Deep Dive 1
Inside the Planner: How Claw Agents Decide Between Search and Execution
A close look at the decision boundary that separates low-risk lookup steps from high-impact mutating operations.
By Research Desk
|9 min read
|Filed February 12, 2026
The Decision Boundary
Claw planning now scores each task on reversibility, financial impact, and freshness risk before selecting a tool path.
When freshness risk crosses threshold, agents must fetch current sources even if prior memory appears sufficient.
Execution First, Not Explanation First
Teams reported that throughput improved when agents moved from long proposal messages to concrete tool calls and incremental validation.
The planner still emits concise rationale, but defaults to implementation once constraints are clear.
Operational Implications
This model reduces stale assumptions and keeps audits cleaner because each high-stakes decision leaves source-linked evidence.
It also lowers recovery time when a run goes off track, since the boundary checks expose where confidence was overstated.