FEATURED / 7 MIN READ
What should trigger an agent governance review?
Review should follow material changes in purpose, authority, data, users, dependencies, evidence or incidents—not an arbitrary calendar alone.
The next move. Considered. Ideas for the people turning agentic AI into real work: strategy, systems and the evidence behind better decisions.
FEATURED / 7 MIN READ
Review should follow material changes in purpose, authority, data, users, dependencies, evidence or incidents—not an arbitrary calendar alone.
EDITOR-CURATED
An agent can only be evaluated in the context of what its tools allow. Examine identity, delegated authority and action boundaries before you put a workflow in motion.
A release decision needs a traceable connection between expected behaviour, test conditions and observed results. Here is a practical way to build that connection.
A compelling demo leaves important questions open. Use a five-dimension rubric to examine the data, authority, evidence, ownership and people behind your next agent initiative.
A retrieval system should establish the active principal and filter authorised resources before similarity ranking or model context assembly.
A computer-use agent treats pixels, accessibility data and interface state as both evidence and an action surface. Security must bind intent to effects beyond the screen.
A list of AI ideas is not an operating plan. Define the work, decisions, authority and evidence before deciding whether an agent belongs in the workflow.
Production readiness for an AI agent spans workflow requirements, system identity, evaluation, recovery and operations—not just a working model endpoint.
Legal agents can organize evidence and prepare work, but professional judgement, client authority and verified legal positions cannot be delegated by interface.
A safe handoff transfers the decision, evidence, current state and bounded authority—not a transcript dump or a vague request for someone to take over.
Openness can improve inspectability, control and portability, but only when an organisation can own the supply chain, operation and evidence it inherits.
Classify AI by the action path it creates, not the label on the product. The distinction determines ownership, controls, evaluation and release evidence.
A wrong answer is the final symptom of failures that may begin with source coverage, access control, parsing, retrieval, context assembly, generation or action.
KEEP EXPLORING
Read the method, assumptions and questions to ask.
A little more clarity
Start with the questions that shape a better decision.
The blog examines where agents create business value, how teams define release evidence, how authority and tool access should be bounded, and how engineering, security and governance owners can make a shared decision.
They are written for product, engineering, AI platform, security, governance and transformation leaders responsible for moving an agent workflow from idea or pilot towards accountable operation.
Articles explain the problems and decision methods behind the consultancy’s service direction. They are educational material and do not replace a scoped review of an organisation’s actual system.