Task Paralysis and AI

If you look at agile processes one of the biggest criticisms is that there's always a magic "customer" role that needs to prioritize existing work, do acceptance testing for completed tasks, and give requirements deep enough to create real specifications. This often required a lot of attention to detail and very fine grained judgment typically lacking in those that are eager to have a job title of "customer".

And now if you look at dark software factories, these pieces are also basically everything they're missing. The person/people responsible for this role were never seen as being engineers/programmers in those processes, but I think that's where most SWEs will end up, because as these tools mature to the point they manage the code all on their own that's what's going to be left to the SWE in the chair.

The SWE of course won't be the actual customer/stakeholder, they'll be the proxy, the one that has to navigate meetings in meatspace and make soothing noises to the actual customers. Will they be happy doing this? That's a big group of "they" so some will, sure. But I think a lot of people who got into this career consider this the worst part of it, and it's now going to be the whole job.

Now I am just a monkey thats: 1) add enough context, description and harness to an agent 2) review ouput and repeat 1) if context is lacking

It was bottom to top: from understanding to implementation. You were the owner. Now it is top to bottom: get implementation first, try to get understanding later. Thinking is also delegated. "Think" nowadays is "reformulate,answer questions, add context, try again". This doest feels like I am doing the work, this feels like I am a limiting factor here

Another side effect is that any code now have 0 value. No one evaluating how you guided an agent, what decisions you took. People seeing your work and think "ye, I could vibe code that too with enough time" even if this is not true

And my work isn't css and html (with all respect). It is mostly high performance clusters, parallel computing, OS, low level, SOTA online llm inference etc

Now I am seriously considering blue collar job, as I have more joy building stuff with my hands than to be a passenger/context generator to an ai. I am not a business driven person, I don't really care how much money my company earns (sorry). I just like to solve technical puzzles and think hard

P.S. yes, there are corner cases ai can't do well: non trivial, highly specific algorithms and implementations; complex patches to gigantic multi domain proprietary code bases, but that's like 5% of my work

I've tried to stay away for a variety of reasons (not approving of the way the tech was developed hovering up everyone's data for commercial gain, high amongst them), but the company I'm now part of (due to them buying us) is drinking deep from the GenAI water fountain, so I will very soon have no choice but to engage or be pushed out¹. I get it, I see the benefits, but it feels like turning into a manager (for GenAI agents rather than people, but still…) which is something I've always avoided because I want to tinker, I got into programming and database work because I like to play with the nitty-gritty details and I'm going to have to let that go.

To be frank, there is a sizable part of me that has wanted to be out of tech for a while² for various reasons³ and that part of me would prefer to go waiting tables if that is what it takes to escape! Maybe then I can reclaim tinkering as a hobby.

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[1] Redundancy would be nice, with 26 years service the statutory minimums would be more than enough to tide me by for a while, but I expect they'd not do that. I'd instead be put on a PIP for not performing (assuming they can make a case for not engaging with GenAI making me less efficient), and if I still don't play ball that'll be grounds for dismissal.

[2] Or at least take a fairly long sebatical.

[3] Not liking remote teams being a significant one, and even though I go into the office⁴ I'm still remote because most of everyone else is.

[4] which grants me the home/work separation

So there's a lot of nuance to the "is it that you enjoy figuring out the instructions to use to solve a problem".

At the surface I don't enjoy typing, I don't enjoy fighting syntax checkers, rust's borrow checker, or manual memory management in my personal C projects, typing out the HDL for nand2tetris problems, etc...

However, there have been studies done decades before this LLM boom about the psychological concept called the Generation Effect. While everyone is different and it's not completely black and white, the studies have found that people learn more by actual practice (the act of doing) than just by reading material. That's 100% the case for me.

I can read blogs and resources till the cows come home and I'll have a very surface understanding of a concept. Then I'll go to write the code to implement it and it rarely works right away because there are demonstrable gaps in my understanding. I'll debug it and iterate on it until it works, and that is what actually solidifies the mental model of what I was trying to learn in my mind. Not only can I say for sure that I remember it better, that seems to form connections in my brain that allows me to apply it in other use cases, or build fascinating technical tangents.

I not only get my high from that initial "Aha!" moment when I really feel like I understand a concept enough to actually apply it in other scenarios, but I also get my high from tangents that spawn off of that concept.

In many cases, I can map a direct line of my personal projects to a set of root projects that spawned them off because of ideas I came up with while actually implementing the projects. Since I tried real hard to optimize a C# game engine for an embedded platform, I realized where limitations were and it solidified my knowledge of how old game consoles worked.

This led me down to the interest of creating a GPU out of embedded device that I can pair with I/O constrained embedded devices. This taught me soooo much about the embedded space, and while I heavily improved my C writing abilities it also made me wish I could write C# on embedded.

Since I had learned C for the embedded project (and I knew MSIL from previous deep dives), I realized I can just translate MSIL into C and that would allow me to run C# anywhere (got C# working on an SNES, the linux kernel, and on an ESP32S3).

By implementing that by hand and coming face to face with many small decisions I had to make, that solidified a bunch of concepts in my head around intermediate representations and why they are a massive benefit. Those aha moments (among others) then led me down the path to implementing a just-in-time compilation engine for NES games and the C64 OS into the .net runtime.

The learnings from that have already spawned some other ideas in my mind, which is why I'm now learning Verilog and FPGA development.

None of these projects solved any useful problem (as in nothing was created that I or anyone else would use). The satisfaction and the high I got from them was having the curiosities of a problem, ideas of a solution, and persevering (partially due to being stubborn) through it and actually accomplishing it. The satisfaction that I actually understand the concepts at a foundational level, which actually ends up breeding excitement for a whole other tangent/problem.

These learnings have indirectly helped me in my day job as well. While I'm not working on anything that sophisticated or cool, all of these actual implementations I've learned have given me direct learnings I have been able to successfully use to create better software in other domains.

So it's not the actual typing I enjoy, but the whole picture of what comes out of the end through that typing. LLMs take most of that away. It lets me ideate on a vague solution and then it goes ahead and implements it for me. Even if I'm specific on the details of the algorithm it uses, it subtly fills in the blanks and the missing pieces that I haven't cemented in my brain yet thus making me miss out of the opportunity to do so.

And it steals the accomplishment of the final thing existing. I don't feel an accomplishment by typing in google "I need a C# to C transpiler" and just downloading it. That's what LLMs feel like, even if I'm trying to steer them at a lower architectural level. I don't have the aha moments, I don't have the learnings, and I'm disconnected from the code.

Thus it feels like it's stealing all the intrinsic rewards from me, only leaving the extrinsic ones. And those are not rewards I am particularly motivated by.