Background Workers & Autopilots
Auto-triggered workers, autopilot modes, continuous execution loops, event-driven architectures, and methodology-as-plugin (SPARC, ADR, DDD).
Audit and Optimize Workers
Audit workers continuously inspect recent agent activity (commits, edits, decisions) for regressions, anti-patterns, or risks; optimize workers proactively rewrite code, prompts, or configurations toward measured improvements — together they form the most-cited concrete example of the background-worker pattern.
Autopilot Modes
Autopilot modes let the harness run an agent without per-action user confirmation — bounded by a budget (tokens, time, steps), gated by permission scopes, monitored by background workers, and ended by an explicit checkpoint where the user reviews — they are the UX surface that makes long-horizon agentic work practical.
The Background Worker Pattern
Background workers are agents the harness runs between user turns — auditing recent changes, optimizing code, looking for test gaps, refreshing memory — without requiring the user to ask, and they are one of the most important emerging patterns in 2026 harnesses.
Continuous Execution Loops
A continuous-execution loop runs an agent indefinitely against a stream of tasks, events, or goals — distinct from a “session” that has a start and end — and is the runtime model that supports background workers, autopilot, federated agents, and always-on agentic services.
Event-Driven Harness Architectures
An event-driven harness reacts to events — file changes, GitHub webhooks, build completions, schedule triggers — by invoking the agent loop without a user typing anything; this architecture turns a user-driven harness into an autonomous service and is the substrate for background workers, autopilot, and federated coordination.
Methodology as Plugin: ADR and DDD
Architecture Decision Records (ADR) and Domain-Driven Design (DDD) are the two most-cited “discipline” methodologies in software engineering; ruflo packages each as a plugin (ruflo-adr, ruflo-ddd) so the discipline becomes a slash command rather than a team practice.
Methodology as Plugin: SPARC
SPARC (Specification, Pseudocode, Architecture, Refinement, Code) is an agent-driven engineering methodology packaged as a ruflo plugin (ruflo-sparc) — it is the cleanest example of how a software methodology can be encoded as a multi-step agent workflow, not just adopted as a habit.
Testgap and Coverage Workers
A testgap worker continuously identifies code without test coverage and proposes (or generates) tests; coverage workers track what’s covered and aren’t, surface deltas after each session, and prevent slow erosion of test quality — among the highest-leverage background workers because the work they do is something humans skip under time pressure.