I don't know what kind of work he's doing that doesn't require actually reading the code to ensure it's appropriately maintainable, but more power to him. I actually like knowing what the hell my code is doing and that it conforms to my standards before committing it. I'll accept his condolences.

Same, seems completely irresponsible.

We don't have time for safety, or security, or accuracy, or even understandability anymore. We need to move fast! /s

I really despise that people like you ruined em dashes for the rest of us who have enjoyed using them.

An idea I like to bounce around is that everyone at the highest offices of power (not going to define that here) should be forced to live in monastic conditions during the term in which they hold power.

You are fed, clothed, and housed by the state. You have no luxurious amenities, no exercise of personal wealth, no contact with anyone other than for official business.

If you honorably discharge your duties to the completion of your term of office, you will be compensated for life to such a degree that you will never have to work again.

There's a lot of nuance that I'm glossing over, but the gist is that holding powerful positions ought to require severe personal sacrifice, but you will be handsomely rewarded after-the-fact if you bear that burden with dignity.

> handsomely rewarded after-the-fact

The other more important effect is that it neuters any kind of quid pro quo type of corruption, if paired with a big enough stick. It's hard to bribe someone if they will get to live in luxury for the rest of their life anyway, and where discovery of the deal would land them in prison for life.

There's a subset of people whose identity is grounded in the fact that they put in the hard work to learn things that most people are unable or unwilling to do. It's a badge of honor, and they resent anyone taking "shortcuts" to achieve their level of output. Kind of reminds me of lawyers who get bent out of shape when they lose a case to a pro se party. All those years of law school and studying for the bar exam, only to be bested by someone who got by with copying sample briefs and skimming Westlaw headnotes at a public library. :)

It's not that our identity is grounded in being competent, it's that we're tired of cleaning up messes left by people taking shortcuts.

It's that, but it's also that the incentives are misaligned.

How many supposed "10x" coders actually produced unreadable code that no one else could maintain? But then the effort to produce that code is lauded while the nightmare maintenance of said code is somehow regarded as unimpressive, despite being massively more difficult?

I worry that we're creating a world where it is becoming easy, even trivial, to be that dysfunctional "10x" coder, and dramatically harder to be the competent maintainer. And the existence of AI tools will reinforce the culture gap rather than reducing it.

It's a societal problem we are just seeing the effects in computing now. People have given up, everything is too much, the sociopaths won, they can do what they want with my body mind and soul. Give me convenience or give me death.

We just have a magnetic whiteboard on the refrigerator and write down things we need to buy when we run low/out. A true modern marvel, and no AI bot required!

Target undeserved businesses with niche problems that have traditionally been ignored by tech companies because those markets have always been considered "too small" to be worthwhile.

Why would any big software company need to care? There are so many small businesses with unique problems with no current off-the-shelf software solutions because they've always been too niche to justify the time and expense of bespoke development. Now that door is open. Big software companies can keep servicing big businesses and mass markets, while opportunities abound for anyone else willing to innovate on smaller problems. Not everything needs to be built to scale.

I don't care about technology for what it is. I care about it for what it can do. If I can achieve what I want by just using plain English, I'm going to achieve what I want faster and more thoroughly enjoy the process. Just my two cents.

I accept there are productivity gains, but it's hard to take "10x" seriously. It's such a tired trope. Is no one humble enough to be a meager 2.5x engineer?

10x probably means “substantial gain”. There is no universal unit of gain.

However if the difference is between doing a project vs not doing is, then the gain is much more than 10x.

I don't know what to tell you, it's just true. I have done what was previously days of BI/SQL dredging and visualizing in 20 minutes. You can be shocked and skeptical but it doesn't make it not true.

There is no x is because LLM performance is non deterministic. You get slop out at varying degrees of quality and so your job shifts from writing to debugging.

Even 2.5x is absurd. If they said 1.5x I might believe them.

I'm building an AI agent for Godot, and in paid user testing we found the median speed up time to complete a variety of tasks[0] was 2x. This number was closer to 10x for less experienced engineers

[0] tasks included making games from scratch and resolving bugs we put into template projects. There's no perfect tasks to test on, but this seemed sufficient

Have you evaluated the maintainability of the generated code? Becuause that could of course start to count in the negative direction over time.

Some of the AI generated I've seen has been decent quality, but almost all of it is much more verbose or just greater in quantity than hand written code is/would be. And that's almost always what you don't want for maintenance...

One concern is those less experienced engineers might never become experienced if they’re using AI from the start. Not that everyone needs to be good at coding. But I wonder what new grads are like these days. I suspect few people can fight the temptation to make their lives a little easier and skip learning some lessons.

That sounds reasonable to me. AI is best at generating super basic and common code, it will have plenty of training on game templates and simple games.

Obviously you cannot generalize that to all software development though.

As you get deeper beyond the starter and bootstrap code it definitely takes a different approach to get value.

This is in part because context limits of large code bases and because the knowledge becomes more specialized and the LLM has no training on that kind of code.

But people are making it work, it just isn't as black and white.

That’s the issue, though, isn’t it? Why isn’t it black and white? Clear massive productivity gains at Google or MS and their dev armies should be visible from orbit.

Just today on HN I’ve seen claims of 25x and 10x and 2x productivity gains. But none of it starting with well calibrated estimations using quantifiable outcomes, consistent teams, whole lifecycle evaluation, and apples to apples work.

In my own extensive use of LLMs I’m reminded of mouse versus command line testing around file navigation. Objective facts and subjective reporting don’t always line up, people feel empowered and productive while ‘doing’ and don’t like ‘hunting’ while uncertain… but our sense of the activity and measurable output aren’t the same.

I’m left wondering why a 2x Microsoft of OpenAI would ever sell their competitive advantage to others. There’s infinite money to be made exploiting such a tech, but instead we see highschool homework, script gen, and demo ware that is already just a few searches away and downloadable.

LLMs are in essence copy and pasting existing work while hopping over uncomfortable copyright and attribution qualms so devs feel like ‘product managers’ and not charlatans. Is that fundamentally faster than a healthy stack overflow and non-enshittened Google? Over a product lifecycle? … ‘sometimes, kinda’ in the absence of clear obvious next-gen production feels like we’re expecting a horse with a wagon seat built in to win a Formula 1 race.

> That sounds reasonable to me. AI is best at generating super basic and common code

I'm currently using AI (Claude Code) to write a new Lojban parser in Haskell from scratch, which is hardly something "super basic and common". It works pretty well in practice, so I don't think that assertion is valid anymore. There are certainly differences between different tasks in terms of what works better with coding agents, but it's not as simple as "super basic".

I'm sure there is plenty of language parsers written in Haskell in the training data. Regardless, the question isn't if LLMs can generate code (they clearly can), it's if agentic workflows are superior to writing code by hand.

There's no shortage of parsers in Haskell, but parsing a human language is very different from parsing a programming language. The grammar is much, much more complex, and this means that e.g. simple approaches that adequate error messages don't really work here because failures are non-actionable.

I estimated that i was 1.2x when we only had tab completion models. 1.5x would be too modest. I've done plenty of ~6-8 hour tasks in ~1-2 hours using llms.

Indeed. I just did a 4-6 month refactor + migration project in less than 3 weeks.

Downvoted for...confidently saying how successful I was using an AI? I don't get it.

What's the link?

The site is password protected because it's intended for scholarly researchers, and ironically the client doesn't want LLMs scraping it.