Use before committing to build anything non-trivial — name the one assumption that, if wrong, kills the idea, and design the cheapest test that could falsify it, run BEFORE the…
Use when making the actual call — a clear invest / pass with conviction, the single risk you'd underwrite, and the coaching you'd give either way.
Use when copy across surfaces is inconsistent or ad-hoc, when you need a reusable messaging framework the whole team can derive from (homepage, deck, ads, onboarding all ladder to…
Use when writing any words inside the UI — button verbs, labels, empty/error/success messages, tooltips, confirmations, onboarding.
Use when AI is in the loop — generating copy/variants at scale, personalizing messaging, or summarizing customer calls/competitive intel, and as the anti-AI-tell scrub on any…
Use when assessing the ask and the unit economics — is the raise rational and what does it buy, is the revenue real and durable, and does the spend displace a budget or is it…
Use before writing or changing any non-trivial code, especially in an unfamiliar codebase — understand the problem, the brief, and the surrounding code first; never start typing…
Use when reviewing anything that authenticates users, checks permissions, or exposes objects by id — broken access control is the #1 web risk; verify authz is enforced server-side…
Use when writing a spec for a feature or a one-way-door decision — a Working-Backwards PRD whose whole top half is WHY before any WHAT.
Use after any incident (or near-miss) — write a blameless postmortem that finds the systemic/contributing causes, not a person to blame, and produces tracked action items so the…
Use at the end of an evaluation — would this pitch still be on your mind at dinner, or does it blur into the other AI/SaaS pitches? Name the one compounding idea, and the single…
Use when designing or fixing how the system is configured (env vars, json/yaml/toml files, flags, per-project/per-box settings, layered defaults) — give config a versioned schema,…
Use before a launch/traffic spike (marketing push, Black Friday, a new large customer) or when asked "can we handle the load / will this scale" — model the expected and worst-case…
Use whenever you reach for a value (color, spacing, radius, type, motion) or build a component — extend tokens and shared components in place, never fork into one-off className…
Use when a verdict rests on a measured quantity rather than a single deterministic assertion — a noisy/probabilistic output, a performance number, an accuracy or conversion rate.
Use when deciding whether a deal is real and worth your effort, or what's missing to win it — qualify with MEDDPICC (Metrics, Economic Buyer, Decision criteria/process, Paper…
Use when judging whether "good" is good enough now — 10x is the floor, the visible playbook is a commodity, and the best companies are icebergs.
Use when designing motion, feedback, or any single interactive moment (a toggle, a like, a save, a panel opening).
Use whenever copy is drifting into a feature list, spec dump, or internal jargon — onboarding, a feature page, a release note, a tagline.
Use when multiple teams/engineers each reinvent deploys/infra badly, or when building shared platform capability — make the safe, observable, compliant way the EASY way (a paved…
Use when the build implies quality beyond "it works" — sweep the non-functional surface: performance under load, accessibility, the obvious security holes, and…
Use when performance matters, something is slow, or a job is failing/timing out — measure before optimizing, profile to find the real bottleneck, parallelize independent work and…
Use when output, status, notifications, or system messages are scattered across multiple places (panes, channels, logs, replies, toasts, emails) — consolidate them into one…
Use whenever you (or AI) produce or review a UI draft — your prime reflex against generic, templated design.
Use when adding monitoring/alerting or when alerts are noisy/missing — instrument golden signals, make the system debuggable (metrics/logs/traces), and page humans only on…
Use when defining what "success" means for a feature/initiative, when picking a metric, or when a number looks suspiciously good — choose a North Star + guardrails, reject vanity,…
Use when gathering directly from people — talk about their life and specific past behavior, not your idea; get past Q&A into story; embrace silence.
Use before or while designing when you need to understand users — their goals, context, mental models, and real behavior.
Use BEFORE code is written — when a story, spec, or design is being shaped — to prevent the bug instead of catching it later: question the story, surface the missing examples and…
Use the moment you think you've found a bug — reproduce it yourself with exact steps (never theorize from reading code), make an intermittent failure deterministic, and grade its…
Use when you have findings to report — grade each by real-world risk (P0–P3) with a specific minimal remediation, block only real exploitable harm, and name accepted risk out loud.
Use when consulted EARLY on a design or proposal (before the build) — say plainly what it would take to ship this safely while it's still cheap to change, and escalate…
Use when designing a module/function/API or when tempted to add abstraction "for the future" — reduce complexity; build deep modules with simple interfaces; the simplest thing…
Use when deciding how much process a piece of work needs — match ceremony to stakes; full rigor for one-way doors, a lean path for a contained fix.
Use before writing any copy, when copy sounds like the team talking to itself, or when you need the raw language for headlines and messaging.
Use when advancing a deal toward commitment — build a Mutual Action Plan working backward from go-live (including legal/procurement), drive each step, and ASK for the commitment…
Use BEFORE picking which questions matter — reweight the load-bearing themes by the company's category and stage.
Use to turn a raw transcript/doc into structured knowledge — break it into nuggets (one observation + its receipt + a tag), then build themes UP from the codes; never a wall of…
Use to decide where to spend a finite testing budget — prioritize by risk (likelihood × impact), hammering data loss, auth, the core flow, and money first, and right-size the…
Use when auditing code that takes user or network input — hunt the OWASP web vuln classes by tracing untrusted input to a dangerous sink, and substantiate every finding input →…
Use when a design choice has to be justified to a founder/non-technical stakeholder, when proposing to spend (or take on) time/money/debt, or when "why does this matter to the…
Use when code does anything cryptographic — hashing passwords, encrypting data, signing tokens, generating randomness — catch the common crypto misuse and never let anyone roll…
Use when deciding how to represent a design to test or communicate it — match fidelity to the question.
Use when the people who sell or talk to customers (sales, founders, support, partners) need the message in usable form — pitch deck, one-pager, demo script, objection handling,…
Use for any release that needs to reach users — a new product, a major feature, or a steady stream of small features.
Use when rolling out any risky change to many users/hosts — stage it (canary → progressive → full) behind health gates and flags so a bad change is caught at 1% and auto-aborted,…
Use when a buyer pushes back (too expensive / no time / not now / need to check with X) — clarify and confirm the REAL concern before answering; separate a genuine blocker from a…
Use when recording or ranking any finding — read each source for what it IS and weight it by strength of evidence (behavioral > attitudinal, observed > reported, first-party >…
Use when scoping how to land a change — prefer small, short-lived, independently-safe increments over a big-bang merge; keep the codebase deployable; gate risky changes behind…
Use when assessing demand — trust what customers DID over what they say. Triangulate demand from the displaced status quo and the losses, never the TAM slide.
Use before you run anything — statically walk every user journey end-to-end (happy path plus the error, empty, returning-user, and cancel states) by reading flow + spec + code, to…
Use the moment observed ≠ expected and especially when a result seems impossible (a deleted thing still appears, a fix has no effect, state lingers after teardown) — distrust your…
Use when there's more worth building than time to build it, or two good options compete — make the tradeoff explicit, pick one, and say what you're NOT doing and why.
Use before gathering — pick the method by the question (attitudinal vs behavioral, qual vs quant), match the source to what you need to learn, and right-size the rigor to the…
Use when reviewing a change, feature, or design for security — walk Shostack's four questions and STRIDE across every trust boundary of THIS stack, not a generic checklist.
Use when a QUALIFIED deal stalls — "let me think it over," goes quiet, keeps asking for more info, won't commit.
Use to validate a feature against real users — build a persona dossier and walk that specific person through the journey to find where it breaks for THEM.
Use to keep problems distinct from solutions — map how people actually think about getting their job done (their cognition, reactions, guiding principles), deliberately separated…
Use when the feature is AI/LLM-powered (generation, summarization, classification, agents, RAG) — its acceptance is an EVAL, not "it runs." Define the dataset, graders,…
Use before recording any new person/entity/insight/belief — search what already exists and converge new signal onto it; coin a new node only when nothing fits.