♟️ The Metagame #046: The Double-Edged Sword of AI

Welcome back to today's edition of The Metagame.

Before we get into it, a quick plug:

I've been building BetterBets—an AI-powered NBA prediction agent that delivers daily player points picks to Discord. If you're interested in data pipeline automation, cloud architecture, or building with AI agents, I share my tips and technical details on Twitter/𝕏. And if you just want the picks, the Discord is open.

Speaking of AI—let's get into it.

Read time: 5 minutes

A few years ago, if you wanted to build an app, you needed to be a developer.

You needed to understand frontend frameworks, backend architecture, databases, authentication, deployment pipelines, and about a hundred other things that would make any normal person's head spin.

Today? You can describe what you want in plain English and watch it materialize in front of you.

I'm not exaggerating.

I've seen people with zero coding experience ship functional products in a weekend.

This is either the greatest democratization of technology in human history or the beginning of a very messy chapter. Probably both.

The Case For AI Coding

Let me start with the positives, because they're genuinely transformative.

Speed

The most obvious benefit is velocity. Tasks that used to take hours now take minutes. I can scaffold an entire application, write tests, debug issues, and refactor code in a fraction of the time it used to take.

When I was building my iOS app OneHome, I hit a particularly challenging issue with enabling logins with Google and Apple accounts. In the old world, I would have spent half a day digging through Stack Overflow and Apple's documentation. With AI, I described the problem, got three potential solutions, and had it fixed in twenty minutes.

This isn't just convenience. It's a fundamental shift in what's possible for individual creators.

Automation

Beyond just writing code faster, AI unlocks automation workflows that were previously out of reach for solo developers.

I have agents that monitor my data pipelines, generate daily reports, and flag anomalies before they become problems. Setting up these systems used to require dedicated DevOps engineers.

Now it's a conversation.

The barrier between "I wish I could automate this" and actually automating it has essentially disappeared.

Full-Stack Creation

Here's the big one: AI lets you become a full-stack creator.

I'm primarily a backend developer. Frontend has always been my weakness. But with AI assistance, I can build polished UIs and websites that don't look like they were designed by a college freshman in their "Intro to Web Design" course.

The traditional boundaries—frontend vs. backend, mobile vs. web, design vs. development—are dissolving. One person can now do the work that used to require a team.

This is incredibly empowering.

It means more ideas can come to life. More problems can be solved. More people can participate in building the digital future.

However...

The Case Against AI Coding

There's a darker side to this revolution, and we need to talk about it.

The Laziness Trap

When AI can write code for you, there's a temptation to stop learning.

Why understand how a sorting algorithm works when you can just ask for one? Why learn the fundamentals of database design when AI handles your queries?

This creates a dangerous dependency. You become a prompter, not a programmer. And when something breaks in a way that AI can't immediately fix—and it will—you're stuck.

I've caught myself falling into this trap. There have been moments when I accepted AI-generated code without truly understanding what it was doing. That's a habit I've had to actively fight against.

The best developers using AI are the ones who already know how to code. They use AI as an amplifier, not a replacement. They can evaluate AI suggestions critically because they understand the underlying principles.

If you skip the fundamentals, you're building on sand.

The Understanding Gap

This leads to a more systemic problem: a growing population of people shipping code they don't understand.

When you don't understand your code, three things happen:

First, you give poor direction. You can't effectively guide AI toward what you actually need because you don't know what questions to ask or how to evaluate the answers.

Second, you introduce security vulnerabilities. AI models are trained on vast amounts of code, including insecure code. Without the knowledge to spot issues like SQL injection, XSS attacks, or improper authentication, you're essentially deploying ticking time bombs.

Third, you create what everyone is calling "AI slop"—code that technically works but is poorly structured, inefficient, and unmaintainable. It's the digital equivalent of fast food: it satisfies the immediate craving but leaves you worse off in the long run.

The Money Grab Epidemic

Finally, there's the economic reality of lowered barriers to entry.

When anyone can build an app, everyone tries to build an app.

The result is a flood of low-quality products, half-baked SaaS tools, and shameless cash grabs. App stores are being overwhelmed with AI-generated clones. Product Hunt is saturated with "AI-powered" everything, most of which adds no real value.

This makes it harder for genuinely good products to stand out. It erodes user trust. And it creates a race to the bottom where speed matters more than quality.

We're seeing the same pattern that happened with content mills and SEO spam, but now applied to software development. The platforms haven't figured out how to filter for quality yet, and users are paying the price.

So where does this leave us?

I'm not a doomer about AI coding. I use it every day, and it's made me significantly more productive.

But I think we need to be honest about the tradeoffs.

The developers who will thrive are the ones who treat AI as a tool, not a crutch. Who invest in understanding fundamentals even when they don't have to. Who review AI-generated code with the same scrutiny they'd apply to a junior developer's pull request.

The products that will succeed are the ones built by people who actually care about quality, security, and user experience—not just shipping fast.

And the ecosystem will only stay healthy if we collectively push back against the tide of AI slop and hold ourselves to higher standards.

The democratization of coding is real. What we do with it is up to us.

Here's a quote that's been stuck in my head lately:

Thanks for reading!

If you have any questions, hit me up on LinkedIn or on Twitter/𝕏 at @sam_starkman, or feel free to reply to this email!

— Sam