It's not just corpo talk. The ultimate goal in LLM and AI progress is "replacement" of professional knowledge workers. In the march of the 9s of the accuracy of the generated LLM output, the engineers role would matter less and less.
It's asking engineers to "adapt" to being efficient in filling out the last 10% then 1% then 0.1% then 0.01%.
Hah, ultimate vibe coder nightmare scenario. I wonder if, in six months time, there will be enough stories like this for sanity to prevail a little more.
There's a neat / weird ladder that I keep seeing friends go through as they work through this.
- Volume. Kill the backlog! 8 agents in terminals, frantically!
- Ambition. Do the things you always want to do! You have the power!
- Clarity. Oh god I have to figure out what to do next.
That last one is honestly super-hard, but it's also the most valuable. Like, do you want to wake up every day and find new work, because you understand the machine better than everybody else? I know a bunch of people that love that stuff, but also a bunch that don't. I totally get that the transition is hard.
This is the right take. I wouldn't dare to write a TypeScript compiler a year ago but now I'm trying it and I have to say this has taught me so much about compilers, Rust and performance overall that wouldn't be possible before. It's a lot of fun to embrace the new technology and do bigger things.
Doing this sort of project is giving me a glimpse of what it is going to be like managing software projects. As software engineers we have to learn how to manage much bigger changes and in a much higher level of abstraction. I personally don't think models are good enough for this level of automation yet but in a weekend that I had access to Fable I could see how things are going to change soon. Most of criticism towards LLM coding was not applicable to Fable. I'm not hyping anything, just an observation.
The DJ analogy is useful actually. I live in Berlin and essentially everyone is a DJ but only a few get to make money from it. The difference is of course taste but also grit and how well those people leverage available tools to them. A good DJ knows how to use the tools and has a good understanding of the market. Different skill that a musician but nevertheless a valuable skill
Maybe, but the author's DJ analogy in the post was rather off the mark. Skill-wise, DJing is actually a perfect example of "it used to be hard" in pretty much every aspect -- beatmatching on vinyl, mixing in key, discovering new records, building and reaching a fanbase, getting distribution for mixes, physically carrying tons of records around and sometimes getting them stolen or damaged.
If everyone is a DJ now, it's because software and technology has made it so much easier than it used to be. Although to be clear, I completely agree with your comment on how successful DJs are the ones who leverage modern tools and understand the market.
But in terms of the analogy in the original post, the author is making some weird comparison between guitar players and DJs, which is totally apples to oranges... not to mention that selling out stadiums solo has never been easy for anyone, regardless of year or whether you're a guitar player or a DJ.
I live in Berlin and not everyone is a DJ. You just live in DJ circles. Everyone I know is a vulture capitalist. There's a lot of room for monetisation in this city.
Yes! And more projects. And you have the freedom to try and fail.
Was thinking of a comparison, cars are faster than walking. Imagine saying, no I prefer only walking. It is healthier than sitting in a car and your legs will atrophy. That is very much true (and we can see the consequences in car dominated societies). Nevertheless, for many industries cars are very important. You don’t say, I would rather carry all these pallets by hand rather than use a forklift.
LLMs are similar in my mind. They turbocharge your output in all senses but is less holistic than hand-coding. Like cars, you are making a trade off but I don’t think it’s fully a replacement. We still walk with cars in our lives. And we don’t eschew cars because they are “worse” for you than walking. We adapt and make tradeoffs
Agreed, I don't know if it's going to stay like this forever, but right now, if anything, the difference is amplified. You can make unbelivable stuff happen through the sheer power of knowing what you're doing.
I feel the same. More projects, more ambitious projects. I would have not been able to even imagine sone of the things I am building now, not to talk about implementhing them alone.
Almost every item in this list (except Karpathy's LLM Wiki) is based around vector embeddings.
Vector embeddings were super-hot a couple of years ago, but I don't think they have sticking power.
The moment you have an agentic tool calling loop the idea of doing a big fuzzy embedding search and hoping you get back relevant results loses attraction. You can give your agent ripgrep and let it figure out how to find the right results all on its own.
The biggest downside of embeddings is that it's very hard to set a threshold score below which you ignore things. If you ask a vector index for 10 results ordered by similarity you'll get 10 results - but results 3-10 might be total junk.
Very cool, never thought of that! "way smaller" is almost an understatement, when it's 50kb :P Neat that it loads in GitHub READMEs as well, which is probably a large reason people use .gif today.
It's a cool tool/platform, but very different. Asciinema tries to make the "multimedia" itself better by making it actual text instead of being video/images, while the CLI command above turns actual text into multimedia supported by platforms already. Both are useful, both have their use cases :)
I have a bunch of opinionated/personal-use binaries like this in my $HOME/bin/, like delete-all-npm, clean-rust-cache, download-youtube-playlist, and get-markdown <url>. It feels good, and I don't need to remember any commands. Sometimes my coding agent can figure out how to call some of those tools too ;))
This isn't the first time this has happened, either. I do not understand how these consultancies - who sell these "reports" for six or seven digit sums - continue to mess this up. It should be excruciatingly embarrassing for them.
I guess nobody ever got fired for paying KPMG and friends for an expensive report that supported their priors.
KPGM et al. are used as political ammo to push through internal changes. Those in power rely on consultancies underlying their decisions (painful redundancies, firings, etc.). Acknowledging that the arguments for these painful decisions was hallucinated will lead to many problems for powerful people, so for now it's best to just try and sweep it all under the rug.
These six-figure reports are produced by underpaid kids in their twenties working 18 hours a day.
The purpose of paying for these reports is for executives to have someone else to blame when their idea doesn't work. It has nothing to do with the correctness of the content.
> These six-figure reports are produced by underpaid kids in their twenties working 18 hours a day.
That's accurate, for the first draft. Similar to big legal firms - subsequent versions are signed-off and passed up (and if revisions request, down) the hierarchy, each stratum with its own billing rate(s).
Which makes me wonder when the hallucinations got added.
It can't have been at any of the big 4, because partners aren't skipping 4+ org-chart layers to look at draft documents written by early-career associates. I have no experience with body shops - if that's where you were.
I would have to disagree, this report in question sounds more like thought leadership dribble rather than a report commissioned by a client with a scope attached.
The purpose of most reports are absolutely for Assurance to decision makers or management and often times, we disagree with management or provide a view that might not favorable. Which just reflects the realities of what we have identified or tested.
As I said, this seems like thought leadership dribble which absolutely even as someone who has worked in Big 4, I think they're pretty average.
The problem is that there's a lot of people running around who believe the polite fictions we tell ourselves about review processes. It's very hard to explain why it doesn't work to have someone manually clean up a sloppy AI draft without discussing the fact, which many people find unacceptable, that manual review can't catch all errors.
I lurk on the teachers subreddit and get shown videos by teachers on TikTok and the impression I get from that algorithmic bubble is that the kids can't read any more - reading comprehension in particular is terrible. Lots of anecdotes of kids who can't read a few paragraphs and then answer questions about what was in them.
My impression of that sub is that it's a lot of people who went through honors classes in a "good" school district, and are now teaching non-honors, potentially in a "bad" school district and are discovering how the other half lives.
Hasan Piker's political project polls extremely high (universal healthcare, abortion access, and more), so actually you could understand American voter politics by reading Hasan's comments amusingly enough.
As of ~8 months ago the quality is most definitely there, for almost every form of programming I've experienced.
If you're working in some vanishingly rare domain then maybe it's not yet, but most coding challenges are very much in the wheelhouse of the current frontier models.
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