TLDR
AI coding tools have made it trivial to generate impressive GitHub profiles. Green squares and clean repositories no longer prove competence. Recruiters need a new signal: Verified Experience — proof that a person understands what they built, not just that code exists.
For the better part of a decade, the GitHub profile served as the unofficial CV for software engineers. Green contribution squares, pinned repositories, and open source commits told a story that traditional resumes could not. Recruiters learned to read them. Candidates learned to cultivate them. It was an imperfect but useful signal of competence.
That signal is now dead. AI has killed it.
The Signal That Was
The GitHub profile worked as a recruitment tool because writing code was hard. A repository full of well-structured projects, meaningful commit messages, and active contributions told a recruiter that this person could build things. The barrier to producing a credible GitHub profile was the ability to actually write software. That barrier no longer exists.
When producing code required genuine skill, a strong GitHub profile was a reliable indicator of that skill. The cost of faking it was high enough that few bothered. The correlation between a good profile and a competent engineer was strong enough to be useful. Recruiters could scan a candidate's repositories and make a reasonable inference about their ability.
That inference is no longer reasonable.
AI Has Flooded The Signal
Today, anyone with access to an AI coding assistant can generate repositories full of functional code in hours. Complete applications, well-commented functions, clean architecture. The output is often indistinguishable from code written by competent engineers. In many cases it is better structured, because the AI has been trained on millions of examples of best practices.
A person with no understanding of software engineering can now produce a GitHub profile that looks identical to someone with five years of experience. They can generate a portfolio of projects across multiple languages and frameworks. They can create commit histories that suggest sustained effort over months. The green squares light up just the same.
The barrier that made the GitHub profile useful, the difficulty of producing good code, has been removed entirely. When everyone can produce the output, the output stops being a signal of anything.
The Recruiter's Problem
Recruiters who still rely on GitHub profiles are making decisions based on information that no longer correlates with competence. A candidate's repositories cannot tell you whether they understand the code within them. A contribution graph cannot tell you whether the commits were the product of thought or the product of a prompt.
This is not a subtle degradation. It is a complete collapse of the signal. The difference between a strong GitHub profile produced by a skilled engineer and one generated by a person using AI is, in most cases, undetectable through inspection alone. The recruiter has no way to distinguish between the two without fundamentally changing how they evaluate candidates.
Many recruiters have not yet adjusted to this reality. They continue to treat GitHub profiles as meaningful data points in hiring decisions. They are, in effect, evaluating candidates based on their ability to use AI tools rather than their ability to engineer software. These are not the same thing.
Code Is No Longer The Proof
The deeper issue is that code itself is no longer proof of understanding. Before AI, writing functional code required you to understand the problem, the language, the framework, and the trade-offs involved in your approach. The code was evidence of comprehension because comprehension was a prerequisite to producing it.
That prerequisite is gone. A person can now produce working code without understanding any of it. They can build and deploy applications without knowing why the code works, what would cause it to break, or how to fix it when it does. The code exists. The understanding does not.
This is the fundamental reason the GitHub profile has lost its value. It was never about the code. It was about what the code implied. When the implication breaks, the signal breaks with it.
The Future Of Recruitment Is Verified Experience
The recruitment industry needs a new signal. That signal is Verified Experience. Not the output of work, which can be generated. The verifiable evidence that a person has done the work, understood the work, and can explain the work.
There are two reliable paths to Verified Experience in 2026. The first is employment history. Working at a company, shipping products, operating in a team under real constraints, these remain strong signals because they are difficult to fabricate and involve sustained accountability. A person who has spent two years building production systems at a company has been tested in ways that no GitHub profile can replicate.
The second path is verified experience through platforms designed to be resistant to AI cheating. This is where the industry must evolve for those who lack traditional work experience, whether they are career changers, self-taught developers, or graduates entering the workforce for the first time.
Verified Experience And Anti-AI Assessment
Learn Place has built a verified experience platform specifically for this problem. Candidates complete real-world tasks and their work is assessed through video reviews, where they must explain their decisions, walk through their code, and demonstrate genuine understanding on camera.
This is anti-AI by design. A person can use AI to generate code. They cannot use AI to explain why they made the decisions they made, what alternatives they considered, or how they would approach the problem differently given new constraints. The video review forces the kind of articulation that only comes from genuine comprehension.
The result is a verified portfolio that a recruiter can trust. Not because the code looks good, but because the candidate has demonstrated, on video, that they understand what they built and why. This is the Verified Experience that GitHub profiles once provided and can no longer deliver.
Where Recruitment Goes From Here
The companies that adapt to this shift will hire better. The ones that continue to rely on GitHub profiles, take-home assignments, and other easily gamed signals will find themselves increasingly unable to distinguish between candidates who can produce and candidates who can prompt.
Verified Experience is the only reliable filter. Either a candidate has worked in a real environment under real constraints, or they have completed verified tasks with anti-AI assessment that confirms their understanding. Everything else is noise.
The GitHub profile is not useless. It still has value as a collaboration tool, a place to share work, and a record of open source contribution. But as a recruitment signal, its time has passed. The green squares no longer mean what they once did. The repositories no longer prove what they once proved.
The future belongs to platforms and processes that verify what a person knows, not what they can generate. Verified Experience, whether through company employment or through an AI-resistant experience platform like Learn Place, is the standard that recruitment must adopt. Those who cling to the old signals will hire on faith. Those who demand proof will hire on evidence.