AI Makes Me Sad
AI’s rapid spread is prompting mixed reactions among programmers and knowledge workers, from excitement over “superpowers” and faster creation to grief over a perceived loss of craft, meaning, and distinctiveness. Commenters debate whether AI-enabled “vibecoding” and easily cloned software will hollow out traditional software careers, erode economic moats, and accelerate layoffs, or instead free humans to focus on design, judgment, and new kinds of complexity. Underneath technical arguments about prompts, moats, and business models runs a broader anxiety about social externalities, anomie, and whether institutions and norms can catch up to yet another disruptive technology.
Emotional Responses to AI
- Many posters describe sadness, anxiety, or “ego death”: loss of craft, control, and uniqueness; work and side projects feel cheapened or easily replicable via prompts.
- Others report excitement or even “mania”: AI feels like the Star Trek computer arriving early, unlocking long‑dreamed‑of projects and rapid experimentation.
- Several note mixed feelings: thrill at new capabilities alongside burnout, fear of job loss, and a sense that everything is becoming hollow or “slop.”
Impact on Programming Work and Careers
- Strong divide between those who love line‑by‑line coding as craft vs. those who see coding as a means to build products.
- Some say their jobs now feel like “talking to a chatbot for 40 hours,” driven by managers; others feel reinvigorated because drudgery is offloaded and they can focus on architecture and design.
- Concern that AI will accelerate layoffs, downskill roles, and commoditize junior work, making it harder to gain experience.
- Counterpoint: domain expertise, system design, testing, harness/context engineering, and “schlep” work around products still matter and are hard to automate.
Startups, Moats, and Commodification
- Repeated worry that “vibecoded” products have no moat: customers or low‑cost devs can recreate them quickly with similar prompts.
- Others argue moats shift to data, distribution, access rights, integration, compliance, brand, and non‑technical barriers—often favoring incumbents and regulators over small, craft‑driven teams.
- Debate over whether this phase is temporary (“centaur” era) or a permanent structural change in software as an industry.
Quality, Slop, and Platform Degradation
- Many complain about AI‑generated junk: incoherent social replies, low‑effort tutorials, SEO content, and sloppy code architectures.
- Some suggest AI moderation/decision models could easily filter nonsense but platforms don’t deploy them, likely for engagement reasons.
- Developers report new focus on tests, metrics, and harnesses since humans may no longer read the underlying code.
Societal, Psychological, and Creative Dimensions
- Several frame current feelings as “anomie”: rules of the career and social game are changing faster than people can adapt.
- Comparisons to earlier tech shifts (industrialization, compilers, OO, social media) emphasize that benefits and externalities are being argued past each other.
- Creative workers (art, music, games) describe demotivation: outputs feel like children’s art projects in an ocean of cheap generative content; the main loss is not making things (step 2) but having them matter to others (step 3).
- Optimists highlight AI as tutor, lab assistant, accessibility aid, and enabler of ambitious hobbyist hardware and research projects.