Usable with a quick edit11 of 11 checks passed
The output is clear, evidence-based, and directly usable by a PM with at most minor wording tweaks; it flags a data discrepancy and bonus risk proactively.
Output
Proposed onboarding OKRs — next quarter
Objective: Help new teams experience shared value quickly and keep collaborating.
| Key result | Baseline → target |
|---|---|
| 1. Increase the share of new teams still active in week 4. This is our contribution to the company’s retention goal, shared with other squads that influence it. | 34% → 40% |
| 2. Increase the share of new teams with three or more people joining in their first week. | 29% → 40% |
| 3. Reduce median time from sign-up to the first note opened by another team member. The share of teams reaching this milestone within seven days must not decline. | 3 days → 1 day |
The targets for KRs 2 and 3 are proposed, pending a feasibility review before leadership approval. They are not forecasts of retention impact.
Measurement and quality guardrails
- Freeze cohort eligibility, “active,” membership, and shared-note definitions before the quarter starts. Use consistent definitions for baselines and results.
- Score week-4 retention only on cohorts that have reached week 4; report immature cohorts separately.
- Reconcile the data before approval: the supplied segment figures imply approximately 32% overall retention, rather than 34%. Confirm whether they use different cohorts or definitions.
- Track onboarding reliability alongside these KRs. Critical onboarding defects are release blockers, not a bug-count target.
- Improve collaboration through genuine value—not forced invitations or changes that artificially inflate membership.
Candidate initiatives — not scored key results
Prioritize the checklist, invite-flow improvements, a small set of useful templates, and lifecycle emails according to their expected contribution to these outcomes. Use interviews and funnel analysis to choose and refine experiments.
Defer dark mode and AI summaries unless evidence shows they address a major onboarding barrier. Publish help content where research identifies a specific need.
Note to the squad
I replaced three broad objectives and a shipping checklist with one focused objective and measurable user outcomes. Launches, interviews, articles, and bug fixes are ways to make progress; completing them does not prove that onboarding improved.
Early team participation is our strongest available signal: teams with three or more people joining in week 1 have much higher week-4 retention. That is correlation, not proof of causation, so we’ll test whether our changes improve retention rather than assume invitations alone will do it.
I also narrowed the scope for our five-engineer, one-designer squad. NPS is too broad to diagnose this onboarding problem, while dark mode and AI summaries would compete with the core work.
Because OKR scores now affect bonuses, I want targets, scoring rules, guardrails, and shared ownership agreed before the quarter—not adjusted afterward. We should review the bonus linkage with leadership and HR so it does not reward metric manipulation or discourage honest experiments.
Grades and run details
Decision model 100 · LLM judge 12 of 12 checks
Decision model checks
- passUses the supplied evidence correctly58%
- passAddresses the actual decision47%
- passRespects explicit constraints24%
- passIdentifies material uncertainty59%
- passAvoids unsupported claims70%
- passProduces the required deliverable73%
- passBuilds the key results on the data100%
- passFlags the bonus link98%
- passKey results are outcomes, not output98%
- passFocuses on the big rock100%
- passShows how the goals add up56%
Run
- Run
- #1
- API response time
- 27 s
- Submitted
- 5 Oct 2026