Use it when writing docs, a guide, a README or an internal how-to.
3 rolesRead moreThe team already knows how the job is done.
124 playbooks, among them how to ship a launch nobody has to rescue, shape a post for where it will be read, run experiments instead of opinions and read an ad account without double-counting. Each one is written around how the work usually goes wrong, and the team picks the right one for the task.
Written by people who do the job.
Each playbook captures the steps and the traps, not just the task name.
Picked for the task.
Ask Iris why signups dropped and Iris uses the analytics playbooks. You don't have to choose.
Every one is listed below.
Browse all 124, grouped by the kind of work.
SHOWING 1–15 OF 15
Use it when more work is proposed than can be built.
2 rolesRead moreUse it when something broke and the review must produce change.
2 rolesRead moreUse it when asked to test, verify, or check whether something works.
2 rolesRead moreUse it when choosing and sequencing what to try next for growth.
2 rolesRead moreUse it when a shipped change must be described to users.
2 rolesRead moreUse it when coordinating the launch of a feature or product.
2 rolesRead moreUse it when raw user conversations must become conclusions.
2 rolesRead moreUse it when customer feedback has to become a decision.
2 rolesRead moreUse it when engineering wants time for work users will not see.
1 roleRead moreUse it when new users sign up and do not come back.
1 roleRead moreUse it when someone asks for a dashboard or a recurring report.
1 roleRead moreUse it when a feature, endpoint or plan is being removed.
1 roleRead moreUse it when commitments must be matched to real capacity.
1 roleRead moreUse it when asked for a spec or PRD, or to scope a feature.
1 roleRead moreDocumenting the intent rather than the behaviour. If the code does something else, the doc is a bug report wearing a doc's formatting.
Producing a scored ranking whose numbers were invented. A prioritisation framework turns judgements into arithmetic, and arithmetic reads as evidence — so an unsourced score is more persuasive and less honest than the opinion it replaced.
Reporting a single root cause, which is almost always the last human action in the chain. Naming a person as the cause ends the investigation exactly where the systemic contributors start, and it teaches everyone else to report less next time.
Reporting "looks good" from reading the diff. A false pass costs more than an honest "I could not run it".
A backlog ranked by enthusiasm, run without a written hypothesis, so nothing is ever concluded and the same ideas return every quarter with the same lack of evidence.
Writing release notes as a list of what the team did, ordered by what was hard. The reader is not interested in the work — they are scanning for whether anything affects them, and a note that does not answer that in the first line is not read at all.
A launch date agreed before support, sales and docs were asked, so the announcement arrives ahead of anyone able to answer a question about it and the first day is spent apologising.
Reporting what users asked for as though it were what they need, and counting mentions as evidence of importance. A feature request is a user's proposed solution to a problem they did not state, and the problem is the part that generalises.
A feature request list ranked by how many people said it, which reliably produces the thing customers can name rather than the problem they have — and buries the one account whose problem was worth solving.
Arguing for debt work on the grounds that the code is bad. "Bad" is an aesthetic claim that loses every argument against a customer-visible feature, and the loss is deserved — the real case is a cost that is already being paid and can be shown.
Adding a product tour to a first-run experience whose real blocker was that the user had no data to work with. A tour explains an empty screen; it does not fill it.
Building the dashboard that was asked for, as a set of metrics. A dashboard with no decision attached is looked at twice and then never again, and its existence is used as evidence that the question is covered.
Concluding that nobody uses a feature from an aggregate usage number. Low total usage routinely hides a small number of accounts that depend on it completely, and those are disproportionately the oldest and largest ones.
Planning against headcount multiplied by working days. That number has never been available in any team — it silently books support, review, meetings, interviews, holiday and the unplanned work that arrives every week at full capacity, and the plan is over-committed before it starts.
Silence on the empty, error and permission-denied states, which the build then invents differently from what anybody wanted.
Stop launching into silence.
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