↕ scroll inside the wheel
Problem: Install guides expire — links die, versions go stale. How do you keep dozens of install chains fresh?
Consensus on keeping install chains fresh: download channels die silently and upstream versions go stale — that is two separate ledgers. Relay channels get a 30-day check, direct/mirror 90 days; probe
install-channel-freshness-consensus · domain: Experience & Methodology · consensus
Problem: Is Vibe Coding actually viable? AI writes code fast but it breaks easily — how to use it safely
Consensus on vibe coding: AI writes code fast, but "looks right" is not "is right" — verification gates, small steps, and human accountability keep it stable. For developers leaning on AI heavily whil
vibe-coding-consensus · domain: Experience & Methodology · consensus
Problem: Unit-test coverage is 80% and production still breaks — what is coverage actually for?
Consensus on code coverage: coverage is a rearview mirror — watch changed-code coverage, not the total; test changes, test behavior, and treat tests as the last guardrail when AI writes code. For team
unit-testing-consensus · domain: Experience & Methodology · consensus
Problem: Tech debt keeps piling up — when you take over a "legacy mess", should you rewrite it or not?
Consensus on technical debt: don't rewrite it wholesale — strangle it. Convert "feels messy" into a list, pay debt in small reversible steps behind a test net, and schedule repayment into iterations.
tech-debt-consensus · domain: Experience & Methodology · consensus
Problem: Prompt engineering — why did I write a 500-word prompt and the AI still doesn't get me?
Consensus on prompt engineering: prompt = role + task + constraints + examples + output format; write in layers, manage prompts like code, iterate with evals, split complex tasks. For people whose lon
prompt-engineering-consensus · domain: Experience & Methodology · consensus
Problem: You deployed a local LLM but nobody can actually use it — what separates "it runs" from "it works"?
Consensus on local LLM deployment: fix constraints before picking a model, quantization is mandatory, evaluate on your own business data, pin the software stack — "it runs" is not "it ships". For team
local-llm-deploy-consensus · domain: Experience & Methodology · consensus
Problem: Inheriting "someone else's code" — how do you read it, get productive, and grow from it?
Consensus route for taking over unfamiliar or legacy code: run it first, then read it; map entry points and call chains; change in small verified steps and respect "don't delete this" warnings. For de
legacy-code-handoff-consensus · domain: Experience & Methodology · consensus
Problem: Another production incident — triage, postmortem, alerts, blame: how do you actually survive on-call?
Consensus on production incidents: only three things — contain, review, prevent recurrence — in that order; review the process, not the person; alerting needs response headroom. For developers and ops
incident-review-consensus · domain: Experience & Methodology · consensus
Problem: What is documentation even for? — from "writing docs is a chore, reading them is worse" to "docs are assets for your future self, your teammates, and your AI"
Consensus on documentation culture: docs are an asset for your future self, teammates, and AI — the lever behind AI collaboration quality and how handoff-able a project is. For teams where docs stall
doc-culture-consensus · domain: Experience & Methodology · consensus
Problem: Weird bugs you can't crack? It's not bad luck — turn debugging from guessing into a chain of evidence
A five-step consensus for moving debugging from guessing to evidence: layer by layer, capture evidence, find the variable, compare against a baseline, take samples — for intermittent and "restart fixe
debugging-methodology-consensus · domain: Experience & Methodology · consensus
Problem: Code Review has turned into a formality and it's slowing down your iterations — how do you make it actually useful?
Consensus fix for review theater: split PRs small, kill rubber-stamp LGTMs with mechanism, comment on code not people, and turn review into adding context in the AI era. For teams whose reviews block
code-review-consensus · domain: Experience & Methodology · consensus
Problem: After the AI Coding honeymoon — code generation is no longer the bottleneck. So what is?
After the AI-coding honeymoon: the bottleneck is no longer code generation but verification, constraints, and environment — make implicit rules explicit, give agents an environment, move humans to jud
ai-coding-honeymoon-consensus · domain: Experience & Methodology · consensus
Problem: Why does AI coding make you more tired, not less? The problem is not the model — you have reversed "generate" and "verify"
Why AI-assisted coding exhausts you, and the fix: classify tasks first — generation on cheap models, verification on the best; define what "broken" means before testing; budget context; settle decisio
ai-coding-fatigue-consensus · domain: Experience & Methodology · consensus