Radar turns SkillFM’s four loops into source-backed content: manage agent state, save token cost, learn reusable workflows, and turn judgment into earning assets.
This weekly long read compresses manage, save, learn, and earn into reusable content rules for the next batch.
Prompt hygiene, tools, context, and asset health.
Remove repeated context and find lighter execution paths.
Turn one useful run into a workflow your agent can reuse.
Turn judgment into pages people can search, subscribe to, and reuse.
The agent is not slow. It is rereading an old rule block every day.
When durable rules, reusable workflow, and one-off input live in one prompt block, every run rereads context that should have stayed stable.
Audit prompt drift before swapping models. The thing worth caching is the stable rule set your team actually manages.
The agent is not slow. It is rereading an old rule block every day.
When durable rules, reusable workflow, and one-off input live in one prompt block, every run rereads context that should have stayed stable.
Audit prompt drift before swapping models. The thing worth caching is the stable rule set your team actually manages.
The agent is not slow. It is rereading an old rule block every day.
When durable rules, reusable workflow, and one-off input live in one prompt block, every run rereads context that should have stayed stable.
Audit prompt drift before swapping models. The thing worth caching is the stable rule set your team actually manages.
The agent is not slow. It is rereading an old rule block every day.
When durable rules, reusable workflow, and one-off input live in one prompt block, every run rereads context that should have stayed stable.
Audit prompt drift before swapping models. The thing worth caching is the stable rule set your team actually manages.
The agent is not slow. It is rereading an old rule block every day.
When durable rules, reusable workflow, and one-off input live in one prompt block, every run rereads context that should have stayed stable.
Audit prompt drift before swapping models. The thing worth caching is the stable rule set your team actually manages.
The agent is not slow. It is rereading an old rule block every day.
When durable rules, reusable workflow, and one-off input live in one prompt block, every run rereads context that should have stayed stable.
Audit prompt drift before swapping models. The thing worth caching is the stable rule set your team actually manages.
The agent is not slow. It is rereading an old rule block every day.
When durable rules, reusable workflow, and one-off input live in one prompt block, every run rereads context that should have stayed stable.
Audit prompt drift before swapping models. The thing worth caching is the stable rule set your team actually manages.
The agent is not slow. It is rereading an old rule block every day.
Many teams blame the model when AI gets expensive. The first thing to inspect is whether the agent rereads a drifting block of old rules every day.
Audit prompt drift before swapping models. The thing worth caching is not a magic prompt. It is a stable rule set your team actually manages.