AI Can Make You Suck Faster Too

Not too long ago, I shared a post that I really liked by Disesdi Shoshana Cox. They went through the math of how many revolutionary tech companies we should have by now thanks to AI. With a 10x improvement on development speed, the technical aspects of launching an app are no longer a limit to reaching a target market. It seems like AI has finally provided the silver bullet that solves the problem of programmers moving so slowly.

Borrowing Disesdi's logic in their arithmetic (which is hard to argue against), after four years of open source LLMs, we should have three AirBnBs,¹ two Stripes,² and three Dropboxes³ thanks to the power of AI.

So. Where the fuck are they?

The biggest new tech companies in the world since the advent of GenAI are, well, GenAI companies. OpenAI, Anthropic, and High-Flyer (developer of DeepSeek) are being valued at record-breaking sums of money. But the biggest disruptions they're causing is to the global economy. The most noticeable contribution to society from GenAI is making poorly worded emails the norm, flooding social media with garbage, and ruining the quality of internet search engines.

Or else admit this is a dopamine game that makes you feel like The Universe's Most Special Programmer™️ when it's really just gamified mass-scale intellectual dependency.

Disesdi Shoshana Cox

Disesdi's post struck a chord with me because I've witness the same underwhelming output of software during this AI rage. These tools, in the hands of non-technical people who have not put in the time and effort to learn about the nerdy stuff, are simply not able to generate working apps that will persist and be security-hardened against run-of-the-mill attacks. And when experienced software engineers use them, the impact feels like a limp handshake.

The massive blindspot here is that writing lines of code isn't the part of software development that drains the most time. This may seem like I'm contradicting myself on the argument that we should have at least a handful of AirBnBs or Dropboxes by now. But there isn't a contradiction because leaders of companies and startups truly believe that LLMs have solved the bottlenecks in product delivery. It's the perception that all technical issues in software development no longer exist because you can "just get Claude to do it".⁴

I recently attended a tech conference where there was a panel discussion on the main stage that was titled something like "No code, No problem". The panel comprised four startup founders who vibe coded their way through MVP and, assumedly, are taking money from customers.⁵ The moment that made me walk out of the session was when one of the founders said he didn't have, and won't ever need, a CTO because he can just use Claude to solve his technical problems.

Imagine that. You don't need software expertise in your software company. You don't need a structural engineer to design the structure of an office building. You don't need a surgeon to perform surgery.

I. An Experiment

I've been told by people who are much, much better developers than I am that they've sped up their productivity in writing software by using Claude and other coding agents. So I thought, what the heck? When you run a consultancy, you can actually convert that type of development speed into money! I had already used a few different AI agents to help write the boring stuff - boilerplate code, repetitive SQL, etc. But I wanted to see if I can get in on this 10x magic. I decided to put my money where my mouth was and I bought $10 worth of DeepSeek credits to use with a project I was working on.⁶

The process was incredibly infuriating. The chatbot recommended some of the dumbest shit you could possibly do. And let's be clear here: the code DeepSeek wrote would run, but it was a clown car rolling around with wheels held on by duct tape. Now, you might be thinking, "Well this fucking guy doesn't know how to prompt. If he was just better at prompting, he wouldn't suck so much." And you might be right. But I've also shipped a product before, which is infinitely more than most people accomplish in their entire engineering career. So maybe I do suck at prompting. Or maybe something else sucks.

II. Today's Sad Reality

Until very, very recently, the way you would find the answer to something you didn't know was by Googling it, reading a bunch of different opinions, and filtering and combining those thoughts to generate your own position. And before Googling was the go-to method for finding the answer to something, you'd have to travel to a monstrous building full of dusty humans so you can search, aisle by aisle, for the right collection of tomes that each contained a portion of the thing you wanted to understand better (I like to call it "doing it in the stacks" whenever I visit a library). That's all been replaced with a text war between you and a robot that spews whatever shit some asshole on Reddit posts. Just take a second to digest this stat!!!:

Reddit outranks financial experts 176% of the time when ChatGPT answers finance questions, despite YMYL guidelines prioritizing authoritative sources.

Carlos Silva, writer for Semrush

Too many people don't think for themselves enough in this post-GenAI world. The curiosity hasn't left us - which is very encouraging - but instead of thinking critically about a problem or question, there's an app for that. The issue is that the "app for that" can't reason. Its source of information is a range of differing opinions mostly from non-experts that aren't verified for legitimacy.

There used to be a barrier to entry into skilled domains - which was a good thing.

For instance, would you ever do the electrical wiring for your own home? Well, why not? You can get a step-by-step guide on your phone while staring at your switch board (that is, if ChatGPT recommended starting at the switch board). The chatbot can probably look up ways to connect your lights to one circuit and your oven to another. You may even learn how to spread parts of your home across different breakers to balance load.

But what if you make a mistake? What are the consequences? Maybe an electrical fire in the middle of the night, or maybe you electrocute yourself before that happens. The obvious, and potentially catastrophic, consequences are probably enough for most of us non-electricians to hire an expert. So why isn't the same logic used when building software? Most apps these days gather credit card details and enough personal identifiable information to ruin someone's life if it gets leaked to the wrong person. All it takes is some bored 16-year-old with an internet connection somewhere on this planet to infiltrate a poorly guarded production database. The outcome won't be as cinematic as a house fire, but your life can be completely fucked by careless software design. On top of that, people who are new to software development aren't the only ones who have access to these chatbots. If you really believe in this 10x effect of AI on productivity, imagine how it's going for hackers.

It's the same idea when it comes to vibe coding an app, charging people for it, and collecting sensitive data. Except you're not gambling whether your amateur electrical work will burn down your house. Instead, you're gambling with other people's money (from VCs or your customers), privacy (anyone who's trusted you with their data by using your app), and livelihood (every single person you've hired in your company).

III. The Wizard of Oz

I think the path to how much trust we put into GenAI was paved with "good enough" information that these AI chatbots provided. These LLMs curate a vast amount of information in seconds about topics the user has no idea about. The chat box and conversational feel has replaced the painstaking process of doing it yourself. (As an aside, it's incredibly hilarious that Googling something has become a pain point. A microsecond-in-human-history ago, you would visit a library and look through physical cards containing codes for books that might have the information you were after and you would read them solely based on the title. But I digress...) The real problem here is the blind trust our society has placed on AI tools like ChatGPT.

You can only start pulling back the curtain to see what's on the other side when you're familiar with the subject you're asking the chatbot about. For software engineers, it's when the AI recommends putting your web app, database, and background processes all on the same server.⁷ For running coaches, it's when ChatGPT tells you to include 40-metre sprint training in a beginner marathon program. And for literally anyone, it's when you're encouraged to put ant poison in your sandwich. Some AI hallucinations are funny, but others can be damning if they're just believable enough not to be questioned.

The tech industry needs to become (more?) responsible (again?). It needs to hire, work with, and learn from experts. GenAI can be incredibly helpful with pulling a wonderful idea out of your head and giving it life. But that thing is closer to a Homunculus from Full Metal Alchemist than anything actually living. An idea needs to be nourished so it has time to develop into a something great. If it isn't, the results are ugly and can be extremely dangerous.

AI will make you faster at shoveling shit if you only know how to shovel shit.