OKR drafting

Outcomes with baselines, not a task list in disguise

Your AI turns goals and task lists into OKRs the way a chief of staff would: few objectives, key results written as metric moves from baseline to target, owners for everything, a capacity check and a weekly check-in rhythm.

By Vander Labs. Works with Claude, ChatGPT, Cursor and Claude Code.

What your AI learns

• Separates outcomes from activities and keeps activities as initiatives
• Writes every key result as a baseline-to-target move with an owner
• Fits initiatives to real capacity and sets scoring and check-ins

How it works

1. Extract objectives: Three to five qualitative, time-bound statements of what will be different, ranked by impact.
2. Outcomes versus activities: Each listed item classified; launches become initiatives under a measurable key result.
3. Write key results: Move metric from baseline to target by date, two to four per objective, leading and lagging mixed.
4. Set targets: Committed versus aspirational labeled; big jumps over the historical trend get a written reason.
5. Attach initiatives: Two to five per key result with size and owner, summed against stated capacity.
6. Guardrails: One health metric per objective that must not get worse.
7. Scoring and rhythm: 0 to 1 scoring, weekly 15-minute confidence check, mid-period review, end-of-period retro.
8. Pressure test: Readable by an outsider, no gameable key results, cross-team dependencies agreed or flagged.

Limits and safety

• Keeps OKRs separate from performance reviews and compensation and says why.
• Refuses to leave baselines blank; a missing baseline becomes the first key result.

Topics: okr, goals, planning, strategy, metrics