For thirty years I programmed with Phish on, every day

What Phish Is and Music-for-Coding Culture

• Several commenters clarify that Phish is an American jam band, with some comparing them to the Grateful Dead.
• Many share their own “coding soundtrack” histories (Phish, the Dead, techno, jungle, EDM, grindcore, Toto, etc.) and how music once tightly coupled to deep work and “flow.”
• A few people say they can’t work with music at all, underscoring how individual this is.

Loss of Flow State and Identity

• Strong resonance with the sense of grief: longtime programmers and sysadmins describe losing a cherished flow state and feeling less like “real” practitioners.
• Some describe decades of deep, uninterrupted coding as a core life identity; AI and agent workflows feel like that world abruptly ended.
• Others argue that some people are “born” engineers and are now going through genuine mourning as their craft changes.

Agents, LLMs, and the Changing Nature of Programming

• Many say their day-to-day work has shifted from writing code to managing LLM agents: specifying tasks, reviewing output, and handling errors.
• This new workflow is described as staccato, interrupt-driven, and often manic, in contrast to long, immersive coding sessions.
• Some see benefits: more “big picture” focus, faster output, new kinds of problems to solve, and better leverage of experience.
• Others find it joyless “babysitting interns,” with less learning-by-doing and more black-box systems.

Debate: Is This Still Engineering?

• One camp insists this is still engineering: design, architecture, tradeoffs, and accountability remain human. Coding is likened to pouring concrete.
• Another camp says this is effectively management, not engineering; delegating everything to an opaque system erodes understanding and increases risk.
• There is disagreement over whether LLM use inevitably sacrifices quality for speed.

Learning, Craft, and Career Anxiety

• Some feel they’re unlearning skills and losing the satisfaction of craftsmanship; LLMs erase the “small wins” and the pleasure of mastering tools.
• Others say they learn faster with LLMs (concepts, tradeoffs) and welcome offloading rote work.
• Several worry about career futures, ageism, and eventual automation of both “idea work” and coding, while others suggest focusing on broader “engineering” skills, hardware, or entirely different crafts.
• A minority notes that using agents is a choice for now, but others respond that companies are already rewarding or expecting heavy AI usage.