Simon Lively
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Personal / lab

An AI-assisted environment built around human control.

Bastion explores how context, tools, permissions, and review can work together without granting an assistant unrestricted authority.

Personal / lab:This independent learning project is not presented as client or employer work.

Challenge

AI assistance becomes risky when context is scattered, permissions are broad, and actions are difficult to inspect. The design challenge is to make useful automation possible while keeping boundaries visible and consequential actions reviewable.

Approach

Separate conversation, context, orchestration, and tool execution. Give each action the least capability it needs, preserve an audit trail, and place a human decision before consequential changes.

Architecture

Bastion conceptual architecture A sanitized flow showing the main boundaries in the Bastion pattern. Operator intent and approval Bastion core policy and context Tool gateway scoped actions Reviewed action human-controlled Knowledge layer curated context Audit record evidence
Conceptual architecture only. Operational identifiers, endpoints, credentials, vendors, and private topology are intentionally omitted.

Tools & methods

  • Permission boundaries
  • Context routing
  • Tool adapters
  • Human review
  • Audit trails
  • Progressive automation

What this demonstrates

Systems thinking across AI, identity, automation, privacy, and operations. The value is not a specific model or vendor; it is a control pattern that makes assisted work understandable and reversible.

Privacy by design. This case study describes patterns and decision boundaries only. It does not publish private addresses, credentials, customer data, employer systems, exact inventory, or operational access details.
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