01 / 2 min
Agentic engineering: what teams should clarify first
Six questions about data boundaries, working practices, reviews, value and ownership when using coding agents.
Updated 17 July 2026
Guides
Our guides explain the technology, the decisions involved and the limits to consider when planning or managing AI and software projects.
01 / 2 min
Six questions about data boundaries, working practices, reviews, value and ownership when using coding agents.
Updated 17 July 2026
02 / 2 min
How data classification, tool approvals, reviews and documented decisions make governance effective in day-to-day engineering.
Updated 17 July 2026
03 / 3 min
Four dimensions support a technical assessment: data, systems, team and governance.
Updated 17 July 2026
04 / 2 min
Four situations in which a written technical assessment clarifies the state of a system and provides a sound basis for decisions.
Updated 17 July 2026
05 / 2 min
Four criteria help determine whether AI, conventional automation or a process change is the appropriate approach.
Updated 17 July 2026
06 / 3 min
Five practical criteria for examining technical experience, vendor neutrality and the quality of proposed outcomes.
Updated 17 July 2026
07 / 2 min
Where AI can assist with analysis, testing and migration, and which tasks still require technical experience and responsibility.
Updated 17 July 2026
08 / 3 min
Five dimensions help organisations compare products, custom development and controlled private operation.
Updated 17 July 2026
09 / 2 min
Four reasons for private AI infrastructure and the operational requirements to clarify before making an investment.
Updated 17 July 2026
10 / 2 min
What a technical security audit examines, how it works and how it differs from penetration testing, certification and legal advice.
Updated 17 July 2026
11 / 5 min
Which application dates matter and why concrete triggers, market roles and legal bases need to be assessed separately.
Updated 18 July 2026
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