Design the Agent-Computer Interface (ACI)
Apply SWE-agent's key finding: agents perform dramatically better when their commands, viewers, and feedback are designed for models, not humans.
The Route
0/5 verifiedAudit your current tool surface
You cannot design an interface you have not honestly measured.
Build the windowed file viewer
The single highest-leverage ACI component in the research.
Add validated edits with corrective feedback
An edit command that cannot fail loudly will fail silently.
Constrain search and command outputs
Concise, ranked results are an interface decision, not a nicety.
Benchmark against the raw baseline
The ACI claim is empirical - test it that way.
Context Pack
Paste this first. It briefs the AI on requirements, constraints, and the Definition of Done before your first build prompt.
Paste this into your AI builder first. It teaches the AI what you want before you give it the build prompt.
Related routes
More Agent Architecture flows that share ground with this one.
Design a Single-Loop Agent
Build the core agent loop the leading coding agents use: one model, one loop, tools in, results folded back into context.
+2 more steps to Done
Best forproduction-grade builds with strict verification
Add a Plan/Todo System to Your Agent
Give your agent the planning discipline of the leading harnesses: an explicit, model-visible todo list that survives long tasks.
+1 more steps to Done
Best forbuilders who have shipped a basic app before
Agent-to-Agent Protocols (A2A)
Connect two agents over an explicit protocol - task handoff, acknowledgment, and failure handling - instead of hoping chat works out.
+1 more steps to Done
Best forproduction-grade builds with strict verification