always-on-agent-applications

What problem does it solve?

Many teams build always-on agent infrastructure but struggle to identify high-value, launchable applications that justify the cost and complexity of persistence and episodic memory. This Skill helps translate architecture into concrete product workflows, prioritizing ROI, scope boundaries, and safe proactive behavior so teams avoid scope creep, cost creep, and privacy drift.

Core Features & Use Cases

• Decision tree for persistence: Step-by-step criteria to decide when to build an always-on agent versus a session-based solution, including an ROI threshold and narrowing heuristics.
• Application patterns and triggers: Mapped use cases (developer companion, personal chief of staff, learning journal, health observer, ambient intelligence) with recommended triggers, memory strategy, and quality gates.
• Failure modes and mitigations: Practical checks for hallucinated memories, memory pollution, cost creep, scope drift, and privacy boundary leaks plus concrete fixes and monitoring signals.
• Worked example: A complete PR-description developer companion example covering ROI math, memory scopes, triggers, and launch readiness criteria.

Quick Start

Ask the agent what high-ROI persistent assistant you should build for your workflow, and include suggested scope, triggers, memory strategy, and an ROI estimate.