System NotesXendai / Technical publication
We write about designing, building and operating AI inside real businesses: architecture, agents, automation, knowledge, models, evaluation and operations.
Notes from the system.Field notes from building systems — not weekly AI news, prompt lists or model summaries on a schedule.
Model selection becomes meaningful once the work is understood. This Note examines how to define outcomes, constraints, and acceptance criteria before comparing capabilities, and why that definition should evolve with evidence from early tests.
Read the note →Automation can accelerate an activity while leaving the waits, reviews, and handoffs that constrain its outcome unchanged. This Note explains why processes need state, acceptance conditions, and responsibility, and how to recognize improvement without automating everything.
Read the note →An agent's autonomy is a delegation with conditions. This Note examines consequences, effective permissions, meaningful human review, and revocation to explain where that delegation should end and what evidence can justify extending it.
Read the note →Production begins when someone depends on a system for real work. This Note examines the service commitment that follows, from dependencies and traceable changes to continuity and ownership, with engineering rigor proportionate to the dependency created.
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