Overview
Rolling out Cursor to an engineering team requires more than just distributing licenses. This guide covers the full lifecycle: from initial evaluation through scale-out.
Phase 1: Evaluation & Procurement
#Security Review
Before procurement, your security team will need answers to:
- Data handling: Does code leave your environment? (Answer: Cursor processes code locally; only prompts are sent to AI providers)
- Model providers: Which AI models are used? (Answer: Configurable - OpenAI, Anthropic, or your own)
- SOC2 compliance: Is Cursor SOC2 certified? (Answer: Yes, Type II)
- Data retention: How long is data retained? (Answer: Configurable per organization)
#Procurement Checklist
- ] Request Cursor Business trial
- [ ] Complete security questionnaire
- [ ] Review data processing agreement
- [ ] Negotiate enterprise pricing (volume discounts available at 50+ seats)
- [ ] Set up SSO integration
Phase 2: Pilot Planning
#Choose a Champion Team
Select 5-10 developers for the initial pilot:
- Mix of seniority levels
- Different tech stacks/domains
- At least one security-minded engineer
- Ideally volunteers/enthusiasts
#Define Success Criteria
Before the pilot, agree on what "success" looks like:
- Adoption rate (target: 80%+ daily active users)
- Developer sentiment (NPS or similar)
- Productivity signals (PR cycle time, code review velocity)
- No security incidents
#Set Up Telemetry
Implement usage tracking from day one:
- Daily/weekly active users
- Features used (autocomplete, chat, edit)
- Rejection rate (how often suggestions are dismissed)
Phase 3: Pilot Execution
#Week 1: Onboarding
- Install Cursor for pilot team
- 30-minute kickoff session covering key features
- Distribute prompt template cheatsheet
- Set up Slack channel for questions
#Week 2-3: Active Usage
- Daily check-ins (async)
- Document common issues and workarounds
- Collect feedback on productivity impact
- Monitor telemetry
#Week 4: Evaluation
- Survey pilot participants
- Review telemetry data
- Document learnings and policy adjustments
- Go/no-go decision for broader rollout
Phase 4: Scale-Out
#Phased Rollout
Don't go all-at-once. Recommended phases:
1. Tier 1: Early adopters (10% of org)
2. Tier 2: Mainstream (50% of org)
3. Tier 3: Remaining teams (100%)
#Training Program
- Recorded onboarding session (20 min)
- Role-specific guides (frontend, backend, data)
- Prompt engineering best practices
- Security do's and don'ts
#Policy Enforcement
- Publish AI coding assistant policy
- Add to onboarding checklist
- Include in code review guidelines
- Set up automated guardrails where possible
Common Pitfalls
1. No policy before rollout: Leads to inconsistent usage and security gaps
2. Forcing adoption: Let developers opt-in; forced usage creates resentment
3. No measurement: Can't justify expansion without data
4. Ignoring feedback: Early users surface real issues; listen to them
Next Steps
Ready to execute? Our [Cursor Enablement Sprint
delivers all of this in 2 weeks, including the policy documents, telemetry setup, and onboarding materials.
#
Security Review
Before procurement, your security team will need answers to:
- Data handling: Does code leave your environment? (Answer: Cursor processes code locally; only prompts are sent to AI providers)
- Model providers: Which AI models are used? (Answer: Configurable - OpenAI, Anthropic, or your own)
- SOC2 compliance: Is Cursor SOC2 certified? (Answer: Yes, Type II)
- Data retention: How long is data retained? (Answer: Configurable per organization)
#Procurement Checklist
- ] Request Cursor Business trial
- [ ] Complete security questionnaire
- [ ] Review data processing agreement
- [ ] Negotiate enterprise pricing (volume discounts available at 50+ seats)
- [ ] Set up SSO integration
Phase 2: Pilot Planning
#Choose a Champion Team
Select 5-10 developers for the initial pilot:
- Mix of seniority levels
- Different tech stacks/domains
- At least one security-minded engineer
- Ideally volunteers/enthusiasts
#Define Success Criteria
Before the pilot, agree on what "success" looks like:
- Adoption rate (target: 80%+ daily active users)
- Developer sentiment (NPS or similar)
- Productivity signals (PR cycle time, code review velocity)
- No security incidents
#Set Up Telemetry
Implement usage tracking from day one:
- Daily/weekly active users
- Features used (autocomplete, chat, edit)
- Rejection rate (how often suggestions are dismissed)
Phase 3: Pilot Execution
#Week 1: Onboarding
- Install Cursor for pilot team
- 30-minute kickoff session covering key features
- Distribute prompt template cheatsheet
- Set up Slack channel for questions
#Week 2-3: Active Usage
- Daily check-ins (async)
- Document common issues and workarounds
- Collect feedback on productivity impact
- Monitor telemetry
#Week 4: Evaluation
- Survey pilot participants
- Review telemetry data
- Document learnings and policy adjustments
- Go/no-go decision for broader rollout
Phase 4: Scale-Out
#Phased Rollout
Don't go all-at-once. Recommended phases:
1. Tier 1: Early adopters (10% of org)
2. Tier 2: Mainstream (50% of org)
3. Tier 3: Remaining teams (100%)
#Training Program
- Recorded onboarding session (20 min)
- Role-specific guides (frontend, backend, data)
- Prompt engineering best practices
- Security do's and don'ts
#Policy Enforcement
- Publish AI coding assistant policy
- Add to onboarding checklist
- Include in code review guidelines
- Set up automated guardrails where possible
Common Pitfalls
1. No policy before rollout: Leads to inconsistent usage and security gaps
2. Forcing adoption: Let developers opt-in; forced usage creates resentment
3. No measurement: Can't justify expansion without data
4. Ignoring feedback: Early users surface real issues; listen to them
Next Steps
Ready to execute? Our [Cursor Enablement Sprint
delivers all of this in 2 weeks, including the policy documents, telemetry setup, and onboarding materials.
- ] Request Cursor Business trial
- [ ] Complete security questionnaire
- [ ] Review data processing agreement
- [ ] Negotiate enterprise pricing (volume discounts available at 50+ seats)
- [ ] Set up SSO integration
Phase 2: Pilot Planning
#Choose a Champion Team
Select 5-10 developers for the initial pilot:
- Mix of seniority levels
- Different tech stacks/domains
- At least one security-minded engineer
- Ideally volunteers/enthusiasts
#Define Success Criteria
Before the pilot, agree on what "success" looks like:
- Adoption rate (target: 80%+ daily active users)
- Developer sentiment (NPS or similar)
- Productivity signals (PR cycle time, code review velocity)
- No security incidents
#Set Up Telemetry
Implement usage tracking from day one:
- Daily/weekly active users
- Features used (autocomplete, chat, edit)
- Rejection rate (how often suggestions are dismissed)
Phase 3: Pilot Execution
#Week 1: Onboarding
- Install Cursor for pilot team
- 30-minute kickoff session covering key features
- Distribute prompt template cheatsheet
- Set up Slack channel for questions
#Week 2-3: Active Usage
- Daily check-ins (async)
- Document common issues and workarounds
- Collect feedback on productivity impact
- Monitor telemetry
#Week 4: Evaluation
- Survey pilot participants
- Review telemetry data
- Document learnings and policy adjustments
- Go/no-go decision for broader rollout
Phase 4: Scale-Out
#Phased Rollout
Don't go all-at-once. Recommended phases:
1. Tier 1: Early adopters (10% of org)
2. Tier 2: Mainstream (50% of org)
3. Tier 3: Remaining teams (100%)
#Training Program
- Recorded onboarding session (20 min)
- Role-specific guides (frontend, backend, data)
- Prompt engineering best practices
- Security do's and don'ts
#Policy Enforcement
- Publish AI coding assistant policy
- Add to onboarding checklist
- Include in code review guidelines
- Set up automated guardrails where possible
Common Pitfalls
1. No policy before rollout: Leads to inconsistent usage and security gaps
2. Forcing adoption: Let developers opt-in; forced usage creates resentment
3. No measurement: Can't justify expansion without data
4. Ignoring feedback: Early users surface real issues; listen to them
Next Steps
Ready to execute? Our [Cursor Enablement Sprint
delivers all of this in 2 weeks, including the policy documents, telemetry setup, and onboarding materials.Select 5-10 developers for the initial pilot:
- Mix of seniority levels
- Different tech stacks/domains
- At least one security-minded engineer
- Ideally volunteers/enthusiasts
#
Define Success Criteria
Before the pilot, agree on what "success" looks like:
- Adoption rate (target: 80%+ daily active users)
- Developer sentiment (NPS or similar)
- Productivity signals (PR cycle time, code review velocity)
- No security incidents
#Set Up Telemetry
Implement usage tracking from day one:
- Daily/weekly active users
- Features used (autocomplete, chat, edit)
- Rejection rate (how often suggestions are dismissed)
Phase 3: Pilot Execution
#Week 1: Onboarding
- Install Cursor for pilot team
- 30-minute kickoff session covering key features
- Distribute prompt template cheatsheet
- Set up Slack channel for questions
#Week 2-3: Active Usage
- Daily check-ins (async)
- Document common issues and workarounds
- Collect feedback on productivity impact
- Monitor telemetry
#Week 4: Evaluation
- Survey pilot participants
- Review telemetry data
- Document learnings and policy adjustments
- Go/no-go decision for broader rollout
Phase 4: Scale-Out
#Phased Rollout
Don't go all-at-once. Recommended phases:
1. Tier 1: Early adopters (10% of org)
2. Tier 2: Mainstream (50% of org)
3. Tier 3: Remaining teams (100%)
#Training Program
- Recorded onboarding session (20 min)
- Role-specific guides (frontend, backend, data)
- Prompt engineering best practices
- Security do's and don'ts
#Policy Enforcement
- Publish AI coding assistant policy
- Add to onboarding checklist
- Include in code review guidelines
- Set up automated guardrails where possible
Common Pitfalls
1. No policy before rollout: Leads to inconsistent usage and security gaps
2. Forcing adoption: Let developers opt-in; forced usage creates resentment
3. No measurement: Can't justify expansion without data
4. Ignoring feedback: Early users surface real issues; listen to them
Next Steps
Ready to execute? Our [Cursor Enablement Sprint
Implement usage tracking from day one:
- Daily/weekly active users
- Features used (autocomplete, chat, edit)
- Rejection rate (how often suggestions are dismissed)
Phase 3: Pilot Execution
#Week 1: Onboarding
- Install Cursor for pilot team
- 30-minute kickoff session covering key features
- Distribute prompt template cheatsheet
- Set up Slack channel for questions
#Week 2-3: Active Usage
- Daily check-ins (async)
- Document common issues and workarounds
- Collect feedback on productivity impact
- Monitor telemetry
#Week 4: Evaluation
- Survey pilot participants
- Review telemetry data
- Document learnings and policy adjustments
- Go/no-go decision for broader rollout
Phase 4: Scale-Out
#Phased Rollout
Don't go all-at-once. Recommended phases:
1. Tier 1: Early adopters (10% of org)
2. Tier 2: Mainstream (50% of org)
3. Tier 3: Remaining teams (100%)
#Training Program
- Recorded onboarding session (20 min)
- Role-specific guides (frontend, backend, data)
- Prompt engineering best practices
- Security do's and don'ts
#Policy Enforcement
- Publish AI coding assistant policy
- Add to onboarding checklist
- Include in code review guidelines
- Set up automated guardrails where possible
Common Pitfalls
1. No policy before rollout: Leads to inconsistent usage and security gaps
2. Forcing adoption: Let developers opt-in; forced usage creates resentment
3. No measurement: Can't justify expansion without data
4. Ignoring feedback: Early users surface real issues; listen to them
Next Steps
Ready to execute? Our [Cursor Enablement Sprint
- Install Cursor for pilot team
- 30-minute kickoff session covering key features
- Distribute prompt template cheatsheet
- Set up Slack channel for questions
#
Week 2-3: Active Usage
- Daily check-ins (async)
- Document common issues and workarounds
- Collect feedback on productivity impact
- Monitor telemetry
#Week 4: Evaluation
- Survey pilot participants
- Review telemetry data
- Document learnings and policy adjustments
- Go/no-go decision for broader rollout
Phase 4: Scale-Out
#Phased Rollout
Don't go all-at-once. Recommended phases:
1. Tier 1: Early adopters (10% of org)
2. Tier 2: Mainstream (50% of org)
3. Tier 3: Remaining teams (100%)
#Training Program
- Recorded onboarding session (20 min)
- Role-specific guides (frontend, backend, data)
- Prompt engineering best practices
- Security do's and don'ts
#Policy Enforcement
- Publish AI coding assistant policy
- Add to onboarding checklist
- Include in code review guidelines
- Set up automated guardrails where possible
Common Pitfalls
1. No policy before rollout: Leads to inconsistent usage and security gaps
2. Forcing adoption: Let developers opt-in; forced usage creates resentment
3. No measurement: Can't justify expansion without data
4. Ignoring feedback: Early users surface real issues; listen to them
Next Steps
Ready to execute? Our [Cursor Enablement Sprint
- Survey pilot participants
- Review telemetry data
- Document learnings and policy adjustments
- Go/no-go decision for broader rollout
Phase 4: Scale-Out
#Phased Rollout
Don't go all-at-once. Recommended phases:
1. Tier 1: Early adopters (10% of org)
2. Tier 2: Mainstream (50% of org)
3. Tier 3: Remaining teams (100%)
#Training Program
- Recorded onboarding session (20 min)
- Role-specific guides (frontend, backend, data)
- Prompt engineering best practices
- Security do's and don'ts
#Policy Enforcement
- Publish AI coding assistant policy
- Add to onboarding checklist
- Include in code review guidelines
- Set up automated guardrails where possible
Common Pitfalls
1. No policy before rollout: Leads to inconsistent usage and security gaps
2. Forcing adoption: Let developers opt-in; forced usage creates resentment
3. No measurement: Can't justify expansion without data
4. Ignoring feedback: Early users surface real issues; listen to them
Next Steps
Ready to execute? Our [Cursor Enablement Sprint
Don't go all-at-once. Recommended phases:
1. Tier 1: Early adopters (10% of org)
2. Tier 2: Mainstream (50% of org)
3. Tier 3: Remaining teams (100%)
#
Training Program
- Recorded onboarding session (20 min)
- Role-specific guides (frontend, backend, data)
- Prompt engineering best practices
- Security do's and don'ts
#Policy Enforcement
- Publish AI coding assistant policy
- Add to onboarding checklist
- Include in code review guidelines
- Set up automated guardrails where possible
Common Pitfalls
1. No policy before rollout: Leads to inconsistent usage and security gaps
2. Forcing adoption: Let developers opt-in; forced usage creates resentment
3. No measurement: Can't justify expansion without data
4. Ignoring feedback: Early users surface real issues; listen to them
Next Steps
Ready to execute? Our [Cursor Enablement Sprint
- Publish AI coding assistant policy
- Add to onboarding checklist
- Include in code review guidelines
- Set up automated guardrails where possible
Common Pitfalls
1. No policy before rollout: Leads to inconsistent usage and security gaps
2. Forcing adoption: Let developers opt-in; forced usage creates resentment
3. No measurement: Can't justify expansion without data
4. Ignoring feedback: Early users surface real issues; listen to them
Next Steps
Ready to execute? Our [Cursor Enablement Sprint
Ready to execute? Our [Cursor Enablement Sprint