OKR Generator
Generate well-structured OKRs (Objectives and Key Results) with measurable outcomes aligned to company strategy.
The Prompt
(2 messages)You are an OKR coach who helps teams set ambitious but achievable objectives and measurable key results. OKR rules: - **Objectives**: Qualitative, inspiring, action-oriented. What do you want to achieve? - **Key Results**: Quantitative, measurable, time-bound. How will you know you achieved it? - Each objective should have 2-4 key results - Key results should be outcomes (not tasks) — "Reduce API latency to <200ms" not "Optimize database queries" - Use the 70% rule: if you achieve 70% of your KRs, the OKR was well-calibrated - KRs should be independently measurable — no "and" connecting two metrics Guidelines: - Align OKRs to the stated company/team priorities - Include a mix of ambitious (stretch) and achievable KRs - Make sure KRs don't incentivize gaming (e.g., "increase signups" without quality)
Generate OKRs: Team/role: {{team}} Time period: {{period}} Company priorities: {{priorities}} Context: {{context}}
Variables
Fill in these inputs to customize your output:
{{team}}Example: Platform Engineering Team (6 engineers)
{{period}}Example: Q2 2026
{{priorities}}Example: Improve developer experience, reduce incident frequency, prepare infrastructure for 10x traffic growth
{{context}}Example: Currently handling 50K requests/min. Had 4 P1 incidents last quarter (2 were database-related). Deploy pipeline takes 25 minutes. Team just adopted Kubernetes.
Example Output
Here's what this prompt generates with the sample inputs:
{
"okrs": [
{
"objective": "Make our infrastructure reliable enough that on-call engineers sleep through the night",
"key_results": [
{
"kr": "Reduce P1 incidents from 4 per quarter to 1 or fewer",
"current": "4 P1 incidents in Q1",
"target": "1 or fewer in Q2",
"measurement": "PagerDuty incident count filtered by severity"
},
{
"kr": "Achieve 99.95% API uptime (up from 99.8%)",
"current": "99.8%",
"target": "99.95%",
"measurement": "Uptime monitoring dashboard (monthly)"
},
{
"kr": "Implement automated database failover with <30s switchover time",
"current": "Manual failover (~15 min)",
"target": "Automated, <30 seconds",
"measurement": "Failover drill results (run monthly)"
}
]
},
{
"objective": "Make deploying code feel instant and safe",
"key_results": [
{
"kr": "Reduce deploy pipeline time from 25 minutes to under 8 minutes",
"current": "25 minutes",
"target": "<8 minutes",
"measurement": "CI/CD pipeline duration (p50)"
},
{
"kr": "Ship canary deployment capability — 100% of production deploys use canary by end of quarter",
"current": "0% (all deploys are full rollout)",
"target": "100% canary",
"measurement": "Deployment logs showing canary stages"
}
]
},
{
"objective": "Prove we can handle 10x traffic before we need to",
"key_results": [
{
"kr": "Pass load test at 500K requests/min with p99 latency under 500ms",
"current": "50K req/min (10x not tested)",
"target": "500K req/min, p99 <500ms",
"measurement": "Quarterly load test results"
},
{
"kr": "Implement auto-scaling for all stateless services with <60s scale-up time",
"current": "Manual scaling",
"target": "Auto-scaling, <60s",
"measurement": "Kubernetes HPA metrics during load tests"
},
{
"kr": "Reduce infrastructure cost per 1K requests by 30% through right-sizing",
"current": "Current cost/1K requests baseline",
"target": "30% reduction",
"measurement": "Cloud billing normalized by request volume"
}
]
}
]
}Configuration
Optimized settings included when you add this prompt. You can adjust them later.
Provider
ANTHROPIC
Model
claude-sonnet-4-5
Temperature
0.4
Output
Structured JSON
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