OKR Planning Document Assistant
You get AI help to write, review, and format OKR planning documents
What It Does
AI acts as an OKR planning specialist that helps you create well-structured Objectives and Key Results following industry best practices.
What is OKR Planning?
OKRs (Objectives and Key Results) are a goal-setting framework used by organizations to define measurable goals and track their outcomes:
- Objective: Qualitative, inspiring, time-bound goal (e.g., "Become the fastest checkout experience in e-commerce")
- Key Results: 3-5 quantitative, measurable outcomes that prove the Objective was achieved (e.g., "Reduce checkout time from 4 minutes to 90 seconds")
What AI helps with:
- Writing OKRs: Generate well-structured OKRs from project context
- Reviewing OKRs: Check if Objectives are qualitative and Key Results are measurable
- Improving clarity: Ensure KRs have specific metrics (numbers, percentages, completion status)
- Alignment validation: Verify Key Results actually measure progress toward the Objective
- Format compliance: Follow OKR best practices (ambitious yet achievable, SMART criteria)
Common OKR Mistakes AI Catches:
- ❌ Objective is too vague: "Improve the product" → ✅ "Deliver the most intuitive user onboarding experience"
- ❌ Key Result has no metric: "Better performance" → ✅ "Reduce API response time from 500ms to 100ms"
- ❌ KR doesn't measure the Objective: Objective about "user satisfaction" with KRs about "lines of code written"
What AI does NOT do:
- Set your business goals (you define what matters)
- Decide your priorities or strategy
- Replace stakeholder alignment discussions
Think of it as an OKR coach that ensures your goals follow the framework correctly.
StrategyRadar Notes
AI helps with structure and clarity, but you remain responsible for setting meaningful, aligned goals that drive your business forward.
Prompts
Review OKRs for Clarity and Measurability
You are an OKR planning expert. I will share my OKRs with you, and you will review them and provide feedback on structure, clarity, and format.
**Your role is to:**
- Analyze the structure and format of the OKRs I provide
- Give feedback on clarity and measurability
- Suggest improvements to formatting and wording
- Help me refine what I've already written
**You should NOT:**
- Invent new objectives or key results
- Change the intent or meaning of my OKRs
- Make strategic decisions about what goals I should have
**Review these aspects:**
1. **Objectives Quality**:
- Are objectives qualitative and inspiring?
- Do they clearly describe desired outcomes?
2. **Key Results Quality**:
- Are key results quantitative and measurable?
- Do they have clear metrics (numbers, percentages, completion status)?
- Can success/failure be objectively determined?
3. **Alignment**:
- Do the Key Results actually measure progress toward the Objective?
- Is there any mismatch between what the Objective says and what Key Results measure?
**Provide feedback in this format:**
- **Objective Analysis**: [Your assessment]
- **Key Results Analysis**: [Your assessment for each KR]
- **Recommendations**: [Specific suggestions for improvement]
- **Improved Version**: [Your rewritten version with better structure/clarity, keeping my original intent]
Please wait for me to share my OKRs.Resources
Related AI Capabilities
Conventional Planning
Project planning as the baseline approach, completely human-driven. This encompasses defining **project scope** (goals, deliverables, success criteria), **resource planning** (team structure, timelines, budgets), and **work organization** (epics, milestones, roadmaps). You can plan using different approaches depending on your context: traditional waterfall (detailed upfront planning), iterative/agile methods (continuous adaptation), or hybrid approaches. Each has its place depending on project constraints, industry regulations, and team dynamics. ## Common Approach Today: Iterative Planning The most common practice in software development today emphasizes **short-term cycles** and **continuous adaptation**. Teams plan in sprints or iterations (typically 1-6 weeks), allowing them to incorporate real feedback and adjust course quickly. The key is creating _just enough plan to start_, then evolving it based on what you learn. This approach includes: - **Short-term planning cycles** - Sprint planning (1-4 weeks) - Iteration planning (2-6 weeks) - Release planning with flexible scope - **Feedback loops from other phases** - **Analysis:** Validate requirements through stakeholder discovery - **Design:** Test feasibility with architecture spikes - **Coding:** Learn from MVPs, prototypes, and proof-of-concepts - **Continuous adaptation** - Adjust priorities based on user feedback - Refine scope as you discover new information - Embrace uncertainty instead of fighting it - **Validation and alignment** - Regular planning reviews with stakeholders - Feasibility and capacity checks - Team alignment meetings _See the Resources section below for recommended books and guides on planning practices._
Planning Framework Recommendations
Ask the AI agent for ideas and inspiration on suitable **project planning frameworks** based on your context. Share basic information about your project—team size, timeline constraints, how stable your requirements are, industry regulations—and ask the agent what planning approaches might work well for your situation. ## Why This Matters: Choosing the wrong planning framework can waste time and frustrate your team. A lightweight approach like Kanban might be perfect for a small startup but chaotic for a regulated enterprise. Waterfall might work great for fixed-scope contracts but be too rigid for R&D projects. The AI helps you explore options by considering: - Your project's complexity and how much change you expect - Your team's size, work style, and organizational culture - Industry constraints (documentation requirements, audit trails) - Budget and timeline pressures ## Examples of Common Scenarios: - **"We're a 5-person startup building an MVP with unclear requirements"** → AI might suggest Kanban or Shape Up - **"Enterprise project with 50+ people across multiple departments"** → AI might suggest SAFe or structured Scrum - **"Healthcare app with strict regulatory requirements"** → AI might suggest plan-driven approaches with strong documentation - **"Fixed-price contract with clear deliverables and deadline"** → AI might suggest Waterfall or Critical Path The AI explains trade-offs and why certain frameworks fit your context, but **you decide** what works for your team and culture. _Check the prompt below to see how to structure your question._
Project Planning Assistance
AI assists in project planning and scope definition at the project level. Works between projects and requires: • Organizational context • Team structure • Current assignments • Resource availability