Our efforts, in part, define us

Identity, Craft, and Changing Roles

• Many connect their sense of self to their craft (coding, photography, carpentry, etc.), so automation feels like erosion of identity, not just job risk.
• Some describe similar dislocation moving from hands-on coding to management; peace came when they reframed their value as enabling others rather than producing artifacts.
• Others insist it’s normal and healthy to tie some identity to work, and that people deserve space to grieve lost trades rather than being shamed as inflexible.

AI, Software Work, and Jobs

• One camp sees AI as a “force multiplier” that expands what individuals can build in limited time; coding becomes higher‑level design and debugging.
• Another camp experiences AI as a “step backwards” that hollows out the most satisfying part of the job, or floods the world with low‑quality code and misinformation.
• Several argue LLMs currently resemble “clueless juniors”: useful snippets, poor reasoning, still needing senior oversight. Embedded/low‑level work is cited as an area where they’re weak.
• Some fear long‑term income erosion for programmers; others doubt mass replacement, seeing past waves (COBOL, no‑code, Dreamweaver) as cautionary analogies.

Effort, Satisfaction, and Meaning

• A recurring distinction: people don’t necessarily value raw effort, but the satisfaction and meaning derived from struggle, mastery, and contribution.
• Some say when effort becomes “effortless” via tools, the locus of craft simply moves up a level of abstraction; others feel the joy evaporates and shift to new hobbies.
• There’s extended reflection on meaning as something humans create, not discover; tying all meaning to work is seen as risky, yet common.

Communication as the Real Job

• Multiple commenters reframe software engineering as fundamentally communication and translation: between people, systems, and representations.
• Under this view, code generation is a small part; the hard, valuable work is problem framing, aligning stakeholders, and designing robust solutions.

Historical, Cultural, and Class Angles

• Comparisons are made to blacksmiths, miners, film photographers, DJs, artisans: technology repeatedly devalues specific skills while enabling new ones.
• Some highlight that white‑collar workers are only now feeling a precarity long familiar to other classes; sympathy from those groups may be limited.
• Cultural differences in valuing effort (e.g., Protestant/Japanese vs. Mediterranean attitudes) are mentioned as shaping reactions to AI and automation.