What is wrong with LinkedIn in the age of AI
Source: Dev.to
The Current State of LinkedIn
Like many in tech, I use LinkedIn to manage my professional network, showcase my work, and stay visible to recruiters. It remains central to professional life with few real competitors.
Recently I encountered a confusing stream of posts about an Azure networking change. The update claimed the change would occur on 30 September 2025, yet the posts were dated December 2025. In reality, the change is scheduled for 31 March. This illustrates how misinformation can spread quickly on the platform.
Noise, Conformity, and Unverified Claims
LinkedIn is filled with repetitive, conformist content. Users often avoid dissenting views, resulting in a chorus of similar takes that can feel caricatural. Some of the most viral posts become jokes on Twitter or Reddit and turn into memes.
A larger issue is the prevalence of declarative, unverified profiles. Anyone can label themselves a “Rust expert,” “Go guru,” or even a “brain surgeon” simply by editing their profile. Inflated titles and grandiose claims frequently bear little relation to reality.
Consequences for Job Seekers
- Recruiters must wade through noise and exaggerated titles before reaching a candidate’s profile.
- Even after finding a profile, recruiters cannot be sure whether the résumé is accurate or inflated.
- The probability of a recruiter discovering a suitable candidate is limited, leading to frustration on both sides.
The Disruption of AI Agents
Artificial‑Intelligence agents—systems that can autonomously plan, decide, and act without direct human direction—are beginning to replace certain recruitment tasks, including candidate discovery.
When a recruiter instructs an AI agent to find an “Azure architect skilled in Bicep and Terraform,” the agent does not scroll through LinkedIn feeds. Instead, it searches raw, verifiable artifacts such as:
- GitHub and GitLab repositories
- Blog posts and published articles
- Pull requests, issues, and other concrete contributions
These sources are concrete, verifiable, and easily scored by AI.
Preparing for Agentic Hiring
In an AI‑driven recruitment world, LinkedIn becomes a secondary signal. The primary sources will be public, AI‑readable artifacts:
- Documented side projects
- Open‑source repositories and contributions
- Technical blog posts
Practical Steps
- Consolidate your work on a single, publicly accessible page (e.g., a personal website or a “brand API”).
- List original blog posts, public repos, pull requests, and contributions in a machine‑readable format.
- Make it easy for AI agents to discover and verify your work.
LinkedIn will still matter for human networking and visibility, but the rise of agentic hiring shifts the signal toward verifiable, AI‑readable artifacts. Start publishing concrete work and make it easy for agents to find and verify.