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Asana cleared 5 years of engineering work in 2 weeks with Codex

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Re: Asana cleared 5 years of engineering work in 2 weeks with Codex

#81

Post by avgDev »

amluto wrote: post #80

I can easily clear lots of low-priority engineering work quickly using AI. It takes a bit longer if I want to do a good job. But here’s the rub: this is, basically by definition, low-priority engineering work. Those fixed papercuts are nice to have fixed but they do not necessarily add a lot of value. And it’s all too easy to lose value by doing this. For example, current LLMs really really like adding test cases, an…

It has it risks too. I've used chatGPT for a feature I am working on. It works, I have already resolved some bugs the it didn't pick up. However, the code quality is odd, I've had some hardcoded types as it is unlikely they will ever change. For some of them chatGPT created enums but only for some.

I also realized that review generated code sucks, I can generate a whole app quickly, but I have no understanding of small decisions. It is extremely difficult to wrap your hand around hundreds of lines of code written by someone else.

Re: Asana cleared 5 years of engineering work in 2 weeks with Codex

#83

Post by iamleppert »

forrestthewoods wrote: post #46

5 years? Bruh. There’s no way from scratch it would take 5 years.

It does when you have a team of 100's of engineers every change has to pass through, 3 layers of management, SRE teams, DevOps YAML engineers, product management and a partridge and a VP.

Re: Asana cleared 5 years of engineering work in 2 weeks with Codex

#85

Post by structural »

localhoster wrote: post #14

You see, I call bs on that. Not on the part that agents are an accelerator, they might be, but at the part that it was a 5 year project. We engineers, had the power to dictate how our days will look, and we were able to give ballooned timelines to give us room to braeth. This has changed. The power is no longer in our hands, for good or bad. I suspect it as a two month project without agents. Max.

The five year project likely represents a bunch of engineers that are stuck in meetings and coordination for 75% of their time, then you staff the project with more people (because you need four times as many) then they all need more meetings to coordinate too. And then they need to write a lot more documentation in the process because in that five years the people working on the project will all turn over at least once if not 2-3 times. Never mind critical people getting pulled off the project to work on other more important things on a monthly basis as is common at large firms.

It's entirely possible for a 2-3 month project if one senior person was left the hell alone to do it to take a dozen people five years.

Re: Asana cleared 5 years of engineering work in 2 weeks with Codex

#87

Post by internet_points »

YeGoblynQueenne wrote: post #77
internet_points wrote: post #60

Earlier quoted context omitted.

> parroted in the media ugh just recently I saw a news article gushing about how AI had helped with some health/medicine study, and various patient organizations were all like "oh yeah this is a Good use of AI" and then I click the link to read the study and it's decision trees and clustering on a tiny dataset that you could analyze with a ten year old laptop. I mean, sure at some point decision trees and clustering…

Decision tree learning is a form of machine learning and machine learning is subject of AI research. Same for clustering. Why are you saying they "were" called AI? They still are. Maybe everyone now synechdochically calls LLMs AI but that doesn't mean other kinds of AI are not AI. AI research is not over yet. If OpenAI and Anthropic fail to bring on the Singularity, what are we going to call the continuing research o…

> that doesn't mean other kinds of AI are not AI

I kind of agree, though I find "AI" to be an almost useless term, in particular these days. I dislike the current state of discourse where AI is used to mean inhumanly large models, so I tend to use a specific term like LLMs instead of AI. But the point here wasn't whether this or that form of ML is in fact AI. The term "AI" was almost never used in mainstream media until a few years ago, when it suddenly it was all over the place https://trends.google.com/trends/explore?date=all&q=AI,Biden... and nearly without exception referring to very large generative text/image models. So when a news article in 2026 talks about AI without specifying that it's nothing to do with ChatGPT etc. (and in fact using a very different method requiring no large pre-trained model and no dependence on large companies), I find it highly misleading.

Re: Asana cleared 5 years of engineering work in 2 weeks with Codex

#88

Post by amluto »

avgDev wrote: post #81
amluto wrote: post #80

I can easily clear lots of low-priority engineering work quickly using AI. It takes a bit longer if I want to do a good job. But here’s the rub: this is, basically by definition, low-priority engineering work. Those fixed papercuts are nice to have fixed but they do not necessarily add a lot of value. And it’s all too easy to lose value by doing this. For example, current LLMs really really like adding test cases, an…

It has it risks too. I've used chatGPT for a feature I am working on. It works, I have already resolved some bugs the it didn't pick up. However, the code quality is odd, I've had some hardcoded types as it is unlikely they will ever change. For some of them chatGPT created enums but only for some. I also realized that review generated code sucks, I can generate a whole app quickly, but I have no understanding of sma…

If you mean chatgpt.com, try with a real “agent” harness. The exact same model on chatgpt.com frequently performs much worse than it does with a proper harness, not to mention that the chatgpt.com frontend itself is quite bad.

codex-rs, popularly known as Codex or maybe the Codex CLI, is a fine choice.

Re: Asana cleared 5 years of engineering work in 2 weeks with Codex

#90

Post by zeristor »

One thing from experience having worked on a project 4 years ago, 2 of us spent a a couple of months investigating and coming up with a solution.

I tried it in AI and virtually did it all in a few hours! Magic?

Well I had gone through it to explore the problem space, and we had found a working solution which just petered out. But I still remembered the learnt lessons, and I was just eager to see what it would be like to use DuckDB on it.

My point being these second passes on projects often skip the hard won knowledge part.

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