AI in Web Development | This changes everything

Today we’re talking about AI in Web Development — ‘This Changes Everything’. In the last 18 months we’ve gone from autocomplete to agents that plan, code, run, test, and fix—across any stack. Surveys show most devs now use AI tools, but trust is mixed—so human-in-the-loop is the edge. And yes, the solo-builder wave is very real: platforms like Replit hit a $3B valuation and are projecting massive growth on the back of ‘vibe coding.’ We’re early—but the curve is steep. Let’s break it down in 10 points you can apply this week.”

1. Your 24/7 “average engineer” across every stack.

You now have a decent generalist sitting next to you—all day—who speaks every major language.

AI assistants cover frontend, backend, infra, tests, Database migrations, Docker, and CI. In controlled field studies, Copilot-style tools show meaningful productivity gains—not magic, but enough to rewire your day. I treat AI like a mid-level pair who works fast but still needs review.

2. Full-stack acceleration & painless context-switching.

Porting snippets from Python to Node, writing Terraform from a diagram, or drafting a Prisma schema—minutes instead of hours.

The win isn’t just speed, it’s context switching without losing flow.

As a freelance web developer, I work on multiple CMSs that have their own particularities and some even their own language.

It's so helpful for using the right syntax for what you need instead of wasting hours researching it, and keeping up with the latest changes.

3. From copilots to agents (the next leap).

Agentic AI is the shift from a ‘tool that suggests’ to a virtual coworker that can plan → code → run → test → iterate.

Enterprises are piloting these loops right now.

And as Sam Altman, CEO of OpenAI, said, "This is the stupidest model we will have" meaning that things are only going to get better from now.

I've used only prompts for a side project and I rarely needed to jump in and code. Don't get me wrong, it was not like I said build this app and it did it magically.

I had to prepare the plan, guide it, and intervene on what approach it should use, and many other things. I was doing medium-sized steps and it did just fine. Of course it got stuck and I got involved in debugging but it was still good and faster than I would have done it.

Could I have done a better technical job? Yes, of course but I don't need an enterprise-grade code quality for a side project.

I need it done as fast as possible so I can test it with real world customers.

4. Vibe coding & the rise of solo builders.

In 2023 I said AI would be great for devs—and it is. Vibe coding means describing what you want and steering. Even non-technical folks can ship simple apps. Proof the wave is real: Replit’s $3B valuation and explosive growth tied to agentic building.

I've even seen medium-sized companies jump off traditional Content Management Systems like Squarespace and Webflow to Lovable for their simple websites.

5. Juniors aren’t obsolete—verification is the new superpower.

Juniors + AI > juniors without AI. But the winners validate: write tests, run linters, ask ‘why,’ and learn. Studies show uplift with oversight—so juniors who verify become force multipliers.

I think juniors are the ones who should know how to leverage AI the most. But they should also improve their technical skills so they know what the AI has outputted and stear the AI better.

6. Adoption is high; trust is… complicated

Most developers now use AI tools, but trust lags—only a minority say outputs are reliably accurate.

That’s why human review and tests stay non-negotiable.

Like I said in the previous points.

AI is not doing everything in coding; it still needs developers to supervise.

And don't expect the coding copilots to code a long task as their core; the AI models aren't yet good at doing long-term tasks.

Prepare the steps and sometimes even break them into smaller ones, and do them ideally one at a time.

7. Goodbye doc-dredging for edge cases.

We’ve all lost evenings to outdated docs.

Now I ask AI for current examples, then I prove them with quick scripts and tests. The result: edge-case resolution in minutes, not hours.

One experience I can tell you about, with AI agents coding, was when the agent was stuck, and even with multiple iterations, it didn't solve the error.

As an experienced developer, I suspected that something was not right, as the task was not that complicated.

So I pointed him to the latest docs and it figured it out and used the latest approach.

Another time with an open source project, it was again stuck and I pointed him to the source code of the plugin, and he figured it out.

8. Company strategy: don’t fire—upskill

Some companies overreact, cutting engineers instead of retooling them.

Research this year highlights the gap: many firms adopt gen-AI but struggle to capture value—skills and process are the choke point.

Teams that keep engineers and train them to wield AI win.

Am I thinking companies exaggerate by firing software engineers and don't hire as many? Yes, I do.

You still need humans in the loop, and if you're firing and not allowing those people to leverage AI, you will lose to the companies that don't fire but hire and train people how to leverage AI.

Google's CEO, Sundar, shares the same philosophy. |

In an interview, he said that Google's engineers have become 10% more productive, and they will just do more things, so he is not thinking about firing.

9. New career math: side hustles → micro-SaaS → unicorns

With AI and agents, you can go from a side hustle to a micro-SaaS, and maybe even to a unicorn, faster than ever before.

Why? Because the heavy lifting is now shared with AI.

Prototyping that used to take a few weeks, now takes a few hours.

You can design, build, test, deploy — even integrate payments or analytics — in a single weekend.

And because developers are better positioned on the software topic they can take advantage the most in this.

10. "This changes everything,”—and we’re early

To quote Larry Ellison: ‘AI changes everything.’ Whether you’re team Oracle or not, the signal from leaders is the same: this is a platform shift.

We’ve essentially built a non-biological, digital intelligence that pairs with us. The winners will be the teams—and the solo builders—who learn to drive and guide it.