Data minimisation for agents that always want more context
Better agent context is not the largest possible context. It is the smallest authorised, relevant and timely data set that supports the task.
Softlander blog perspectives published in April 2026.
Better agent context is not the largest possible context. It is the smallest authorised, relevant and timely data set that supports the task.
Self-modification turns runtime learning into controlled software change. Separate what may adapt, require evidence for promotion and preserve a recoverable baseline.
Live agents cut across product, operations, risk and technology. One accountable service owner needs explicit decision rights supported by named control owners.
A logistics agent earns trust when data becomes late, routes close and plans conflict—not when everything follows the timetable.
Stopping one process may leave tools, queued actions, delegated agents and credentials active. Define the safe state, control every action path and rehearse the stop under load.
Key exchange migration is largely a configuration change. Signature migration runs into certificate sizes, fixed-width image headers, verifiers you cannot update and archives that must stay verifiable for decades.
Audit committees can oversee AI through ownership, control evidence, reporting integrity and assurance scope without turning meetings into model-architecture tutorials.
Inject realistic faults, verify state and judge the recovery path. A retry that finishes the task can still duplicate work or hide uncertainty.
Administrative agents can reduce coordination work, but clinical meaning and patient access can enter the workflow sooner than the label suggests.
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