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How to find an AI-native developer (and not make a mistake)

Understanding who AI-native engineers are, why the old hiring approach no longer works, and what signals to look for when choosing a candidate.

Authors: slavb18

AI-native Developer Roadmap 1

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Everyone is currently looking for "strong developers".

But the problem is that the market has already split into 2 types:

  1. Regular engineers

  2. AI-native engineers, who accomplish 5-10x more

And if you hire using old criteria - you are almost guaranteed to hire the first type.


💥 Why standard hiring breaks down

You look at:

  • stack (React, Python, PostgreSQL)

  • years of experience

  • past companies

But this says nothing about real effectiveness.

Two candidates might look identical. But one will take 2 weeks to build a feature, while the other will put together the entire product over a weekend.


🧠 What distinguishes an AI-native developer

We currently systematically analyze candidate experience and identify AI Insights - signals of how a person truly works.

Here's what to look for:


🔹 1. Using AI as a multiplier

Not "tried ChatGPT", but:

  • Cursor / Claude / Copilot in daily work

  • code, test, architecture generation

  • working through agents

👉 If this is missing - they are not AI-native


🔹 2. Speed (the most underrated signal)

Look for phrases like:

  • "built an MVP in 2 weeks"

  • "did 5+ experiments a week"

  • "launched a product in a month"

👉 speed is the main marker


🔹 3. Product thinking

An AI-native engineer:

  • talks about churn / retention / conversion

  • and not just "implemented an API"

  • participates in product decisions


🔹 4. End-to-end thinking

Not "I built the backend", but:

  • "built a feature from idea to production"

  • "launched and measured the result"


🔹 5. Automation-first approach

  • automates routine tasks

  • writes scripts / pipelines

  • reduces manual work


⚙️ How we do this

We break down each candidate's experience into a structure:

  • stack → all technologies (including AI tools)

  • skills → real practices (product, architecture, processes)

  • achievements → measurable results

  • and most importantly → AI Insights with explanation

For example:

AI-native - uses Cursor and Claude for significant development acceleration

MVP Builder - built a product in 2 weeks

Product Engineer - reduced churn by 20%


📊 What this provides

You start to see the difference:

  • not "React vs React"

  • but

  • a regular developer vs a person who genuinely builds products


⚡ The market's main mistake

Companies are still hiring based on:

❌ "5 years of experience"

❌ "stack knowledge"

Instead of:

✅ "product creation speed"

✅ "ability to work with AI"

✅ "focus on results"


🎯 In short

An AI-native developer isn't about tools

it's about behavior and speed


👇 If you want to try

We've created a simple scenario:

  • upload your resume or job description

  • get AI Insights on candidates

  • immediately see who is truly strong

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