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LinkedIn’s New AI Tools Rethink How Job Seekers Discover Career Paths
By understanding intent, not just keywords, LinkedIn’s AI helps users find more meaningful job matches — even in roles they hadn’t considered.
LinkedIn is rolling out new AI-powered job search tools designed to match users with better career opportunities — whether or not they know exactly what they’re looking for.
The new features allow job seekers to describe their goals in natural language instead of relying on rigid keywords or exact job titles. Want to explore “business development in the video game industry” or “use your marketing skills to help fund cancer research”? LinkedIn’s AI now understands even the most abstract of intents and can recommend roles that align — even if job listings don’t use those specific terms.
“It’s about helping people express what they want to do in their own words,” said Rohan Rajiv, head of career products at LinkedIn. “Our AI figures out the semantics behind that and matches it with relevant opportunities”.
This evolution in job search is powered by large language models (LLMs), the same kind of AI that fuels tools like ChatGPT. These models excel at inferring meaning from both job descriptions and user profiles, identifying matches that traditional search engines might miss. For instance, the AI can assume a web developer is proficient in HTML, even if they haven’t explicitly listed it on their profile.
Another tool, called Job Match, assesses how well a user fits a role based on their skills and experience. It also pinpoints gaps — like missing certifications or limited exposure to a required technology — helping users better prepare before they apply.
LinkedIn’s AI also offers context around job listings, such as whether an employer is actively hiring, whether a role is promoted on the platform, and typical wait times between application and response.
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Erran Berger, LinkedIn’s VP of engineering, explained that recruiters are also overwhelmed: “They’re spending up to five hours a day filtering through applications, and over half don’t meet basic requirements”. The new AI features aim to improve quality on both sides, helping candidates apply more strategically and saving time for hiring teams.
With over 15 million job postings and 11,000 job applications submitted every minute on LinkedIn, these tools are a major step toward transforming a job market that often feels inefficient and transactional.
CEO Ryan Roslansky framed the update as part of LinkedIn’s long-term evolution: “Twenty years ago, we connected recruiters with passive candidates. Today, we’re using AI to redefine what’s possible in job discovery”.
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Instagram Now Lets You Tune Its Algorithm, But There’s One Big Catch
The new controls promise users “agency” over their feed, but asking to see more from accounts you actually follow returns an error.
Instagram has expanded its algorithm personalization feature to the main feed, letting users specify which topics they want surfaced more or less often in recommendations.
Instagram chief Adam Mosseri framed the change as a matter of user control. “I believe it’s in our best interest as a business to empower people to shape Instagram into something that works for them, and that people should be able to have a meaningful amount of agency over the products they spend so much time in,” he wrote on Threads.
Though it turns out that agency has limits. The controls only accept interest-based topics, such as “rescue dogs” or “parenting humor”. Requesting “posts from people I follow” returns no results, which is obviously a sore point for creators whose posts rarely reach their own audiences. Mosseri conceded the tension: “Who you follow used to be a meaningful tool people had for shaping their own experience, and as recommendations took over the main feed that tool quietly stopped working”.
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Instagram credits large language models for making its algorithms legible enough to personalize, and says it is “actively working on supporting requests for people, different moods or vibes, content types, and more” – potentially leading to a fully “bespoke” version of the app.
