ACCELERATORS

AI in Engineering Assessment

Understand how ready your software delivery lifecycle and codebase are for agentic AI, and get a prioritised roadmap showing exactly what needs to change to adopt it safely and at scale.

AI and Engineering Assessment

Is your engineering organisation ready for agentic AI?

Unsure whether your engineering teams are ready to work effectively with AI?

Want to move faster with AI in software delivery but don't know where to start?

Concerned that the quality of your codebase will limit what AI tooling can safely do?

Need a clear business case for investing in agentic development practices?

Worried your competitors are pulling ahead by adopting AI in their engineering?

Struggling to know whether your platforms are structurally ready for AI agents to work within them reliably?

Built on Codurance’s 13+ years of software craftsmanship expertise and our deep understanding of how AI is reshaping the engineering profession, the AI Engineering Assessment gives you an evidence-based picture

of your current state and a clear, prioritised path to enterprise-grade agentic development.

WHAT WE ASSESS

Two assessment tracks. One complete picture.

The assessment runs two parallel tracks simultaneously, examining your delivery process and your codebase together, because both must be ready before AI adoption is safe at scale.

TRACK – SDLC AGENTIC MATURITY

How AI-ready is your delivery process?

 

We score your software delivery lifecycle across eight stages against the Codurance Agentic AI Maturity Model – from planning and design through to deployment and governance.

  • AI adoption across all 8 SDLC stages scored
    0–4
  • Human oversight and governance practices
  • Agent loop maturity and self-reinforcement
  • Tooling landscape assessment (Claude Code, Sonnet, Codex)
  • Gap analysis against the Codurance preferred agentic model
TRACK 2 – CODEBASE AI READINESS

How AI-ready is your delivery process?

 

We analyse your codebase directly - identifying the structural characteristics that determine whether AI tooling can operate within it safely, reliably, and without compounding technical debt.

  • Code quality, complexity, and naming clarity
  • Test coverage and mutation score
  • Documentation and architectural boundary definition
  • Security posture and dependency health
  • AI interpretability; how well agents can reason about the code

ASSESSMENT OUTPUT

A clear picture. A prioritised plan.

You receive a single structured report that is evidence-based, specific, and actionable. Not a generic set of recommendations, but a gap analysis and roadmap built from what we actually found in your systems.

  • A scored SDLC maturity heatmap across all 8 stages including your current state versus the Codurance target model

  • A codebase readiness scorecard covering code quality, test coverage, security posture, documentation, and dependency health

  • A gap analysis connecting the two tracks, identifying where AI adoption would be safe today and where it would introduce risk

  • A prioritised roadmap across three horizons: what to fix before AI adoption, what to do in parallel, and the path to full agentic development

  • Specific, evidenced recommendations grounded in the Codurance Agentic AI Maturity Model, built from real findings, not templates

SQA page_report img

HOW IT WORKS

A seamless assessment with no business interruption

Four steps to a clear understanding and agentic AI roadmap, typically completed in two weeks.

  • Step 1

    Scope and access

    We agree which platforms and teams are in scope, establish access to your source control and toolchain, and schedule practitioner sessions with key engineering stakeholders.

  • Step 2

    Automated assessment

    Our AI-powered assessment engine analyses your codebase simultaneously across both tracks, producing scored findings on code quality, test coverage, security posture, documentation, and dependency health.

  • Step 3

    SDLC maturity review

    Our Principal Craftspeople conduct structured interviews and toolchain reviews, scoring each stage of your delivery lifecycle against the Codurance Agentic AI Maturity Model.
  • Step 4

    Collaborative Action

    Work with our team to implement the recommendations and track progress.

Want a plan to act on the findings?

Short of time? Don't have the in-house expertise to close the gaps the assessment identifies?

Post-assessment, Codurance can work with you to implement the roadmap, embedding AI champions in your teams, modernising the codebase, and upskilling your engineers in the craft disciplines that make agentic AI work safely. You'll move from assessment to measurable progress faster than you could working alone.

TYPICAL NEXT ENGAGEMENTS

Embedded AI champions

Codurance practitioners embedded in your teams to accelerate adoption of agentic practices across the SDLC, stage by stage, safely.

Software modernisation program

A structured program to address the codebase readiness gaps, improving test coverage, reducing complexity, and getting your code in shape for AI tooling.

Engineering craftsmanship coaching

Targeted coaching and training to build the craft disciplines in your engineering teams that agentic AI depends on including clean code, meaningful tests, collective ownership.

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