I analyzed 180M jobs to see what jobs AI is replacing today

Software engineering job security and demand

• Several commenters agree with the article that software engineering remains relatively secure versus other white‑collar jobs, at least for the next 10–15 years.
• Others note that many engineers are currently employed on the “AI boom” thesis; if those expectations cool, cascading layoffs and harder job searches could happen even without full automation.
• There’s concern that IT headcount growth has slowed, especially in large offshore markets, leaving many new grads under- or unemployed.

AI tools vs programmers and compilers

• Some compare LLM coding tools to compilers or higher-level languages: historically these increased programmer productivity rather than eliminating programmers.
• Others strongly disagree, arguing LLMs let non-programmers produce working software in ways compilers never did, citing degrees or projects largely completed via ChatGPT.

Who is an “engineer”?

• Long subthread debates whether using AI to build things makes users “software engineers.”
• One side uses a broad dictionary definition (design/build/maintain systems, no credential needed), treating prompt-writing and LLM orchestration as software design.
• The other side stresses profession, training, responsibility, and outcomes—likening “AI users” to flight-sim hobbyists vs licensed pilots, or to mechanics vs engineers.

Methodology and data-quality criticism

• Multiple commenters argue that job postings ≠ jobs: ghost listings, duplicates across sites, reposting, and unknown fill rates heavily pollute the data.
• Critics say the analysis conflates changes in posting counts with “jobs AI is replacing,” without causality or adjustment for layoffs/attrition.
• Short time window (2024→2025) and post‑pandemic volatility make trend attribution to AI especially questionable.
• Lack of absolute counts (only percentages) and missing categories (e.g., sales roles) are flagged as major gaps.

Sector-specific observations

• Frontend roles: many report LLMs are very strong at UI/React work; smaller firms can “vibe code” UIs, larger ones boost FE productivity and hire less.
• Mobile: decline may reflect offshore shift and cross-platform tools; LLMs seem particularly competent at React Native.
• Creative roles: demand for “executors” falls while director-level creative rises—interpreted as induced demand plus cost-cutting in rank-and-file.
• Security: mixed views—some see declining postings, commoditization, and “snake oil”; others report booming consulting work and argue engineers are being pushed to own more security themselves.
• Nursing and other non‑AI‑affected jobs dropping in postings is cited as evidence that broader economic factors, not AI, drive many changes.

AI as productivity multiplier vs headcount reducer

• Several practitioners say AI makes them far more productive and shifts work toward “babysitting” or supervising models, leading management to attempt more projects rather than cut staff.
• Others argue that when firms must choose between guaranteed cost reduction (fewer people) and speculative growth (more projects), they’ll often cut headcount and use AI as the justification.

Offshoring and regional shifts

• Some believe big tech is simultaneously cutting Western headcount and expanding AI and engineering hubs in India, pointing to recent investment announcements and headcount growth there.
• It’s unclear from the discussed dataset whether declines in US postings reflect automation, offshoring, or general belt‑tightening.