Cluster 01
AI Software Engineering
How AI-assisted development fits into a robust engineering process.
Engineering Library
Knowledge for teams that have to answer for AI.
No blog, no news. 24 articles on AI-assisted software development, regulated development environments, validation, MCP and controlled delivery – written for the people who will have to answer for the results.
Our standard
- Every article answers a concrete question – useful even without any interest in the product.
- Regulatory statements rest on primary sources, not on SEO blogs.
- Limits and trade-offs are named, not left out.
Start here
Three articles that frame the field.
The three pillar articles describe the field from the tooling level up to validation. Once you have read them, you can pick the later deep dives deliberately.
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01 · AI Software Engineering
AI in software development: from coding agent to engineering process
What AI reliably delivers in development today, where code generation ends and which engineering steps it does not remove.
Pillar · approx. 11 min.
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02 · Regulated Engineering
AI in regulated software development: speed without losing control
Requirements, architecture, review, tests, traceability, change control and release evidence – and what AI coding actually shifts among them.
Pillar · approx. 10 min.
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03 · GxP & Validation
GxP software development: requirements, validation and traceability
Intended use, a risk-based approach, validation planning, audit trails and the question of how much of that a platform can cover at all.
Pillar · approx. 10 min.
After that
The further deep dives go into individual steps – from traceability and evidence by design through MCP security to OpenAPI, CI/CD and on-premise operation. All 24 articles are sorted by topic cluster: see the overview.
Topic clusters
Six fields, one context.
The library is built along fixed clusters. Each cluster has one overview article and several deep dives – from the basics through to concrete technical implementation.
Cluster 02
Regulated Engineering
Traceability, evidence and change control in projects with elevated requirements.
- AI in regulated software development: speed without losing control Cluster pillar article
- Traceability in software development: from requirement to release Deep Dive
- Evidence by design: producing evidence before the project ends Deep Dive
- What does “validatable software development” mean? Deep Dive
- ISO and software development: what a standard really certifies Deep Dive
Cluster 03
GxP & Validation
Intended use, risk-based validation, audit trails and electronic records in the development process.
- GxP software development: requirements, validation and traceability Cluster pillar article
- GAMP 5 in modern software projects Deep Dive
- Software validation under GxP: what teams have to evidence Deep Dive
- Audit trails in GxP systems: technical and organisational requirements Deep Dive
- AI and GxP: keeping AI-assisted development controllable Deep Dive
Cluster 04
MCP & Agentic Development
How AI agents access development tools through defined interfaces – and where the permission boundary should sit.
Cluster 05
Architecture & Delivery
What has to stay explicit despite code generation – from the API as a contract to your own pipeline.
- Software architecture in the AI era Cluster pillar article
- OpenAPI as the contract between AI-generated frontend and backend Deep Dive
- CI/CD for AI-assisted software development Deep Dive
- On-premise AI software development: control over code, models and delivery Deep Dive
- Platform instead of boilerplate: what should be reusable in client projects Deep Dive
Cluster 06
AI Governance & Security
Rules instead of bans: how teams steer, review and secure the use of AI in engineering.
Editorial
How these articles are written.
Regulatory topics do not tolerate marketing language. That is why fixed rules apply to this section.
Primary sources first
Core regulatory statements rest on official documents – EudraLex, FDA, EUR-Lex, standards bodies – not on secondary blogs. Every affected article lists its sources visibly.
No legal or compliance advice
The texts explain technical and procedural relationships. They replace neither a regulatory assessment nor the responsibility of your own quality organisation.
Limits are named
Where a platform – CodamAI included – can only support a process step rather than take it over, the text says so. No automatic compliance, no automatic validation.
Regular review
Regulatory content is reviewed at least every six months and whenever relevant standards or laws change. The review date is stated at the top of each article.
From theory into your setup.
If the questions raised in these articles are real in your projects, the next step is not a white paper but a technical conversation about stack, delivery and evidence obligations.