jemiluv8

I remember enjoying myself more as an intern in a fullstack capacity than I did when I was given the job full time about three months later. But that was 7 years ago.

I also remembered the sheer joy of forking enterprise codebases like that of cal.com and highlight.io - just to study and try to understand how large teams worked. I followed issues, I read through PRs and related comments, looked at how some of the comments were resolved. I studied the various moving parts of the app - highlight especially being effectively a log ingestion and aggregation platform, had some rather large infrastructure requirements - kafka, redis, postgresql, clickhouse. It was hard to run with infrastructure directly on your computer. You had to use their docker containers.

I also remembered reading through a tutorial for an sqlite clone in C. It was interesting. I particularly enjoyed typing out the C code and even trying alternate implementation of b-tree operations.

I remember back in 2022 - after I was unemployed for a while - I discovered open source bounties on algora.io (LLMs have since made this platform go bust). I was able to earn roughly $300 per month for a while working on open source issues ranging from $50 to $350. Now most $50 bounties can be one-shot with frontier models. So of course, no one posts open source bounties anymore. If you do, you may just end up with 50 slopped PRs.

Just random thoughts.

I haven’t verified the dates of the tweets. But it is a huge leap from a delayed release to a major conclusion that “the rewrite is not looking good”.

Yet another clickbait making outrageous assertions. Fwiw I don’t think anyone’s reputation is on the line and so far, you’ve offered only anecdotal evidence at best. Things like this should be backed by stats and community surveys and a whole lot more. I didn’t see anything about number of downloads or any of the usual metrics used to judge software these days

Your whole scientific endeavor in this seemed to thrive on the rock solid foundation of tweets.

And all those referencing of the Kelly post makes this even more of a clickbait. All you had was to put all the ingredients of a post that will draw the crowd but offer very little on the subject matter it purported to discuss

Awwww maaaan. I was just reading an upstream patch on the erpnext framework. I was going to do their copy the pr to patch my erpnext v15

Nearly everyone I suppose. There are always outliers I suppose. I’m going for 90%+ using llm in some capacity even if just a single ChatGPT prompt.

This post misses a couple of points

1.”Writing software was never the hard part” - isn’t saying coding was easy. The comparison was against building a viable product. Doing business involves a whole lot more ambiguity than sitting in your room writing code. You could build anything and yet the hard part was building something that matters

2. >> Nobody knows how the AI revolution will play out in the end

I disagree with this statement as far as Software Engineering is concerned. We kinda know. Everyone uses an agent harness to code this days - the only real difference is in how - and that still sets developers apart but most are using similar tools.

This reads more and more like clickbait. Sorry. I always find posts like this outrageous but I suppose that was the author’s intent. Outrage will get you votes. Taking extreme positions in an argument will get you attention. Kuddos

I’d go with a balanced view: you need them both for any non-trivial product. I was recently reviewing a PR that renamed a model, I wanted to understand what happened under the hood. Turns out that mariadb had a rename table operation forever ago and that was used by the orm under the hood. So no need to backup the prod table. Just run migrate and be done with it.

PS: I still exported the table before deploying this fyi.

Glad you gave yak-shaving a proper definition. I was always annoyed at my boss for insisting on a particular arrangement of import statements in typescript files. For him, it was a way of telling us to be more mindful of the code we typed. But mostly I’d have preferred a simple eslint config with autofix on save. This kinda yak shaving is no fun - trust me

Task tracking is now obsolete. Only the slowest most inefficient firms do this. So yes, I am learning as well how tasks are now effectively harder to create than actually implement, I tend to be a bit verbose and sometimes research the codebase for how a feature ought to be executed. All in all my tasks could eventually be done faster by llm’s

Personally, since I only do cosmetic changes to PRs like refactoring them to fit into the current codebase and sprinkling some best practices here and there - I haven’t noticed any decrease in coding velocity.

I have fond memories of this project. Contributing to it really helped me ramp up my dev skills and was effectively my introduction to monorepo’s in JavaScript. It was the kind of codebase I couldn’t get my hands on while working in my part of the world. Good luck going closed source.

All the author’s reasons for wanting the raw text that wasn’t altered by AI are all the reasons why I like to pass my messages through llms because for most people clarity in thoughts is not a given.

Often, in formal communication, I find it makes a lot of sense to make it as robotic and to the point as possible because informing my boss about the progress of a project shouldn’t leak any emotions. This is not a romantic or social relationship where emotions need to be expressed.

And I like the idea of setting goals for what I want to convert and having these llms go through the message and let me strip out the fat and ensure there is little room for misinformation and digression.

So yeah, what the author wants probably works more in an informal social setting than in a formal.

Outsourcing to thinking is exactly what I tell our developers. They are hired to do the kind of thinking I’d rather not do.

I was reading the above PR and a couple of others that were rejected primarily because the person making the PR didn't even understand the problem to begin with.

LLMs tend to make most people feel like they can write code without understanding the problem at hand. In a lot of cases, they even climb the ladder of ai-suggested designs and end up with what is probably poorly designed but works anyway. That probably fuels their confidence and gets them to continue - I get away with some of these things on most reactive UI frameworks.

When doing systems programming however, it is hard to get away with poorly designed, conceived and executed work. Especially in open source projects where a couple of maintainers have to retain context of the entire project over a long period of time to facilitate their ability to review and make community contributions possible. These people tend to understand the product deeply and tend to also do gate-keeping for the quality of code that is contributed. Without that gate-keeping, open source might just not be sustainable.

Today with all these llm tools, people just get up and feel like they can ai-slop their way to PRs on open source projects. This is a maintenance burden on open source maintainers that I fear will only increase over time.

It is probably time for github to implement a policy of enabling maintainers to ban some users from making a PR?