TECH Signal 308
Software factory pattern loops on broad goals and audits Linear projects
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An agent skill audits Linear projects for goal definitions, metrics and missing tools, then drives work on non-blocked tasks until completion, then repeats.
The pattern forces explicit goal tracking and metric visibility, preventing missed adoption signals after releases and reducing manual oversight. It also surfaces hidden state dependencies in development workflows.
Written by elseif from the cluster below · every claim links back to a sourceThe three things worth knowing
Agent audits Linear projects for goal definitions, metrics and missing tools before starting work.
It iterates on tasks, updates issue state and adds new work until the project description is fresh.
Post-release monitoring catches adoption spikes or error rate changes that might otherwise be missed.
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What the cluster adds up to.
The software factory pattern introduces a loop that starts with auditing a Linear project's goal definition, metrics and supporting tools before any work begins.
Adoption requires integrating Datadog MCP, Snowflake queries and Linear as the single source of work state, and relies on an orchestrated harness to execute tasks independently of a developer's laptop.
The approach surfaces hidden state hoarding by compelling the system to evaluate whether goals are being met, compelling engineers to make implicit assumptions explicit.
Written by elseif from the cluster below · checked for specifics the sources never containedTHE CLUSTER