Distraction from job postings on LinkedIn: SKIP, 42/100 | Ideas Lab

A LinkedIn filter that hides irrelevant job postings from users who are actively networking or consuming content.

The pain

LinkedIn users see job recommendations they don't want. This creates friction when scrolling for networking or industry insights. The feed becomes noise instead of signal.

The gap

LinkedIn's algorithm prioritizes engagement (clicks, applies) over user intent. Someone browsing for thought leadership content still gets hammered with recruiter spam. No existing tool lets users cleanly separate 'I'm open to opportunities' from 'leave me alone about jobs.'

Build angle

Start as a browser extension that filters job posts based on user-defined rules (seniority level, industry, location, salary range). Track what users hide to learn their actual preferences. Monetize through a freemium model or sell aggregated hiring intent data to recruiters who want precision targeting.

Strengths

Clear, immediate problem that affects millions of LinkedIn users daily
Low technical barrier to build an MVP as a browser extension
Natural path to monetization through recruiter access to filtered user data
Solves a real UX gap that LinkedIn has no incentive to fix

Risks

LinkedIn actively discourages third-party tools and could block extension access or change API policies
User adoption requires habit change—most people tolerate the noise rather than install extensions
Monetization depends on recruiter willingness to pay for filtered access, which may not materialize
The problem is annoying but not painful enough to drive viral adoption
LinkedIn could build this feature themselves in weeks if they saw traction

Fly Labs Method

Is the pain real, is there a gap, is it the right time, can one person build it.

42

Value Equation

Dream outcome and how likely it feels, against the time and effort it costs.

35

One-Person Business

Curiosity pull, identity fit, and a path from free value to paid for a solo creator.

48

Viral Frameworks

Hook strength, shareability, and how cheaply it can be tested.

38

Builder Lens

Evidence the problem exists, timing, defensibility, and a model that fits on a napkin.

41

Five lenses, one composite. How scoring works

The angle

Start as a browser extension that filters job posts based on user-defined rules (seniority level, industry, location, salary range). Track what users hide to learn their actual preferences. Monetize through a freemium model or sell aggregated hiring intent data to recruiters who want precision targeting.

No market research recorded for this idea yet.

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