How developers use AI for custom software development in 2026?

If you’re paying a software agency in 2026 and you haven’t asked them this question yet, you probably should.
“Are your software developers actually using AI? And if they are… is it more than copy-pasting from ChatGPT?”
Fair concern. We asked our coders the same thing.

THE ANSWERS WILL BLO… just kidding.

But check what today’s coding battlefield looks like in practice, not in marketing materials and LinkedIn posts.

What we actually do vs what people assume

There’s a version of AI use that should make you nervous: a junior developer dumps your requirements into a chatbot, pastes the output, and charges you for the hour. No thinking, expertise or judgment.

That’s not what we do.

The version that makes you smarter as a client: senior developers using AI to compress time, tackle problems they’d previously have to skip due to budget, and ship things they simply couldn’t have shipped two years ago with the limited budget.

Here’s what that looks like in practice.

“It wouldn’t be possible in this budget without AI” – Mikolaj, senior frontend developer

One of our senior developers was dealing with a messy situation.
A major third-party library on which his client’s product depends has released a big update, with significant changes. The client wanted better performance and for some long-standing issues to be fixed.

The problem?
Analysing what changed manually, how it affected our code, and whether proposed fixes would break anything else, would take weeks. At a consultant’s day rate, that’s not a conversation a client wants to have.

So instead, he deployed a team of AI agents:

• One analysed the library’s changelog and source code.
• Another mapped the impact on our codebase.
• Another evaluated proposed changes.
• Then they ran an implementation plan together, with him overseeing and correcting as they worked.

The result?
Real improvements got shipped. The client got value they’d never have paid for otherwise. And the developer was honest about it: “I wouldn’t have taken this on if I had to do it alone. Too risky. No budget for it.”

That’s not AI replacing skill. That’s skill making AI useful.

“I started adding tests client didn’t ask for, but appreciated the stability raising” – anonymous backend developer 🥷

Here’s something that should make you feel good, as a client.

One of our backend developers started adding unit tests (ones that verify that each function does what it is supposed to) to the client project without asking. Not because they’re on the spec, not because they’re being charged for it. Because AI has made writing good tests fast enough that it’s no longer a luxury in the startup world.

Previously, proper test coverage was something clients couldn’t afford. It takes time, it costs money, and the benefits are invisible until the day your product doesn’t break during a major update.

Now? Tests get added to the critical parts of the system quietly, as a matter of professional standard.

When something breaks six months from now because of a dependency update or an edge case nobody thought of, you won’t hear about it. The test will catch it first.

“For 6 months I haven’t written a single line of code from scratch” – Patryk, Full-stack developer

One of our more forward-thinking developers has built his own workflow that looks a bit like a small company running inside one person.

It goes something like this:

• A task comes in from the project management tool.
• An AI planning agent reads the brief, maps what’s needed, and asks clarifying questions before anything gets built.
• That plan gets handed to a group of specialised AI models working together, each with a different role.
• Once the work is done, an automated testing agent (using real browser interactions, not just code checks) verifies the results. If it catches a bug, a correction session runs automatically.
• A polished pull request gets created on GitHub, better documented than most humans would bother to write.

This developer hasn’t written a single line of code from scratch in about 6 months. That statement would have sounded alarming in 2023. Now it just means the code is faster, better tested, and more consistent than before.

The time he used to spend on the mechanical parts of writing code, he now spends on the decisions that actually require a brain.

Of course, for the record, it doesn’t always work perfectly, but we are going in that direction.

So is your agency using AI for coding?

That’s the wrong question.

The right question is: “Are you getting output that would have been impossible, or unaffordably expensive, two years ago?”

Better performance. More test coverage. Faster delivery. Richer documentation. Features that previously lived in the “someday if budget allows” column.

AI doesn’t change what a good developer does. Value delivery is still the priority. But it changes how much can be achieved faster and more stably.

We use it.
We use it seriously.
And it’s not about copying code from ChatGPT instead of StackOverflow.
There is slightly more ✌️