Comment by serial_dev | Hacker News Reader

Comment by serial_dev | Hacker News Reader

> We will add AI usage questions to our performance and peer review questionnaire

Not kidding, but I'm actually afraid people will check AI usage and start nagging us that:

> "You are slow because you don't use enough AI. Look at Tom (single 28 yo guy working every weekend on Adderall), he uses AI and he is fast. Gonna add a note to check up on your AI usage metrics in a month, hopefully it will improve".

Our company has Cursor, which I sometimes use, but 1. for lots of tasks, the most precise language is the programming language, 2. I don't love it, prefer other editors, and I go for in-browser search + AI.

If this letter was published by my CEO, I would either 1. ignore it, as CEOs are often out of touch when it comes to actual day to day work or they need to jump on the AI train to show how visionary they are even if they are aware of the limitations, 2. start looking for a job, because honestly, today it's a letter like this, in 3 months, you get a negative performance review because you didn't send enough queries to Cursor.

> for lots of tasks, the most precise language is the programming language

This is my problem with AI, or "vibe coding" or whatever you want to call it.

We already have many language(s) for expressing what we want the computer to do, and I find that natural language is the most difficult one to accomplish that goal.

Sure, LLMs might be able to whip up a fancy landing page and some basic API really quick, but when it comes to solving harder problems I find it incredibly frustrating and difficult to try and prompt in English, when the programming language I'm working in is already well suited to that task and is much more explicit in what I want.

Maybe I'm using it wrong, but it's way less cognitive overhead for me to just type for for x,y := range something {} than it is to try and prompt "Iterate over this list of values...etc."

When I'm programming, I'm not thinking in English

I've found that the only prompts that actually work for generating code reliably are the ones where you already know exactly what code it will output -- where nearly every part of the "how" is precisely clear, it just needs to be compiled from human language into code. Writing this perfect prompt often turns out to be a waste of time. It's a classic specification problem. Human languages will let you under-specify a problem, but the result will not be pleasant.

Maybe I'm using it wrong, but it's way less cognitive overhead for me to just type for for x,y := range something {} than it is to try and prompt "Iterate over this list of values...etc."

I'd say that prompting "Iterate over this list of values...etc." is definitely using it very wrong (autocomplete should more or less handle that sort of thing anyway). Prompts should be more in line with "write a C++ function that can parse XML files that look like this (upload a few sample files) and return the data in this struct (copy and paste struct from your header file)" followed by "write a set of unit tests for this function". You then check that the unit tests look reasonable, add any other things you feel you should test for, make sure the generated code passes the unit tests, and then check it in.

Use AI to generate AI prompts while you continue on with your normal work. How will they know if your code was not written by AI?

The "look at Tom" thing isn't new, there have always been sloppy engineers that crank out bad code faster than their peers and got praised for it while slowing everyone else down because they had to actual debug and integrate the garbage.

I stopped using AI completely but it also feels like 80% of startups now are building AI focused products. It's a huge red flag for me now that the company is just riding a trend instead of building a well thought out product. Maybe that's how startups always were but it feels so nakedly cynical now.

I'm also not a fan of how productivity expectations seem to getting worse because the people in the business side read that this makes programmers 150% more productive. They probably do write more code but if the shelf life of that code is worse and there's less knowledge in the organization about that code because the engineer was leaning on a stochastic tool, how much more are you gonna spend maintaining and rewriting that software? Just seems like we're all super excited to make crappier software faster.

I briefly worked for an “AI” company that was literally just a wrapper over Anthropic’s API. They also claimed to be HIPAA compliant despite sending 100% of their user data to these 3rd parties…

Yeah that's about what I expected lol

> single 28 yo guy working every weekend on Adderall

is that better or worse than ketamine for weekend productivity

> Gonna add a note to check up on your AI usage metrics in a month

Oh, oh and I almost forgot, I'm also going to need you to go ahead and come in on Monday/Friday too. Okay. We lost some people this week so we need to play catch up. Thanks!

> "You are slow because you don't use enough AI.

Or because you spend most of your time unravelling the crap code that AI produces. Creating apps with AI is one thing. Maintaining them is another.

Tom is webscale

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