WEBVTT

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Most people meet AI through a chat window.

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Ask a question, get an
answer, decide what's next.

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But real work rarely ends with one answer.

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A feature needs research, code, tests,

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a review, and a record of the decisions.

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So think of RuFlo as a
workshop, not another chatbot.

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Four pieces are easy to confuse.

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The model does the reasoning.

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A skill is a playbook.

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MCP lets an assistant
discover and call tools.

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And the runtime performs the work.

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“I installed the skill,” and
“the MCP server is connected”

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are two different statements.

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RuFlo helps you plan and coordinate work,

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keep project memory,
learn from what worked,

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build repeatable workflows, test software,

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and add security checks.

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Plan a task, then fan it out.

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Research, build, and test in parallel.

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One coordinator resolves the
findings into a single review,

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and the important findings are
retained for the next session.

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More agents are not automatically cheaper.

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Measure cost per accepted result.

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And an agent saying “done”
is not a test result.

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Verify tool discovery, permissions,

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and the actual output.

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Start small, install the RuFlo skill,

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pick one project and one acceptance test.

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Add the next capability

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only when you can name
the problem it solves.