The New AI Superpowers: Focus and Followthrough

This seems very related to a trend I’m seeing as my company goes all in on AI: everyone thinks that every problem is “a couple hours” with AI now, and they all want zero external dependencies because they can move faster alone. As a result, we’re now in an even worse “yet-another-…” age where everyone has built approximately the same (but somehow incompatible) versions of all the same beginner-level software, and (ironically) while they want no external dependencies they’re also pushing for org-level mandates to require everyone else to use their solution. Meanwhile, no one wants to do the slow/bottleneck part that cant easily be automated or scaled; they just throw an “agent” at it and call it done—but there’s nothing _there_. You can trust the agent on easy tasks and you can’t trust it on hard ones, but you can’t tell which ones are easy or hard. Improvements in foundation model tech move thresholds of the problem but can’t eliminate it.

Long story short, I think we’re in a phase where the organizational value function is lagging behind the tech. A “proof of concept” used to be correlated with “proof of work” and some amount of domain understanding, but I think now what we need is a focus on “proof of understanding” or else you’re probably just wasting tokens on a baby version of the problem. A decent proxy right now is that if you have zero external dependencies then your solution is probably a toy.

In my side hustle time, I use coding agents to explore what if projects I would otherwise never get to build.

At my day job, I use AI to fix config, container, and installation issues so I can spend my time coding instead of struggling to fix mostly other people's mistakes. And really, in this age of python wheels, containers, virtual environments, and fragmented APIs, the cognitive load of doing this by hand would shut me down for the day.

1.5 years in and I haven't burnt out. If anything, I'm ramping up. I'm no longer afraid of adding a web UI, or insane numbers of unit tests, or deploying other people's software.

What I'm not doing is using it to build products, but instead just doing so to augment the supporting stack. All of this is subject to change as the AI landscape evolves.

At least in Enterprise IT, where I work, the challenge is not how you scale technology, but how you scale trust. Big IT problems are always trust problems. That messy CRM systems everyone complains about? The messiness is likely due to low organizational trust, departments working in silos, and disagreements on definitions (what is a customer?).

LLMs can scale technology, but they are terrible with scaling trust. You know what scales trust in Enterprise? Good leaders, good culture, good conversations, good meetings, good narratives, good insights, good decisions. Exactly the things that scaled trust 50 years ago, and exactly the things LLMs cannot directly impact.

But now see what is happening. Rather than doing the hard work of gaining trust and consent, employees are using LLMs to build their localized agents. Of course they are happy! But the Enterprise, as a whole, is not better off, the real problems have not been addressed, the consensus has not been reached.

I came close to burning out around two years ago. It wasn't even the workload so much as the uncertainty of being able to solve hard problems and feature requests on time. I was in a constant state of stress and fear, thinking about those problems in the evening, at night, and in the morning.

With AI—or coding agents, to be more specific—I'm perhaps working even more than before, yet I feel considerably more relaxed. It feels like the variance in task difficulty and uncertainty has flattened out. If I had a difficult network-related issue before, it might have taken me hours of research and debugging before even being able to tell what was even going on and how long it would take to fix. Now I can just spawn an agent with the right keywords, in the right environment, and with the right permissions, and get feedback within minutes while focusing on other stuff in the meantime.

While I was pessimistic about where software development was heading just a year ago, I now feel more optimistic and happy about how things are going. My only concern, however, is whether it will reduce the demand for software engineers in the long run.

I was getting frothy and feeling stress due to juggling sessions. I switched to managing my backlog (Obsidian base), writing specs, launching agents in the background. I review and make changes,merge and release. It's a fixed cycle and I optimize to maintain relaxed engagement. Rate of features and fixes went up a lot.

I'm actually not feeling the 'burnout', though I too have a bunch of projects sitting at various levels of vibe-completeness. Mostly one just kind of yanks on my attention a bit more than the others and so they end up getting a little neglected. I'm fine with it though, I love having all these little forever projects of mine finally coming to life. My worry is kindof the opposite, what happens when I've finished all the things. Will I run out of ideas? I hope not, but already some of my pet projects have reached a level of completeness where I just cannot see anymore to add, for me they have reached a level of done. That frees me up for the next project but what if I run out of projects!

Felt like the article could have benefitted from more focus and follow through tbh. Relatable problem, but it didn't say anything beyond exactly what you would have gotten from reading the title.

> So logically, if AI can help us complete tasks 2-100x faster than before, we should be UNDERWORKED and experiencing ZERO burnout, right?

Got to admit, I stopped reading here.

In my experience, burnout isn't related to the amount of work, but to your confidence in being able to do your job and if you find your job meaningful (like, does it even matter?).

I'm probably doing twice as much work now compared to the period just before I burned out, but I'm also nowhere near a burnout. Part of that is general experience, but it's also because I feel like I know what I'm doing (so, no imposter syndrome) and because I've chosen my job based on what I find meaningful to do (is it ethical? does it make a difference in society? is it interesting?).

I understand why LLM assisted development can lead to burnout. You now have a machine that "does most of the work for you". It's a gateway to questions like "how good are you really at your job?" and "anyone could push these buttons, couldn't they?" and "is this what the rest of my life should be?". It probably also reduces how interesting or fulfilling the job is for many people. You've been reduced to a cog in the machine, and you might be questioning your ability to be anything but.

I am going through this burnout cycle since the COVID-19 days. I noticed that the origin of my burnout is not just due to my job, but also several other factors. Though my job constitutes 80% of it. Within that 80% I noticed that doing a monotonous job contribute to 80% and remaining due to orgn. policies, boss and coworkers.

When I first started using AI agents to automate my work tasks I felt liberated for a few months, but after that I again started feeling burnout. There were days when I tried to compete with AI Agents to complete my tasks earlier like zooming in a race car which added to my burnout.

The quest to learn or gain knowledge will alleviate your burnout and the moment you start unlearning your burnout reappears. Thus I stick to HN for most of the day to kill my burnout though it is overwhelming.

I will never believe the premise of 100x boost from AI, why are we still pushing this narative? Yes, AI is amazing in small, constrained, focused pieces of code but the code is nowhere fit for production and the last 10% needed to ship shows that the 90% that's already been done by AI is absolutely trash. Hacks on top of hacks.

Is no one trying to ship polished things to customers anymore, will each of us have a hacky, bugged version of the same thing with different quirks?

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My first ever software project even before I worked as a swe had less bugs and frictions than all recent projects where AI was used. Some people like mitchellh seem to know what they are doing (I have not taken a look at ghostty's codebase as it's in zig) so I sometimes get the feeling I'm holding it wrong but in the end everyone around me seems to have similar problems with shipping.

It's wild we're seeing people rediscover the same solution to the same problems we've had forever: being precious about your darlings.

Code generators reduced the friction for implementing every shitty idea someone has ever had, but because developers seem to have never experienced throwing shitty ideas away (because if it was written in code it _has_ to be important right?) they treat everything coming out of the Codegen as a precious idea that eventually builds up to clutter one's brain leading to Implementation Fatigue the author experienced. The solution? Go through that same process but focus on one idea at a time and make it good.

It does make me wonder if the people experiencing this had hobbies outside of software engineering (let's say, anything creative) they'd be able to spot the signs earlier.

I'm not sure that AI helps us with that last 1%. Just the 99% which is why, instead of having a backlog of 0% projects, we have a backlog of 99% projects. My hope is that we're more effective prioritizing a backlog of 99% projects than 0% projects.

But AI is only able to get you through those already easy first 90-99%. The hard and most time-consuming part of getting to 100% is still there, and AI does not help or make us more productive achieving that, in my opinion.

The myth you fell into is, assuming that the AI is here to increase your personal productivity. No. Think of AI as a vendor who can provide you with contractors that can code for you. 20 years back, if you are promoted as a manager and approved with a budget to hire 10 contractors, what would you do? You would hire 6 coders, 3 testers and a project manager. Your would mostly interact with the PM giving feature specs, and checking out the progress. You might also ask someone to do the code reviews. You won't sit with every coder and go through the code every day.

AI gives you coders, not some "tool" that you can use to make yourself a faster coder.

Appreciate the quote of the Essentialism book by Greg McKweon, which I am currently reading. Funnily enough I decided the book when I found out (on Imprint app) that one of the key values of the “essentialist” is playfulness. I was sold.

I totally agreed with Rick. A.I is a rabbit hole revealer. And it encourages me to go down them with its "Great Idea" spam.

Edit: Reveler vs Revealer

> Now that AI makes things 2-100x more efficient

What things, why, and how did you measure this?

> I had something like 40 “proof of concept” projects going on

Right. That's the problem. In the non-coding world it's the idea that your pile of crap expands into the available space. So, if you get a garage that is twice as large, it will eventually be just as overloaded and piled-up with crap as the first, smaller, space.

The secret to happiness is to control how much crap you put on your pile. It can be that simple. Or, live with the crap you have and maybe a little bit more, but not 40x more.

"AI speed up your work". Really? How? I still have my 40 hours contract. I still work 40 hours a week.

I launched 1 side project that could potentially help my main project every week, for the last couple of months. To me, it’s not draining at all. I love that the main barrier, time, has been removed. The nagging feeling that I am missing out, did not try, should be working on something, seeing competitors launch my idea. All gone.

I love it. Will any of them succeed? It’s early days, but seeing potentially life changing growth in multiple areas at once gives me a lot of energy.

AI slop.

> So logically, if AI can help us complete tasks 2-100x faster than before, we should be UNDERWORKED and experiencing ZERO burnout, right?

No. you got lied to by AI bros. 100x times the code (that if you burn enough tokens that you could actually hire someone to go thru your ideas and make them...) is not 100x times the productivity

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