AI is wiping out entry-level tech jobs, leaving graduates stranded

Original Article ↗ Hacker News Discussion ↗

State of technological progress

  • Some argue there’s been “a nonstop barrage” of advances, with LLMs, image/video generation, cheaper batteries/solar, quantum milestones, green steel, and domain-specific innovations cited.
  • Others feel most tech is now incremental (e.g., M-series as just A-series iterations, self‑driving building on older systems) and that AI is mostly rehashing “what has been,” not creating radically new consumer products.
  • There’s frustration that, despite promises of AI-driven productivity, consumers don’t yet see a wave of great new apps or obvious benefits.

How bad is the entry-level market?

  • Data linked in the thread shows CS recent-grad unemployment around 4.8–6.1% (2023 data), with relatively low underemployment and high median wages versus other majors.
  • Other sources (SignalFire, Guardian, etc.) suggest entry-level tech hiring is down ~50% from 2019 and continuing to slide, especially for Gen Z.
  • Several commenters argue “wiping out” is overstated; conditions are worse but not catastrophic, and 2019 was an unsustainable boom.

Is AI the cause, or just a scapegoat?

  • Strong view: AI isn’t doing tech jobs; it’s absorbing capital. Money that might have gone to hiring juniors is going into GPUs and data centers.
  • Others note executives use “AI is replacing jobs” as PR to justify layoffs and look innovative.
  • Several say entry-level roles were already declining pre-LLM, blaming macro conditions, end of cheap money, R&D tax changes, and post‑COVID overhiring.

Offshoring, visas, and geography

  • Multiple comments claim offshoring to India and heavy reliance on H‑1B/foreign workers are more important than AI in reducing local junior opportunities.
  • Some describe whole IT departments moved offshore, with quality concerns but powerful cost incentives.
  • A minority advocates strict limits or heavy fees/taxes on imported/exported labor; others argue employment visas are the only realistic path for many skilled immigrants.

Pipeline and long-term risk

  • Concern: if few juniors are hired now—whether due to AI tools, offshoring, or budgets—who becomes mid-level later?
  • Some foresee “COBOL-style” futures in certain stacks (aging experts, expensive consultants), plus increased social instability from youth with no prospects.

Company anecdotes

  • Mixed reports:
    • Some big-tech teams say junior hiring nearly stopped for a couple of years but is now resuming.
    • Others (including EU perspectives) report no visible “post‑pandemic junior boom” at all.
    • A few smaller firms say they’re cutting offshore staff and hiring a trickle of local juniors again.

LLMs as “junior engineers”

  • A subset of developers claim their day is now mostly directing LLMs/agents, which can handle much of what juniors did (especially boilerplate, glue code, basic debugging).
  • Other seniors push back: real juniors grow, can internalize systems, and need less supervision over time; current AI is more like an endlessly fresh but never-advancing intern that increases review burden and can’t truly learn.

Education, skills, and expectations

  • Some blame grads who treated CS degrees as tickets to FAANG salaries without deep skills; others counter that degrees still teach foundational math/CS most won’t learn alone.
  • Several say the main mismatch is expectations: many grads want $150k coastal remote roles; more realistic, lower-paid, non-FAANG or non‑US positions remain available.
  • Others argue that if AI is taking over rote work, juniors will need to come in at a higher baseline—already comfortable coding, using tools, and learning fast.

Macro and social context

  • Commenters emphasize broader forces: end of ZIRP, VC cycles, tax changes, strong dollar, and general economic uncertainty.
  • Some predict rising youth frustration, potential social unrest, and increased appeal of radical narratives in a world where paths to stability appear blocked.