The next two years of software engineering

Junior Developers, AI, and Entry-Level Collapse

• Strong disagreement over advice that juniors should prove “one junior + AI = small team.”
• Critics say this ignores lack of opportunity and that the market is constrained by executive cost-cutting, not junior skill.
• Others argue in the LLM era “we are all juniors,” and that juniors with strong fundamentals plus LLM skills could outcompete seniors who ignore AI.
• Counterpoint: software is high-dimensional and requires “taste” developed via experience; LLMs can let unskilled people create fragile systems faster.

Senior vs Junior Value in an AI World

• One view: seniors are defined by willingness and ability to write original code; LLMs don’t change that.
• Another: senior value is primarily in decomposition, architecture, and managing large, complex systems—still critical even with strong AI.
• Many note LLMs expose how little project code is truly novel, but that tradeoffs and non-obvious constraints still require human judgment.

How LLMs Are Actually Used (vs “Vibe Coding”)

• Many report LLMs mostly speed up existing workflows: better than search, good at boilerplate, syntax, and scaffolding.
• “Vibe coding” (letting AI build full apps without review) is acknowledged to exist, especially for prototypes and disposable side projects, but seen as dangerous for production.
• Concerns: non-determinism, lack of predictability, and social incentives to prioritize velocity over careful review and tech debt control.

Education, Fundamentals, and Credentials

• Debate over whether CS degrees should teach cloud/devops: some say CS is math/fundamentals, others argue “fundamentals” must now include large-scale distributed systems.
• Distinction drawn between CS (theory) and software engineering (practice); several call for proper SE degrees.
• Broad agreement that CS fundamentals age well and are a long-term advantage over “vibe coders” who rely on AI to bypass deep understanding.

Jobs, Economics, and Anxiety

• Cited research suggests modest junior hiring drops in AI-adopting firms; commenters question attribution and point to tax changes and failing AI projects.
• Fears: fewer juniors, more grunt work for seniors, higher expectations per engineer, and more precarious careers, especially for those with families.
• Others argue historical patterns (productivity → more software demand) may still hold, but concede any adjustment period will be painful and uneven.

Quality, Maintenance, and Future Debt

• Major worry that massive amounts of AI-generated, poorly understood code will create a future maintenance crisis.
• Some argue AI will also be used to refactor and “recompile” code, reducing the premium on clean design; others think this underestimates long-term complexity and the need for human oversight.