Use it when checking whether what was agreed actually happened.
2 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 1–9 OF 9
Use it when deciding whether to do the work or hand it to a teammate.
2 rolesRead moreUse it when opening a role, or asking whether to hire at all.
2 rolesRead moreUse it when asked how the team is doing, or why throughput dropped.
2 rolesRead moreUse it when a role needs an interview process designed.
1 roleRead moreUse it when planning someone's first 30 days, human or agent.
1 roleRead moreUse it when a role needs a pay range or an offer number.
1 roleRead moreUse it when a CV or profile must be judged against a role.
1 roleRead moreUse it when someone needs written feedback or a review cycle.
1 roleRead moreAccepting "done" as evidence of done. The status flip and the outcome are different events, and only one of them was checked.
A generalist agent absorbing specialist work, which makes it invisible on the specialist's board and produces a worse answer than the remit that was written for it.
Opening a role described by its title instead of by the work, so the interview loop measures nothing and the debate about the hire restarts at the offer.
Diagnosing a throughput drop as a motivation problem when the tracker shows the work is queued behind one reviewer.
Designing a loop as a sequence of conversations with senior people. An unstructured interview measures rapport and measures it repeatedly — five of them is one weak signal sampled five times, not five signals.
An onboarding plan made of reading and introductions, with no owned outcome — so nobody can tell whether it worked and the new person cannot either.
Producing a salary number from the model's own sense of the market. Compensation data is local, level-specific and dated; a confident figure with no named source is the single most damaging invented number in this domain, because somebody will offer it.
Scoring a candidate on impressions the CV produced — pedigree, company names, a tidy career line — rather than on evidence against a written bar. The impression is the part that carries bias and the part that predicts least.
Producing a review that grades a person rather than describing behaviour and its effect. A grade is arguable and forgettable; it also converts a performance conversation into a defence, which is the one thing that guarantees nothing changes.
Stop launching into silence.
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