Show HN: I quit coding years ago. AI brought me back

Original Article ↗ Hacker News Discussion ↗

AI as On-Ramp and Multiplier

  • Many commenters echo the original poster: they’d stopped or slowed coding (moved into management, academia, farming, finance, CTO roles) and LLMs let them finally build tools they’d wanted for years.
  • AI is framed as the next wave of “end-user programming,” comparable to Excel: domain experts can now build bespoke apps without hiring devs or re-learning full stacks.
  • Several say the real effect is not becoming “10x engineers” but making long-stalled ideas achievable by lowering setup and boilerplate costs.
  • A recurring view: AI is a multiplier on domain expertise, not a substitute. Without deep understanding of the problem (finance, farming, PE, etc.), it just produces plausible garbage.

“Vibe Coding” vs. Software Engineering

  • “Vibe coding” (letting agents generate most of the code, then poking at it) splits the thread:
    • Supporters: great for side projects, internal tools, and tiny bespoke apps; lets non-devs and ex-devs be productive.
    • Critics: this is toy-level coding; real engineering involves architecture, security, performance, maintainability, and deep understanding.
  • Some professionals use LLMs as “junior devs” or advanced snippet/search tools but insist serious projects still need manual design and careful review.

Code Quality, Safety, and Testing

  • Several worry about AI-built calculators and similar tools being inaccurate yet presented as “made with care for accuracy.”
    • Specific issues: buggy compound-interest output, missing features, rough “knowledge base,” mobile layout problems.
  • Concern that users will trust wrong outputs in financial decisions; calls for rigorous testing and edge-case handling, especially once money or personal data is involved.
  • Broader fears: explosion of insecure, poorly understood LLM-generated code will create more security incidents and future “cleanup” work.

Identity, Motivation, and Joy in Coding

  • One camp feels energized: AI removes tedious parts (setup, boilerplate, glue code) and leaves more room for problem-solving and UX.
  • Another camp feels alienated: the craft and “hands-on” aspect are being replaced by slop curation; some contemplate leaving software or pivoting to hardware, FPGAs, or security.
  • Debate over whether the real value is “writing code” vs. “delivering solutions”; some see the enthusiasm for AI as devaluing their hard-earned skills.

HN Culture and Authenticity Concerns

  • Multiple commenters suspect the post and some replies are AI-generated marketing: polished “founder story” tone, AI-written blog, and growth from one to dozens of calculators.
  • There’s frustration that it’s now hard to distinguish genuine personal stories from AI-shaped content and subtle shilling; some advocate treating most posts as having ulterior motives.
  • Others defend the project as a harmless passion build and argue that gatekeeping and hostility from seasoned devs are part of what AI is disrupting.