Experts have it easy (2024)

Mentoring, Juniors, and Mutual Learning

• Many commenters describe deep enjoyment in mentoring juniors: asking “what are you working on?” often reveals dead ends, which become rich teaching moments.
• Mentorship is framed as symbiotic: juniors gain confidence to question decisions; seniors are forced to articulate and re‑examine their own habits.
• Several argue this applies to seniors too: experienced people also wander down bad paths and benefit from peer conversations.
• There’s frustration about industry reluctance to invest in juniors (“they might leave”), which some see as backward: preferring low‑skill, low‑mobility staff.

Informal vs Structured Knowledge Transfer

• Strong disagreement on the article’s swipe at “water-cooler” learning:
  • One camp: relying on chance hallway chats is irresponsible; written, reusable answers (pre‑pivot Stack Overflow style, documentation, blogs) scale expert time far better.
  • Another camp: informal, unguided interaction conveys mindset, culture, tacit patterns, and “links between concepts” that formal material never captures.
• Consensus trend: it’s not either/or. Formal processes raise the floor; informal contact raises the ceiling.

Remote Work, Pairing, and Tools

• Some claim remote work weakens novice learning by removing spontaneous “what are you working on?” moments; screen sharing is useful but a strict subset of in‑person interaction.
• Others counter that in open offices most communication was already via chat; pings are actually easier and less intrusive than walking over.
• Pair programming emerges as a concrete practice that matches the article’s advice: novice drives, expert advises; works well even remotely.

Exploration, Debugging, and Niche Work

• Examples from mechanics and programming highlight how subtle tricks and shortcuts aren’t obvious from manuals or APIs; they’re discovered or observed.
• Several celebrate debugging and untangling legacy or niche systems as a joyful, puzzle‑like path to rapid expertise—though some warn it can turn into career‑long drudgery if you become the only person willing to touch painful systems.
• Learning by live exploration (good debuggers, REPLs, Smalltalk/Lisp environments) is contrasted with modern ecosystems that feel more opaque.

Nature of Expertise and Career Strategy

• Debate over domain specificity: some see expertise as tightly bound to a domain; others argue that meta‑skills and patterns transfer well, and domain knowledge is comparatively easy to acquire.
• Commenters note tacit/“ineffable” knowledge that isn’t in official documents and is hard for current AI or rule‑based systems to capture.
• A few criticize the binary “expert vs novice” framing, preferring a continuum and distinguishing practitioner skill from educator skill; being great at both is seen as extremely rare.
• Career advice appears: specialize in new or neglected niches (e.g., emerging fields, unglamorous systems) to advance quickly, since everyone starts as a novice there.