OpenScout / Field notes
Short explanations for builders
Practical ideas for agents, documentation, architecture, voice, and browser automation.
Narrated diagrams with captions, transcripts, and sources.
The explainers
12 films
How an AI agent handoff works
Follow a request from project and harness selection to a broker flight, completion evidence, and a follow-up with the same handle.
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MCP vs A2A vs an agent broker
A visual explanation of tool access, agent delegation, and broker routing — three responsibilities an agent system may combine.
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Agent identity versus a harness session
Separate an agent's durable identity, its current endpoint, and the harness context you actually want to continue.
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Portable context for AI coding agents
Carry the useful facts, revision and permissions into a new agent's task without assuming the whole conversation transfers.
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A human review gate for AI coding work
Review a specific change against its acceptance criterion, verify its evidence, and make the next decision explicit.
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Agent budgets, timeouts and stopping boundaries
Distinguish measuring usage, warning a person, refusing new work and confirming that execution has actually stopped.
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Documentation as an interface for AI agents
How Dewey turns maintained Markdown into an agent-facing entry point, retrieval map, and source artifacts without requiring a particular documentation website.
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Small documentation indexes, useful agent context
Use a compact index to discover the right source, then fetch a focused page or a broader bundle. A practical explanation grounded in Dewey's retrieval artifacts and the llms.txt proposal.
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Architecture diagrams that show the boundaries
Choose a scope, name the responsibilities, and label the connections. Use Arc's typed diagram data to keep an architecture explanation editable and reviewable alongside the code.
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Voice dictation latency and turn-taking explained
Follow a voice turn from capture to transcription and routing. Learn where to measure delay without confusing transcription speed with a usable result.
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How to evaluate AI agent features with evidence
Use agent directories to make a shortlist, distinguish documented capabilities from reproduced results, and keep unknown fields separate from unsupported features.
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Browser automation: observe, act, verify
Learn a practical browser automation loop: inspect the current page, select a target from evidence, perform one action, and verify a named result.
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