Agent security6 MIN READ
Running an AI-agent incident tabletop exercise
A useful tabletop follows one plausible agent failure through detection, containment, evidence, business recovery and accountable return to service.
THE SOFTLANDER BLOG
Agentic AI insights: security, evaluation and governance for AI agents
The next move. Considered. Ideas for the people turning agentic AI into real work: strategy, systems and the evidence behind better decisions.
Latest perspectives
123 articlesImpact measurement6 MIN READ
How to estimate the cost of an agent failure
Model concrete failure scenarios across detection, containment, correction, disruption and consequence, then use ranges to choose controls.
Agent security6 MIN READ
Testing an agent’s network-egress boundary
“Internet access” is too broad a permission for an agent. Define destinations, protocols, data-release rules and failure behaviour, then test bypasses against the deployed network path.
Governance & privacy6 MIN READ
The board’s questions about AI agents should begin with authority
Boards do not need to review prompts or model scores. They need a clear account of what each agent may do, whose mandate it carries and how control is recovered.
Architecture & engineering6 MIN READ
Agentic AI in manufacturing maintenance
Maintenance agents can turn condition signals into coordinated work, but plant safety and control demand bounded action and field verification.
Evaluation & assurance6 MIN READ
How to design a joint AI evaluation lab
A joint lab should be a governed way to create decision evidence across organisations, with shared methods but explicit ownership of systems, data and conclusions.
Strategy & transformation6 MIN READ
What public-sector buyers should request from an agent supplier
Buy evidence, controllability and lifecycle obligations—not a confident demo or an unrestricted promise of autonomy.
Architecture & engineering6 MIN READ
Why durable agent workflows need explicit state
Long-running agent work cannot rely on a transcript and hopeful retries. Explicit state makes progress, authority, recovery and completion inspectable across failures.
Evaluation & assurance6 MIN READ
Product acceptance criteria for non-deterministic systems
Accept an agent against outcome distributions, critical invariants and recovery evidence—not one scripted response or an average score.
Impact measurement6 MIN READ
The hidden total cost of operating an AI agent
Model usage is one line in a wider cost stack that includes integration, evaluation, control, human work, incidents, change and exit.
Cryptographic engineering7 MIN READ
Cryptographic agility is an interface problem
Agility is not a property of the algorithms you chose. It is a property of how your code, your data formats and your protocols name them—and whether anything can change without a coordinated rewrite.
Evaluation & assurance6 MIN READ
Ten artefacts that make an AI-agent decision reviewable
Reviewable agent decisions depend on a small chain of artefacts connecting workflow purpose, authority, configuration, evidence, findings, controls and ownership.
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Start with the questions that shape a better decision.
Which enterprise agent questions does the Softlander blog examine?
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.
Who are the articles written for?
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.
How do the articles relate to Softlander’s services?
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.