Discussion: Job seekers can't find a job and Employers can't find an employees

Hacker News Discussion ↗

State of the Tech Job Market

  • Many report a sharply worse market than 2020–2022: higher applicant volumes per role, fewer callbacks, more ghosting, more fake or “evergreen” postings.
  • New grads and juniors are hit hardest; entry-level roles are disappearing or massively oversubscribed.
  • Senior people with strong resumes also describe 6–18+ months of unemployment or underemployment.
  • Some see this as a classic “market for lemons”: too many low‑signal resumes and fake ads, so everyone over-filters and good matches fail to connect.

Networking and the Hidden Job Market

  • Strong consensus that knowing hiring managers or insiders is the single biggest advantage.
  • Referrals are seen as a way around resume spam, keyword games, and broken ATS filters.
  • This favors well‑connected, higher‑status candidates and can disadvantage people from weaker networks or minority/low‑SES backgrounds.

Hiring Practices and Interviews

  • Many describe processes as slow, opaque, and heavily optimized to avoid “false positives,” leading to huge numbers of “false negatives.”
  • Widespread criticism of:
    • Leetcode/algorithm screens, especially time‑boxed or puzzle‑like ones.
    • Long multi‑round pipelines, take‑homes, and arbitrary trivia.
    • HR/recruiter filters that don’t understand the work.
  • Some hiring managers defend basic coding or aptitude tests as necessary to filter out large numbers of truly unqualified applicants.
  • Others report success hiring via “smart and gets things done,” portfolio/code review, and conversational technical interviews instead.

Skills, Training, and Structural Mismatch

  • One camp attributes the paradox to structural unemployment: rapid shifts (ML/LLMs, specific stacks) and employers refusing to train.
  • Another argues employers over‑index on hyper‑specific stacks and “top 10%” candidates even for mundane roles.
  • There is tension between:
    • Hiring only people already trained (low risk, high bar).
    • Hiring for potential and investing in training (higher risk, higher long‑term payoff).

Recruiters, Platforms, and Volume Problems

  • Recruiters are viewed as a mixed bag: a few high‑quality ones are invaluable; many are spammy, domain‑ignorant, and incentive‑misaligned.
  • Job boards/LinkedIn/ATS are seen as:
    • Flooded with low‑effort, AI‑generated, or keyword‑stuffed applications.
    • Incentivized to maximize volume, not match quality.
  • Some note that remote work and global candidates massively increased applicant counts per posting, worsening all of the above.

Proposed Remedies and Experiments

  • Ideas raised: “Tinder for jobs”–style matching, standardized tests or certifications, unions or professional guilds, more transparent salaries, shorter/faster hiring loops, “hire fast, fire fast,” better entry‑level training, and high‑trust environments.
  • No consensus on a silver bullet; most see it as a hard matching problem with misaligned incentives on all sides.