ACCELERATORS

AI in Engineering Assessment

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

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In good company on the road to agentic AI

Is your engineering organisation ready for agentic AI?

Unsure whether your engineers can work effectively with AI tooling in their daily practice.

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Concerned that code quality will limit what AI tooling can safely do in your systems.

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

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

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

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

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Are your teams ready to work with AI?

Unsure whether your engineers can work effectively with AI tooling in their daily practice.

Is your codebase AI-ready?

Concerned that code quality will limit what AI tooling can safely do in your systems.

Do you have a clear AI roadmap?

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

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platforms structurally ready-1a
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Are your platforms structurally ready?

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

Modernise with confidence

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

Build lasting engineering culture

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

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Built on Codurance’s 13+ years of software craftsmanship expertise and our deep understanding of how AI is reshaping the engineering profession, the AI in 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.

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TRACK 1 – SDLC AGENTIC MATURITY

Is your delivery process AI-ready?

 

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

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TRACK 2 – CODEBASE AI READINESS

How AI-ready is your codebase?

 

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.

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A scored SDLC maturity heatmap across all 8 stages including your current state versus the Codurance target model
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A codebase readiness scorecard covering code quality, test coverage, security posture, documentation, and dependency health
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A gap analysis connecting the two tracks, identifying where AI adoption would be safe today and where it would introduce risk
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A prioritised roadmap across three horizons: what to fix before AI adoption, what to do in parallel, and the path to full agentic development
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Specific, evidenced recommendations grounded in the Codurance Agentic AI Maturity Model, built from real findings, not templates
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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 sessions with key engineering stakeholders.

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STEP 2

Automated assessment

 

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

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STEP 3

SDLC maturity review

 

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

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STEP 4

Collaborative action

 

We present findings, walk through the roadmap together, and agree next steps – whether that is implementation support or a follow-on engagement.

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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?
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Codurance practitioners embedded in your teams to accelerate adoption of agentic practices across the SDLC, stage by stage, safely.
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A structured program to address the codebase readiness gaps, improving test coverage, reducing complexity, and getting your code in shape for AI tooling.
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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.

FAQs

If you can’t find the answer you are looking for here, please contact us

 

Who is this for?
The AI Engineering Assessment is designed for CTOs, VPs of Engineering, and technology leaders who need a clear, evidence-based view of their organisation's readiness for agentic AI and a roadmap to adopt it safely. 
How long does the AI Engineering Assessment take?
Typically two weeks from scope agreement to final report. The assessment runs alongside your normal delivery work with no business interruption. 
What do we receive at the end?
A single structured report containing a scored SDLC maturity heatmap across all eight lifecycle stages, a codebase readiness scorecard, a gap analysis connecting the two, and a prioritised roadmap across three horizons: what to fix before AI adoption, what to do in parallel, and the path to full agentic development.
Why is this assessment important?
The AI in Engineering Assessment is important as it ensures businesses are able to adopt agentic AI safely, with the right guardrails and at scale. 
What happens after the assessment?
The roadmap gives you a clear set of priorities, and Codurance can help you deliver them. We provide targeted modernisation work to fix what's blocking AI adoption, coaching to embed agentic development practices in your teams, and full implementation engagements to execute the roadmap end to end. 
Why Codurance?
Codurance is an ideal partner to deliver this AI in Engineering Assessment as its approach is grounded in software craftsmanship, which is a key approach with embedding Agentic AI safely and at scale. We don’t sell AI tooling, so our findings aren't shaped by a product we want you to buy. The assessment is grounded in 13+ years of software craftsmanship consultancy and evaluates whether your systems and practices can support any agentic tooling safely, not whether you should adopt a particular vendor's product. 

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