ever more productive languages and frameworks. Can you imagine how little pay you'd make trying to sling websites in assembly language at less than 1% of the pace of today?
palmotea · 1h ago
> It's mind blowing to me how many developers are happy about the developments here.. as if they're going to eventually be paid to just sit there while agents do everything. Ah, work is now so easy!
Software engineers are dumb. Really dumb.
bilbo0s · 3h ago
I mean, I get what everyone's saying. But, just Devil's Advocate, what would be so terrible about software developers having to find some other line of work?
We've used our software development skills to automate other people out of work for what can be argued to be literally decades. Each time we did it, we certainly expected that the people affected would find other work. New jobs were created. The world didn't end. I honestly don't think it would be that much worse this time.
palmotea · 1h ago
> We've used our software development skills to automate other people out of work for what can be argued to be literally decades.
And that's the shitty part of the job, and everyone should be uncomfortable with it. I haven't literally automated anyone out of a job (that I know), but I definitely did not like finding out (after the fact) that one project was meant to enable a large offshoring effort.
> Each time we did it, we certainly expected that the people affected would find other work.
I do not expect that. That's a comforting lie people tell themselves.
> New jobs were created. The world didn't end. I honestly don't think it would be that much worse this time.
It didn't end, but it often got significantly worse for some. If the AI hype pans out, it's going to get significantly worse for software engineers. Your "newly created job," if it exists, will likely pay out a lot less that you're used to. At best, you'll get knocked down to the bottom of the career ladder.
It's a mistake to think about things in aggregate like you're doing. It's easy to hide inconvenient truths.
AstroBen · 2h ago
> what would be so terrible about software developers having to find some other line of work
Uh.. I'm having trouble considering this as a serious question. It's objectively going to lead to them being in a worse situation. Mostly irrelevant resume and needing to re-skill into something and start from the bottom.. out of a well paid career that many enjoy and find fulfilling
My question wasn't an ethical one. It's why are the people that are the target of this automation happy about the progress, to the point of trying to push it forward faster, cheering it on
jampekka · 1h ago
I agree that with the current economic structures a lot of us will end up worse off. Just like e.g. manufacturing workers did.
But the automation is not the problem, it's the economic structure in which increased efficiency makes a lot of people worse off.
AstroBen · 1h ago
Yeah you're right. Improving productivity for society should be a really exciting time for everyone.. instead we just leave the affected with nothing
darth_avocado · 5h ago
It is most definitely going to be the unemployment line. When in the history of productivity gains, has it translated to more time for people to do other things that are not work? It always translates to more profits for shareholders and bigger pay for executive class, followed by more work for half the workers to fill up the time opened up by the said productivity gains, and unemployment for the other half.
sokoloff · 1h ago
200 years ago, 80% of Americans worked in farming. 150 years ago, that was still over half. It’s now under 2%.
If you’ve seen the work hours and work ethic of farmers, it’s safe to say that most of those people got other jobs that take far less work than farmers did/do.
Closer to our field, I think we’d have far worse work lives (fewer of us employed and much lower pay) if we had to code everything in assembler still. The creation of more powerful abstractions and languages allowed more of us to become software devs and make a living this way than if all we had were the less productive tools of the early days of computing.
jampekka · 1h ago
From 200 years ago sure, but the link between productivity growth and income growth got more or less broken in the 1970's.
Think we've got a long time yet for that. We're going to be writing code a lot faster but getting these things to 90-95% on such a wide variety of tasks is going to be a monumental effort, the first 60-70% on anything is always much easier than the last 5-10%.
Also there's a matter of taste, as commented above, the best way to use these is going to be running multiple runs at once (that's going to be super expensive right now so we'll need inference improvements on today's SOTA models to make this something we can reasonably do on every task). Then somebody needs to pick which run made the best code, and even then you're going to want code review probably from a human if it's written by machine.
Trusting the machine and just vibe coding stuff is fine for small projects or maybe even smaller features, but for a codebase that's going to be around for a while I expect we're going to want a lot of human involvement in the architecture. AI can help us explore different paths faster, but humans need to be driving it still for quite some time - whether that's by encoding their taste into other models or by manually reviewing stuff, either way it's going to take maintenance work.
In the near-term, I expect engineering teams to start looking for how to leverage background agents more. New engineering flows need to be built around these and I am bearish on the current status quo of just outsource everything to the beefiest models and hope they can one-shot it. Reviewing a bunch of AI code is also terrible and we have to find a better way of doing that.
I expect since we're going to be stuck on figuring out background agents for a while that teams will start to get in the weeds and view these agents as critical infra that needs to be designed and maintained in-house. For most companies, foundation labs will just be an API call, not hosting the agents themselves. There's a lot that can be done with agents that hasn't been explored much at all yet, we're still super early here and that's going to be where a lot of new engineering infra work comes from in the next 3-5 years.
fhd2 · 5h ago
Well, the optimistic take is that if something gets cheaper to produce (e.g. code), demand for it actually increases.
Now you could argue that any non technical person could just oversee the agents instead. Possibly. Though in my experience, humans like to have other humans they trust oversee and understand important stuff for them.
ninininino · 5h ago
I guess maybe the analogy is we as software devs are all horses.
With Codex and Claude Code, these model agents are cars.
Some of horses will become drivers of cars and some of us will no longer be needed to pull wagons and will be out of a job.
Is that the proper framing?
allturtles · 5h ago
> Some of horses will become drivers of cars
An amusing image, but your analogy lost me here.
jimbokun · 4h ago
Guessing that's sarcasm.
ninininino · 4h ago
It's pretty intentional.
I think CEOs or PMs or Founders are like horse jockeys. Devs are like horses. (Some of them are both the jockey and the horse).
AI is a car. CEO or PM or Founder might smoothly swap out the horse for a car and continue on with little change.
For the horse to become a driver of a car is a more difficult challenge, but not impossible. It needs to evolve.
zackproser · 6h ago
Maybe, maybe that's FUD...I can't predict the future.
righthand · 5h ago
You can’t predict the future or are choosing to ignore the future?
Are you pretending that automation doesn’t take away human jobs?
sokoloff · 1h ago
When automation took away millions of farming jobs, I think that was good for society and virtually every individual in it.
jampekka · 1h ago
In aggregate it was good for society, but it was a disaster for a lot of people and a lot of areas. This is the theme of e.g. The Grapes of Wrath.
We should welcome automation and efficiency, but also address the situation of the "losers" of the development and not just expect the invisible hand will sort everything out.
micromacrofoot · 3h ago
Yeah but if you look to the present... there aren't really any jobs where someone is blissfully wandering the earth delegating tasks. Most of the time I can't even take a walk on calls because someone wants to screen share something with me...
I'd like you to be right, but I live in society where joy at work is often considered antithetical to productivity. No matter how much more productive I get, that space is used to fill in more productivity. We'll need more than tooling to stop this.
yieldcrv · 1h ago
> Codex then clones your repositories into its own sandboxes so it can run commands and create branches on your behalf.
Slurping up trade secrets
but maybe I'll sound like the people that are afraid of using github and other cloud git protocols
interesting crossroads
ramesh31 · 4h ago
Needs checkpointing. A full git commit is too much... commitment. Often you'll go down a bad path with agentic codegen that just falls apart, and you wont know where you wanted to return to until you're there. I'm very skeptical of the "automated PR" solutions at the moment. Too much time and money is lost to trust singleshot yet. And if you still need a human in the loop, best to do it in realtime with constant feedback, i.e. cybernetics not automata.
First, I don’t think they got the UX quite right yet. Having to wait for an undefined amount of time before getting a result is definitely not the best, although the async nature of Codex seems to alleviate this issue (that is, being able to run multiple tasks at once).
Another thing that bugs me is having to define an environment for the tool to be useful. This is very problematic because AFAIK, you can’t spin up containers that might be needed in tests, severely limiting its usefulness. I guess this will eventually change, but the fact that it’s also completely isolated from the internet seems limiting, as one of the reasons o3 is so powerful in ChatGPT is because it can autonomously research using the web to find updated information on whatever you need.
For comparison, I also use Claude a lot, and I’ve found it to work really well to find obscure bugs in a somewhat complex React application by creating a project and adding the GitHub repo as a source. What this allows me is to have a very short wait time, and the difference with Codex is just night and day. Gemini also allows you to do this now, and it works very well because of its massive context window.
All that being said, I do understand where OpenAI is going with this. I guess they want to achieve something like a real coworker (they even say that in their promotional videos for Codex) because you are supposed to give tasks to Codex and wait until it’s done, like a real human, but again, IMHO, it’s too “pull-request-focused”
I guess I’ll be downgrading to Plus again and wait a little to see where this ends up.
- Always run more than one rollout of the same prompt -- they will turn out different
- Look through the parallel implementations, see which is best (even if it's not good enough), then figure out what changes to your prompt would have helped nudge towards the better solution.
- In addition, add new modifications to the prompt to resolve the parts that the model didn't do correctly.
- Repeat loop until the code is good enough.
If you do this and also split your work into smaller parallelizable chunks, you can find yourself spending a few hours only looping between prompt tuning and code review with massive projects implemented in a short period of time.
I've used this for "API munging" but also pretty deep Triton kernel code and it's been massive.
How can non-technical people tell what's "best"? You need to know what you're doing at this point, look for the right pitfalls, inspect everything in detail... this right here is the entire counter-argument for LLMs eliminating SWE jobs...
I'm not sure a tool that positions itself as a "programmer co-worker" is aiming to be useful to non-technical people. I've said it before, but I don't think LLMs currently are at the stage where they enable you to do things you have 0 experience in, but rather can help you speed up working through things you are familiar with. I think people who claim LLMs will completely replace jobs are hyping the technology without really understanding it.
For example, I'm a programmer, but never done any firmware flashing with UART before via a USB flasher. Today I managed to do that in 1-2 hours thanks to ChatGPT helping me out understanding how to do it. If I'd do it completely on my own, I'm sure it would have taken me at least the full day to do so, instead of the time it took. I was able to see when it got mislead, and could rewrite/redirect from there on, but someone with 0 programming experience, probably wouldn't have been able to.
That's where I see AI-written software going, write-once. Some talented engineer gets an AI system to create a whole k8s cluster to run an application and if any changes need to be made, bugs fixed, it will take another talented engineer to come in and have an AI write a replacement and throw out the old one.
Reminds me of this blog, The real value isn’t in the code [0], we're heading for a world that is only code and no one who knows what it does. But maybe it won't matter.
[0] https://jonayre.uk/blog/2022/10/30/the-real-value-isnt-in-th...
The verb you use when you only need to produce boilerplate.
> Prompt™
The verb you use when it's time to innovate.
holy gaslighting Christ have some links, lots of people think that
https://www.reddit.com/r/ITCareerQuestions/comments/126v3pm/...
https://medium.com/technology-hits/the-death-of-coding-why-c...
https://medium.com/@TheRobertKiyosaki/are-programmers-obsole...
https://www.forbes.com/sites/hessiejones/2024/09/21/the-auto...
and on and on, endless thinkpieces about this. Certainly SOMEONE, someone with a lot of money, thinks software engineers are imminently replaceable.
> until the singularity curve starts looking funny.
well there's absolutely no evidence whatsoever that we've made any progress to bringing about Kurzweil's God so I think regardless of what Sam Altman wants you to believe about "general AI" or those thinkpieces, experts are probably okay.
Coding/engineering/etc is all problem solving in a strucutred manner.
That skill is not going anywhere
I wouldn't have to listen to people talk about it all the time if nobody thought it was true
There are also cases where it fails to do what I wanted, and then I just stop trying after a few iterations. But I've learned what to expect it to do well in and I am mostly calibrated now.
The biggest difference is that I can have agents working on 3-4 parallel tasks at any given point.
No comments yet
IMO just keeping an IDE window open and babysitting an agent while it works is less productive than just writing the code mostly yourself with AI assistance in the form of autocomplete and maybe highly targeted oneshots using manual context provided "Edit" mode or inline prompting.
My company is dragging their feet on AI governance and let the OpenAI key I was using expire, and what I noticed was that my output of small QoL PRs and bugfixes dropped drastically because my attention remains focused on higher impact work.
Every iteration I make on the prompts only make the request more specified and narrow and it's always gotten me closer to my desired goal for the PR. (But I do just ditch the worse attempts at each iteration cycle)
Is it possible that reasoning models combined with the actual interaction with the real codebase makes this "prompt fragility" issue you speak of less common?
Seriously, everyone should get good at fixing bugs. LLMs are terrible at it when it’s slightly non-obvious and since everyone is focusing on vibe coding, I doubt they’ll get any better.
Wouldn’t we all want that, but it sounds like you can leave task launching and planning to an AI and go find another career.
- it's a GREAT oneshot coding model (in the pod we find out that they specifically finetuned for oneshotting OAI SWE tasks, eg prioritized over being multiturn)
- however comparatively let down by poorer integrations (eg no built in browser, not great github integration - as TFA notes "The current workflow wants to open a fresh pull request for every iteration, which means pushing follow-up commits to an existing branch is awkward at best." - yeah this sucks ass)
fortunately the integrations will only improve over time. i think the finding that you can do 60 concurrent Codex instances per hour is qualitatively different than Devin (5 concurrent) and Cursor (1 before the new "background agents").
btw
> I haven't yet noticed a marked difference in the performance of the Codex model, which OpenAI explains is a descendant of GPT-3 and is proficient in more than 12 programming languages.
incorrect, its an o3 finetune.
This is Open AI's fault (and literally every AI company is guilty of the same horrid naming schemes). Codex was an old model based on GPT-3, but then they reused the same name for both their Codex CLI and this Codex tool...
I mean, just look at the updates to their own blog post, I can see why people are confused.
https://openai.com/index/openai-codex/
Edit:
Google just did it too. "Gemini Ultra" is both a model (https://deepmind.google/models/gemini/ultra/) and their new top-tier subscription plan (a la Open AI's Pro plan). Why is this so difficult?
1. Cannot git fetch and sync with upstream, fixing any integration bugs; 2. Cannot pull in new library as dependency and do integration evaluations.
Besides that, cannot apt install in the setup script is annoying (they blocked the domain to prevent apt install I believe).
The agent itself is a bit meh, often opt-to git grep rather than reading all the source code to get contextual understanding (from what the UI has shown).
I feel it will get there in short order..but for the time being I feel that we'll be doing some combination of scattershot smaller & maintenance tasks across Codex while continuing to build and do serious refactoring in an IDE...
There are so many content changes or small CSS fixes (anyway you would verify that it was fixed by looking at it visually) where I really don't want to be bothered being involved in the writing of it, but I'm happy to do a code review.
Letting a non-dev see the ticket, start off a coding thing, test if it was fixed, and then just say "yea this looks good" and then I look at the code, seems like good workflow for most of the minor bugs/enhancements in our backlog.
This almost seems like this is a funnel to force people to become software engineers.
Like:
- When making CSS changes, make sure that the code is responsive. Add WCAG 2.0 attributes to any HTML markup.
- When making changes, run <some accessibility linter command> to verify that the changes are valid.
etc.
The non-dev doesn't need to know/care.
It'll probably get there eventually, but today these are not things solvable with context.
For instance I ask it to make a change and as part of the output it makes a bunch of value on the class nullable to get rid of compiler warnings.
This technically "works" in the sense that it made the change I asked for and the code compiles but it's clearly incorrect in the sense that we've lost data integrity. And there's a bunch of other examples like that I could give.
If you just let it run loose on a codebase without close supervision you'll devolve into a mess of technical debt pretty quickly.
"Because we’re doing a fair amount of dynamic/Reflect.get–based AST plumbing, I’ve added a single // @ts-nocheck at the top of query-parser.ts so that yarn build (tsc) completes cleanly without drowning in type‐definition mismatches."
Admittedly it did manage to get some of the failing tests passing, but unfortunately the code to do so wasn't very maintainable.
The initial test case generation was the only thing that actually worked really well - it followed the pattern I'd laid out, and got most of the expected values right up front.
This feels so hopelessly optimistic to me, because "effectively away from our desks" for most people will mean "in the unemployment line"
I expect that anyone who is a skilled dev today will be fine. Expectations and competition might be higher, but so will production and value creation.
I think the demand will come, just as Excel didn’t put finance people out of jobs in aggregate.
Bankers (and customers) benefited from ATMs as far more bank locations became economically sustainable and bank tellers could do higher value work (and do so more safely).
Millions of software developers continue to benefit from improvements in productivity, the resulting value creation, and the resulting high pay in our sector from ever more productive languages and frameworks. Can you imagine how little pay you'd make trying to sling websites in assembly language at less than 1% of the pace of today?
Software engineers are dumb. Really dumb.
We've used our software development skills to automate other people out of work for what can be argued to be literally decades. Each time we did it, we certainly expected that the people affected would find other work. New jobs were created. The world didn't end. I honestly don't think it would be that much worse this time.
And that's the shitty part of the job, and everyone should be uncomfortable with it. I haven't literally automated anyone out of a job (that I know), but I definitely did not like finding out (after the fact) that one project was meant to enable a large offshoring effort.
> Each time we did it, we certainly expected that the people affected would find other work.
I do not expect that. That's a comforting lie people tell themselves.
> New jobs were created. The world didn't end. I honestly don't think it would be that much worse this time.
It didn't end, but it often got significantly worse for some. If the AI hype pans out, it's going to get significantly worse for software engineers. Your "newly created job," if it exists, will likely pay out a lot less that you're used to. At best, you'll get knocked down to the bottom of the career ladder.
It's a mistake to think about things in aggregate like you're doing. It's easy to hide inconvenient truths.
Uh.. I'm having trouble considering this as a serious question. It's objectively going to lead to them being in a worse situation. Mostly irrelevant resume and needing to re-skill into something and start from the bottom.. out of a well paid career that many enjoy and find fulfilling
My question wasn't an ethical one. It's why are the people that are the target of this automation happy about the progress, to the point of trying to push it forward faster, cheering it on
But the automation is not the problem, it's the economic structure in which increased efficiency makes a lot of people worse off.
If you’ve seen the work hours and work ethic of farmers, it’s safe to say that most of those people got other jobs that take far less work than farmers did/do.
Closer to our field, I think we’d have far worse work lives (fewer of us employed and much lower pay) if we had to code everything in assembler still. The creation of more powerful abstractions and languages allowed more of us to become software devs and make a living this way than if all we had were the less productive tools of the early days of computing.
https://www.epi.org/productivity-pay-gap/
Also there's a matter of taste, as commented above, the best way to use these is going to be running multiple runs at once (that's going to be super expensive right now so we'll need inference improvements on today's SOTA models to make this something we can reasonably do on every task). Then somebody needs to pick which run made the best code, and even then you're going to want code review probably from a human if it's written by machine.
Trusting the machine and just vibe coding stuff is fine for small projects or maybe even smaller features, but for a codebase that's going to be around for a while I expect we're going to want a lot of human involvement in the architecture. AI can help us explore different paths faster, but humans need to be driving it still for quite some time - whether that's by encoding their taste into other models or by manually reviewing stuff, either way it's going to take maintenance work.
In the near-term, I expect engineering teams to start looking for how to leverage background agents more. New engineering flows need to be built around these and I am bearish on the current status quo of just outsource everything to the beefiest models and hope they can one-shot it. Reviewing a bunch of AI code is also terrible and we have to find a better way of doing that.
I expect since we're going to be stuck on figuring out background agents for a while that teams will start to get in the weeds and view these agents as critical infra that needs to be designed and maintained in-house. For most companies, foundation labs will just be an API call, not hosting the agents themselves. There's a lot that can be done with agents that hasn't been explored much at all yet, we're still super early here and that's going to be where a lot of new engineering infra work comes from in the next 3-5 years.
Now you could argue that any non technical person could just oversee the agents instead. Possibly. Though in my experience, humans like to have other humans they trust oversee and understand important stuff for them.
With Codex and Claude Code, these model agents are cars.
Some of horses will become drivers of cars and some of us will no longer be needed to pull wagons and will be out of a job.
Is that the proper framing?
An amusing image, but your analogy lost me here.
I think CEOs or PMs or Founders are like horse jockeys. Devs are like horses. (Some of them are both the jockey and the horse).
AI is a car. CEO or PM or Founder might smoothly swap out the horse for a car and continue on with little change.
For the horse to become a driver of a car is a more difficult challenge, but not impossible. It needs to evolve.
Are you pretending that automation doesn’t take away human jobs?
We should welcome automation and efficiency, but also address the situation of the "losers" of the development and not just expect the invisible hand will sort everything out.
I'd like you to be right, but I live in society where joy at work is often considered antithetical to productivity. No matter how much more productive I get, that space is used to fill in more productivity. We'll need more than tooling to stop this.
Slurping up trade secrets
but maybe I'll sound like the people that are afraid of using github and other cloud git protocols
interesting crossroads