- Talk with the people closest to the work.
- Map tools, handoffs and current constraints.
- Separate reported symptoms from root causes.
- Understand what the team has already tried.
AI Engineering Assessment
Find the bottleneck in your AI-assisted development workflow.
In three weeks, we analyze how AI-generated changes move through context, review, tests and delivery. You leave with evidence of where rework or risk is accumulating and a prioritized 30/90-day plan.
One engineering team Three weeks Scope defined after the fit call
The signal
AI-generated changes are moving faster than review and verification.
Teams add coding tools quickly, while context, tests, review standards and ownership evolve one decision at a time.
What is happening inside your team?
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signals selected
Select the signals you recognize.
How we investigate
Context from your team. Evidence from your engineering workflow.
- Review the agreed repositories and PR history.
- Find recurring patterns in quality and review.
- Ground the diagnosis in real examples.
- Build a plan around the evidence.
What we inspect
Four parts of the development system.
We combine conversations with the team, repository analysis and PR history to identify the bottleneck with the clearest cost or risk.
Context and toolchain
Instructions, repository context, model usage and how engineering knowledge is shared.
Evidence · team interviews and repository analysisDevelopment workflow
PR size, review patterns, CI, handoffs and how AI-generated changes move through the team.
Evidence · PR history and workflow conversationsVerification systems
Tests, evals, review guardrails and the evidence required before changes reach production.
Evidence · repositories, CI and recent changesOwnership and measurement
Access, costs, adoption and quality signals, including who owns each decision.
Evidence · team context and available workflow dataTimeline
Three weeks from symptoms to a plan.
The clock starts after the contract is signed, the questionnaire is completed and access is granted.
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01
Week 1: map and investigate
Output · initial findingsKickoff with engineering leadership, conversations with senior engineers, repository review and PR history analysis.
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Week 2: find the bottleneck
Output · draft scorecardCross-reference evidence with team context, identify root causes and prioritize what is worth fixing.
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Week 3: recommend and align
Output · decision-ready assessmentScorecard, 30/90-day action plan, executive session and written handoff.
What you leave with
Evidence, priorities and a plan your team can execute.
Engineering scorecard
A one-page view of context and toolchain, development workflow, verification, ownership and measurement. Each area includes the evidence we found and the gaps worth addressing.
Prioritized findings
Each finding includes the observed symptom, repository or workflow evidence, likely root cause, cost or risk, and recommended decision.
30/90-day action plan
A sequenced list of actions with a suggested owner and timing. The plan also defines the signal that shows whether each change worked.
Executive session
A 60–90 minute discussion with engineering leadership to align on the findings and next decisions.
Why Kodus
Built by the team that operates Kodus.
Kodus builds open source AI code review without vendor lock-in. The assessment combines direct founder investigation with the engineering experience behind the product.
Trusted by engineering teams at
Who it’s for
A good fit when AI coding is already part of the workflow.
Built for CTOs, VPs of Engineering and Heads of Engineering at companies with roughly 15–100 developers already using tools such as Cursor, Copilot or Claude Code.
- 15–100 developers
- Active use of AI coding tools
- Engineering leader involved
- Access to recent repositories and PR history
- A real quality, review or readiness concern
- Willingness to act on the findings
- Looking for employee performance evaluation
- Looking for a pentest or security audit
- No access to repositories or PR metadata
- No owner or ability to act on the findings
- Expecting full implementation during the assessment
The assessment
Three weeks. One engineering team. A concrete next decision.
The scope is fixed after the fit call, then documented in a proposal. Your team can use the plan internally. Hands-on work is scoped separately if you need it.
What’s included
- Up to three repositories
- Up to six months of PR history
- Two leadership and engineering conversations
- Workflow investigation and repository review
- Scorecard and prioritized findings
- 30/90-day action plan
- Executive delivery session
FAQ
Before we start
Is this a performance evaluation?
No. We analyze engineering systems, code and workflows. We do not score individual developers.
Do you need write access?
No. The assessment starts with read-only access to the agreed repositories and metadata.
Do we need to use Kodus already?
No. Existing Kodus customers may have faster setup, but the assessment can evaluate teams using other AI coding and review tools.
Is this a security audit?
No. We may identify security-related code review patterns, but the assessment does not replace SAST, penetration testing or a dedicated security audit.
Will you implement the recommendations?
Implementation is scoped separately after the assessment. Your team can also execute the plan internally.
When do the three weeks begin?
The assessment starts after the contract, questionnaire and required access are complete.
How much time does our team need?
A kickoff, two focused conversations and the final executive session. Additional questions are handled asynchronously.
Start with evidence
Find the engineering problem worth fixing first.
Bring your repositories, PR history and current concerns. We’ll tell you whether the assessment is a good fit.