The Next 10X Engineer
The best engineers now write less code, and this whitepaper shows how to tell them apart from everyone else. Its fourteen pages cover what the job is now, what AI-native means, why the old hiring process stopped working, and both scorecards in full.
Last week I interviewed a developer with 13 years of experience. His CV looked good and the first assessment went well. Then I let him use coding agents.
From that point on he stopped reading. Every change got accepted, every prompt got a "go ahead", and he closed tickets without checking any of them. Most companies would have hired him. We would have too, two years ago.
Three engineers on the same backlog
For as long as anyone has been in this industry, the 10X engineer was the one who closed the most tickets and shipped the most lines of code. If you put three engineers on the same backlog today and watch them for a morning, that definition stops holding.
Doesn't use AI
A good engineer who reads everything and writes all the code by hand.
One agent, one window
Works in a loop of prompting, waiting, reading the result and prompting again.
Four worktrees, an agent in each
One agent works on a feature, one on a bug, one reviews a PR and one writes end-to-end tests. The engineer moves between them and checks what each one produced.
By lunch the third has done what the first will finish on Thursday. AI has also made some engineers worse, because the second produces more than two years ago and sometimes understands less of it.
Lines of code are cheap now
Tickets become a plan, the plan becomes pieces small enough that each PR is readable in one sitting, and the pieces go to agents in parallel. An agent builds whatever you give it, so a gap in the input shows up in the output within the hour.
Unclear requirement?
The agent still generates something, and it's confident and plausible but built on a guess.
Missing context?
The agent makes assumptions about your system, and they're usually the wrong ones.
Weak tests?
Generated code passes them and quietly breaks the behaviour they never covered.
A definition, and what it isn't
The fundamentals come first in that sentence for a reason. If you can't reason about the system without the agent, you can't tell when the agent is wrong.
An AI-native engineer is a full-stack developer with solid fundamentals in code quality, systems design and security, who directs coding agents on how to produce output and validates that output before it ships.
It isn't an AI engineer
An AI engineer builds AI: models, pipelines, retrieval, evaluation, the plumbing around a language model. That's a specialist skill and a different role.
We place those tooIt isn't a prompter
A prompter uses an agent the way you'd use a search box. One window, one request at a time, accept and on to the next prompt.
Why we replaced the old hiring process
Every take-home looks the same because every take-home is model-written, and LeetCode-style tests measure pattern recall under a clock. Neither shows the fundamentals or the agent skills, so we replaced both with two sixty-minute assessments in a real codebase, one with AI tools off and one with the candidate's own agents on.
Assessment 1 · AI tools off
The fundamentals assessment
The engineer gets a codebase they haven't seen, a handful of tickets including one production bug, and sixty minutes to work through them. It runs like a normal working session, with no AI tools allowed.
- Communication
- English level
- Prioritisation
- Debugging
- Context-switch hygiene
- Technical understanding
Assessment 2 · AI tools on
The AI-native assessment
The engineer gets a fresh set of tickets in the same kind of codebase, plus whatever AI coding tools they'd normally use. The assessment shows what they do when an agent is doing most of the work: whether they plan first, whether they read what comes back, and whether they can explain a change they didn't type.
- AI output verification
- Tool orchestration
- Spec-driven development
- Prompt and context engineering
- AI-accelerated debugging
- Context-switch hygiene
And three that don't fit on a card
Judgement by risk
A copy change, a low-risk refactor and a payment migration shouldn't get the same review. Good engineers speed up on the first and slow right down on the third. Agents produce all three at the same speed and with the same confidence.
Ownership
If you merge it, you own it. Tests, observability, rollout and the debugging after release are part of the work whether a person or an agent wrote the code.
Leverage
The best engineers finish the ticket and leave the repo better set up for the next agent: a reusable command, a tighter CLAUDE.md, a test that catches the class of bug rather than the instance.
Change your own hiring process, or use ours
If you're still filtering on take-homes and coding tests, the developer from the introduction is getting through your interviews. The two scorecards are a reasonable place to start.
Every engineer we place has been through both assessments, with both scorecards filled in. You send a brief, we send a shortlist in five working days, and the first commit usually lands about three weeks after that.
Short answers
Our other whitepaper is for product leaders turning an AI mandate into a way of working.
From AI Mandate to AI StrategyIs an AI-native engineer the same as an AI engineer?
No. An AI-native engineer builds products using AI tools. An AI engineer builds and operates the models: fine-tuning, evaluation, retrieval, serving.
Is a 10X engineer someone who writes ten times more code?
Not any more, because lines of code are cheap. The engineer who multiplies a team now turns a vague ticket into a shipped change they can vouch for, and uses agents to speed up the part that used to be typing.
What is the difference between an AI-native engineer and a prompter?
A prompter uses an agent like a search box: one window, one request at a time, accepting each answer. An AI-native engineer plans the work, runs agents in parallel and validates every change before it ships.
How much does an AI-native engineer cost?
It's €5,600 to €8,000 a month per full-time engineer, with employment and compliance included and no recruitment fee. The pricing calculator compares it with a local hire in your country.
Engineers vetted for how the job works now
Every engineer we place has been through both assessments, with both scorecards filled in. You send a brief and get a shortlist in five working days.
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