AI’s impact on engineering jobs may be different than expected

Original Article ↗ Hacker News Discussion ↗

How AI Is Changing Engineering Workflows

  • Many report teams aren’t cutting engineers so much as redistributing work: seniors gain leverage, juniors gravitate toward tooling, glue code, and review.
  • For experienced devs, LLMs feel like an eager junior: they can stand up full stacks or do tedious tasks, but still need careful supervision for security, performance, and correctness.
  • Several see this as just another abstraction layer, like moving from text editors to IDEs or from assembly to high‑level languages.

Force Multiplier, Not Replacement

  • Consensus that AI amplifies existing skill: strong engineers get much faster, weak ones produce low‑quality output more quickly.
  • Good results hinge on precise problem definitions, context, and prompts; vague understanding yields vague garbage.
  • At the org level, AI magnifies existing practices: teams with solid quality controls benefit; sloppy teams accumulate more issues and outages.

Reliability, Limitations, and Frustration

  • People report wild day‑to‑day variability: some days tools feel magical, other days “dumpster fire.”
  • Pushback against the reflexive claim that any bad experience means the user is “holding it wrong.” Even heavy daily users see broken or misleading outputs.
  • There’s worry about overreliance: juniors (and some seniors) may lose the ability to reason and debug independently.

Impact on Juniors, Training, and Skills

  • Skepticism that students trained heavily on AI will truly be “entry‑level seniors”; fears of bigger, harder‑to‑detect mistakes.
  • Some predict a split between engineers who use AI to accelerate deep understanding vs. those who let it replace understanding and become dependent.
  • Analogies to cars: society routinely trades hands‑on knowledge for abstraction, but that leaves people helpless when systems fail.

Labor Markets, Capital, and Jobs Debate

  • Strong undercurrent that macroeconomics (end of zero‑interest era, wealth concentration) matter more for jobs than AI itself.
  • Some argue automation should enable shorter hours and redistribution (UBI, socialism), but instead mainly boosts profits.
  • Others think if 1 dev can do the work of 10, competitive pressure will push firms to use that leverage offensively, so demand for capable engineers persists, though expectations and bar will rise.

Industry Hype and EDA‑Specific Concerns

  • Commenters note the article is about semiconductor/EDA, but see generic, self‑serving “we’re embracing AI” messaging from incumbents.
  • Skepticism about claimed “AI‑driven chip design” metrics and what actually counts as AI vs. traditional automation.