If you’re reading this, you’ve already felt the vibe shift.

Everyone can “build” now. Nobody can maintain. And hiring feels like speed-dating inside a hurricane, except the hurricane has a KPI dashboard and HR is asking if you “use agents” like that’s the sacred question that separates real engineers from scammers.

Spoiler: it isn’t. It never was. HR was clueless before. Now they’re clueless with more filters.

Let’s talk plainly about what the AI wave is actually doing to the developer job market, and how not to get chewed up without turning into a buzzword vending machine.

The ugly but useful truth is this: the market won’t pay more for “more developers.” It’ll pay more for fewer developers who can carry weight.

Not because “coding is dead.” Coding is fine. It’s everywhere. It’s multiplying like rabbits.

What’s changing is trust.

When output gets cheap, companies stop paying for output. They pay for the person who can touch production without turning it into a crime scene.

Primeagen’s take goes like this: “we’ll need more developers because we’ll have to rewrite everything for generative LLMs.” Clean logic. I buy the logic. I don’t buy the calendar.

Most companies don’t reorganize because someone made a smart argument. They reorganize when they take a hit. Like a production incident that costs real money, real customers, and a Zoom call full of gray faces.

Right now we’re in the feature-confetti phase. AI makes it ridiculously easy to ship stuff, so companies do what companies always do: ship. brag. ship again. brag louder. Meanwhile, under the hood, you’re stacking trash, but with incredible confidence.

Then the bill shows up.

And the bill usually isn’t “the code is ugly.” The bill is sneakier: business logic smeared across the repo, patterns changing every three files, duplication everywhere, performance falling off a cliff when traffic grows, tests that don’t test, and a deploy pipeline that has developed a personality disorder.

That’s when hiring changes. Not bigger. Sharper. Meaner.

Less “can you build a CRUD app in a weekend.” More “can you stop the bleeding without breaking payroll, payments, and customer data.”

That’s the real shift. AI isn’t replacing developers. It’s replacing the thing that used to be a proxy for competence: producing code.

Now the proxy is different. The question is: can we trust you on the money path, the data path, the uptime path?

And that’s why your resume might suddenly feel… useless.

Old signals are getting noisier. When anyone can generate a decent-looking project and a confident README, recruiters get flooded with “proof.” So HR and hiring managers (the good ones, anyway) start filtering for things that are hard to fake: real ownership, real scars, real “I was there when it broke” experience.

That’s why you’re seeing experience inflation. “5+ years” for roles that used to be “2+.” Not because companies got wiser overnight. Because they’re trying to reduce risk using the laziest lever they have: raise the requirement on paper and hope it works.

When output becomes abundant, buyers pay for risk reduction. Software isn’t special. It just fails louder and leaves better logs.

The funny part is how predictable the distortion is.

The top of the funnel is packed because AI makes demos cheap. Founders ship prototypes. Marketers ship prototypes. Your friend’s 16-year-old cousin ships a prototype with a landing page, a pricing page, and a “Request Access” button. The button does nothing, but the vibes are immaculate.

This doesn’t replace you. It changes what “impressive” looks like.

In 2019, “I built a full-stack app” was a flex.

In 2026, “I built a full-stack app” is a Tuesday.

The flex now is: “I shipped it, kept it alive, made releases boring, and the graphs stopped looking like an EKG.”

Here’s the movie version, because it sticks.

Scene: 2026. Everyone is shipping. Your competitor clones your feature before your coffee cools down. Investors clap. Product chants “more!” Engineering pretends it’s fine. Production is quietly preparing revenge.

The problem isn’t that LLMs write bad code. Sometimes they write great code.

The problem is they make it easy to produce unowned code. Code nobody truly understands. Code nobody can explain. Code nobody feels responsible for when it blows up at 3 a.m.

That’s why “rewrite everything for LLMs” is the wrong framing. You won’t rewrite everything. You’ll rewrite how you build software, otherwise LLM output turns your codebase into a chaos museum with a tour guide.

You’ll need stricter reviews, clearer boundaries, real tests, decent observability, and fewer merges that happen because “the diff looked confident.”

AI doesn’t remove discipline. It removes the pain that used to force discipline. Then the pain comes back as downtime.

So, when the correction hits, who do companies panic-hire?

Not “people who can prompt.”

They hire the person who can control the system. The one who can set constraints, enforce quality, trace logic, and restore velocity without setting the whole repo on fire. The one who doesn’t just fix the incident, but makes it less likely to happen again tomorrow.

Now the practical part: how do you position yourself without becoming an “AI-first” parrot?

First: stop selling yourself as “fast.”

Everyone is fast now. Even people who don’t understand what they’re doing. Especially people who don’t understand what they’re doing.

Sell yourself as safe.

That doesn’t mean slow. It means you can move quickly without producing surprises. It means you can change production and still sleep. That’s the currency.

If you want a quick test, imagine a hiring manager thinking, quietly, “please don’t be another person who leaves me a mess.”

Answer that fear.

Talk about real outcomes. Incidents reduced. Latency improved. Build times cut. Deploys made boring. Security issues avoided. Legacy modules cleaned up without breaking customers. Not glamorous. Extremely valuable.

And show you can read code, not just write it.

The real nightmare of 2026 is a codebase that looks productive and behaves haunted. If you can walk in, understand it, simplify it, and leave it better than you found it, you’re already above average. Way above.

And yes, use AI. Like an adult.

“I use it to draft. Then I verify with tests, benchmarks, and review.”

That’s it. No prophecies. No superpowers. No “prompt engineering” cosplay.

Now the two uncomfortable questions.

Will AI reduce entry-level roles? It can, especially where the job was basically “take ticket, write code, close ticket.” But it also opens a different path: juniors who can test, triage, maintain, and improve system health become more valuable. If you’re junior, market yourself as someone who reduces risk and learns fast, then prove it with small but real contributions.

Will companies hire fewer people? Some will. Others will hire differently. Fewer roles that tolerate shallow understanding. More roles that demand ownership. Fewer seats, more weight per seat.

One exception: if you’re building throwaway prototypes to validate ideas, speed is the whole point. In that world, “vibe coding” is fine.

The problem is prototypes have a nasty habit of becoming products. And then maintenance shows up like rent. You can ignore it for a bit, but it doesn’t forget your address.

So keep this sentence and throw the rest away if you want:

AI won’t create a magical surplus of developer jobs. It’ll create a surplus of output, and then a premium for developers who can keep systems stable, understandable, and profitable.

If you want one concrete move: pick a domain where failure is expensive. Reliability. Security. Performance. Data correctness. Payments. Infrastructure. Then build proof you can own it in production. Not in a demo. In production.

Because when the correction phase hits, job posts won’t say, “please save us from our own velocity.” But that’s what they’ll mean.