1. Endorsement of heuristics against novelty and over-abstraction
Users strongly praise warnings on tech novelty and abstractions, favoring familiar stacks for reliability.
"Novelty is a loan you repay in outages, hiring, and cognitive overhead." (kayo_20211030)
"There's rarely a bullet point advantage that some new language or tech stack can offer me that would outweigh ten years of observation of how a familiar setup behaves in production" (gdulli)
"Abstractions don’t remove complexity. They move it to the day you’re on call." (kayo_20211030)
2. Suspicion of AI-generated content
Many detect LLM hallmarks in the article's style and bio, dismissing it as slop despite solid points.
"It is very heavily filled with LLM-isms. The writing is bland AI output." (spiralcoaster)
"The blog-post is AI generated or at least AI assisted." (rvz)
"It's just so disrespectful. I put my time in reading this. You (author) couldn't put some time into reading this once over before publishing?" (aprilthird2021)
3. Real-world user behaviors defy expectations (bugs have users)
Anecdotes highlight Hyrum's Law: users rely on bugs; improvements spark backlash.
"At scale, even your bugs have users." (nickcw)
"The load time improvements had destroyed their company culture. Instead of everyone coming into the office... spending the next 10min chatting... the software was ready before they’d even stood up" (trescenzi)
"With a sufficient number of users of an API... all observable behaviors of your system will be depended on by somebody." (davelee, citing Hyrum's Law)