From CLI Harness to Product
Grow a working agent loop into a product: sessions, config, resumability, and the packaging polish the successful terminal agents share.
The Route
0/5 verifiedImplement persistent sessions
Sessions turn a script into a tool people trust with long work.
Build true resume
Resume is the feature that proves your state model is honest.
Layer the configuration system
Every serious tool answers 'where do I change that?' the same way.
Polish first-run and errors
The first two minutes decide adoption.
Package and version it
Distribution is part of the architecture.
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.
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
Assemble a System Prompt Like the Pros
Structure your agent's system prompt the way leading harnesses do: layered sections, dynamic context, and enforceable rules.
+1 more steps to Done
Best forbuilders who have shipped a basic app before