Integrated — Eval gates active, AI embedded in SDLC
Ready For Pilot
Vectrix AI is a Series C startup with 28 engineers, currently assessed at
PRISM D1 Level 3.5 (Integrated).
The automated scanner scored 71/100 and the SA interview scored 71/100,
with an org readiness score of 20/20, producing a blended score of 76.8.
The assessment verdict is Ready For Pilot, routing Vectrix AI to
Track C: Accelerated.
71
/ 100
Scanner Score (40%)
71
/ 100
Interview Score (40%)
20
/ 20
Org Readiness (20%)
Scanner Category Breakdown
Category
Score
Progress
Status
AI Tool Config
9 / 10
90%
Spec-Driven Dev
8 / 10
80%
Commit Hygiene
13 / 15
86%
CI/CD Integration
11 / 15
73%
Eval & Quality
7 / 10
70%
Testing Maturity
8 / 10
80%
AI Observability
5 / 10
50%
Governance
1 / 5
20%
Agent Workflows
3 / 5
60%
Platform Reuse
1 / 5
20%
Documentation
3 / 3
100%
Dependencies
2 / 2
100%
Interview Assessment
Section
Score
Status
AI Tooling Landscape
Claude Code deployed via Bedrock across all 5 squads with standardized configuration
CLAUDE.md in every repository, reviewed quarterly
Kiro IDE is the default IDE for 24 of 28 engineers
Custom Claude Code extensions for internal tooling built by platform team
14 / 15
93%
Development Workflow & Specs
Feature specs mandatory for all new work; enforced via PR template
Bug fix and refactor specs adopted by 3 of 5 squads
Spec quality varies -- some are too brief, missing acceptance criteria
Automated spec-to-PR linking in place via GitHub Actions
16 / 20
80%
CI/CD & Quality
GitHub Actions with comprehensive lint, test, build, and security scan steps
Basic eval gate exists but uses threshold of 0 (everything passes)
Test coverage at 81%, well above average
Bedrock Evaluation integration started but not yet gating PRs
15 / 20
75%
Metrics & Visibility
Custom Datadog dashboard tracks commit volumes and deployment frequency
AI-origin trailer data collected but not visualized
No AI acceptance rate or cost-per-commit metrics
Engineering VP reviews velocity metrics weekly but not AI-specific ones
8 / 15
53%
Governance & Security
SOC 2 compliant: strong data handling for production systems
AI governance policy is informal and undocumented
No agent autonomy levels defined -- all engineers have full access
Security review of AI-generated code relies solely on human PR review
No cost controls on Bedrock usage
5 / 15
33%
Org & Culture
CTO leads AI adoption strategy personally
Two dedicated platform engineers focused on developer tooling
Monthly internal AI showcase with cross-team presentations
New hire onboarding includes AI tooling training module
13 / 15
86%
Organizational Readiness
✓Executive Sponsor Identified
✓Dedicated AI Champion
✓Team Willingness
✓Budget Approved
✓Timeline Commitment
Org readiness score: 20/20
Top Strengths
Documentation: 3/3 (100%)
Dependencies: 2/2 (100%)
AI Tool Config: 9/10 (90%)
Gap Analysis & Remediation
Priority
Category
Score
Recommended Action
#1
Governance (scanner)
1/5 (20%)
Create an AI usage governance charter. Define approval workflows for agent autonomy levels. Document data handling policies.
#2
Platform Reuse (scanner)
1/5 (20%)
Audit for reusable AI components. Create a shared prompt library. Establish a pattern catalog for common AI-assisted tasks.
#3
Governance & Security (interview)
5/15 (33%)
Draft an AI governance charter. Address data residency and PII concerns. Define security review requirements for AI-generated code.
Onboarding Recommendation
Track C: Accelerated
Workshop Modules
ID
Module
Rationale
✗
M00
Environment Setup
Already have a working setup
✗
M01
CLAUDE.md & Standards
Already adopted standards
✗
M02
Spec-Driven Development
Already practicing spec-driven dev
✓
M03
CI/CD & Eval Gates
Close eval and quality gaps
✓
M04
Metrics & Dashboards
Deploy advanced observability
✓
M05
Governance & Scaling
Formalize governance for scale
Success Metrics
Metric
Target
Measure By
Top-3 gap category scores
50%+ improvement
Week 4
PRISM D1 level
Reach L3.5+
Week 8
Governance model
Documented and adopted
Week 2
Advanced dashboards
Live with trend data
Week 4
90-Day Roadmap
Timeline
Milestone
Measurable Outcome
Week 1
Gap remediation started
Top-3 gaps have action plans in progress
Week 2
Advanced dashboards deployed
Custom views live with trend analysis
Week 4
Midpoint checkpoint passed
Top-3 gaps improved 50%+
Week 8
L3.5+ achieved, pilot complete
Re-assessment confirms L3.5+
Week 12
L4 transition ready
Track D architecture review scheduled
SA Engagement Cadence
Week
Type
Duration
Agenda
Week -1
Async prep
15 min (Slack)
Share gap analysis, confirm workshop focus areas
Week 0
Targeted workshop
2 hr
Deliver Modules 03-05 with gap-specific exercises
Week 2
Video call
30 min
Verify gap remediation progress, review dashboards
Week 4
Checkpoint call
45 min
Midpoint review, gap score improvements, adjust plan
Week 8
Pilot readout call
1 hr
Final readout, L3.5+ confirmation, L4 transition plan