Jake Goldsborough

Like a Pig in Shit: Why I Love AI "Slop"

Published November 8, 2025

6 min read

Tags: ai, dev, opinion

I've shipped more projects in the last three months than I did in the previous year. Are they all perfect? No. Are they all polished production-grade code? Hell no. Do I care? Not even a little bit.

I'm having the time of my life building whatever idea pops into my head, and AI is the reason I can actually finish things instead of just thinking about them.

And look, shipping isn't everything. Sometimes the best code never sees the light of day. Sometimes you build something just to learn, or just because it sounds fun. But there's something deeply satisfying about making things that actually work - even if they're just for you.

What I've Been Building

In the last few months alone:

Some of these are polished. Some are "good enough for me." All of them work. All of them solve real problems I had. And I built most of them in a day or two.

The "Slop" Criticism

There's this narrative that AI-generated code is "slop." Low quality, generic, copy-pasted garbage that's polluting the internet. And sure, that exists. That existed before AI when people would blindly copy from Stack Overflow. But the criticism misses something important:

When you're building for yourself, "slop" doesn't matter.

I'm not pushing half-baked code to production systems. I'm not claiming my afternoon projects are enterprise-ready. I'm building tools that solve my problems, learning by doing, and having fun.

If the markdown preview plugin has rough edges, who cares? It works for me. If the presentation tool doesn't handle every edge case, so what? It renders my slides.

The "slop" criticism only matters when you're shipping garbage and calling it gold. When you're building for yourself? Ship it, iterate, move on.

What's Actually Happening

Here's what working with AI looks like for me:

I have an idea. "I want to do presentations in Neovim." Instead of spending a week researching markdown parsers and figlet integration and buffer management, I describe what I want and start building.

The AI suggests approaches. Some work. Some don't. We iterate. I learn what Treesitter can do. I understand how Neovim's highlight system works. I see patterns I wouldn't have thought of.

A few hours later, I have a working plugin.

Is it perfect? No. Did I learn a ton? Yes. Can I actually use it? Absolutely.

The Joy of Building

What the critics miss is how much fun this is.

I used to have a backlog of ideas that never got built. "Someday I'll make that." "That would be cool but it's too much work." "I don't have time to learn X framework."

Now? I just build it.

Want to visualize invite relationships as an ASCII tree? Build it. Want live transit departures in a forum? Build it. Want to fix a bug in a YAML parser? Build it and submit the fix upstream.

The barrier between "I wish this existed" and "I built this" has collapsed. And that's incredible.

But Is It Actually Good Code?

Sometimes yes, sometimes no. And that's fine.

The Ruby psych-pure bug fix I submitted? That's good code. Full test coverage, proper edge case handling, clean implementation. It's going into a production library.

The transit tracker? It works, handles 500k+ MTA stop times, and has solid patterns for data downloading and parsing. Could the UI be more polished? Sure. But it does what I need and I learned a ton building it.

The key is knowing the difference. When it matters, I put in the work. When it's just for me, I ship it and move on.

The Real Productivity Hack

Working with AI isn't about replacing thinking. It's about spending your brain cycles on the interesting problems instead of the boring setup work.

I don't want to spend three hours setting up test infrastructure. I want to spend three hours solving the actual problem. AI handles the grunt work. I handle the decisions.

You Can Vibe and Still Be Productive

Here's the thing: you can have fun, move fast, and still produce quality work. It's not either/or.

I'm "vibing out" projects. Building whatever sounds interesting. Shipping fast. And yet:

You can be a pig in shit and still do good work. The slop is the medium, not the output.

The Gatekeeping Problem

A lot of the "AI slop" criticism is just gatekeeping in disguise.

"Real programmers don't use AI." "You're not actually learning." "This is ruining software quality."

Meanwhile, I'm shipping. Learning by building. Contributing to open source. Having fun.

The gatekeepers can argue about the "right way" to write code. I'm too busy building things.

What Actually Matters

At the end of the day, here's what matters:

If the answer to those three questions is yes, then it doesn't matter if someone on Twitter thinks your code is "slop."

You're building. They're complaining. You win.

Like a Pig in Shit

So yeah, I'm rolling around in the AI slop. Building projects at a pace I never could before. Shipping tools that solve real problems. Learning by doing instead of just reading about it. Old me would think I was full of shit if I tried explaining this.

Call it slop if you want. I'm too busy having the time of my life to care.

The pig pen is the place for me.

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