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AI agents need smaller workflows, not more context, says dev.to author

The author argues that AI agents often become inefficient and costly due to excessive context and a lack of defined workflows. Instead of providing vast amounts of information, developers should focus on creating smaller, more directed workflows that specify the scope of files, tools, and steps involved. This approach, akin to establishing good habits for the agent, leads to more focused tasks, reduced token usage, and better outcomes compared to simply increasing the context window. AI

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IMPACT Suggests a shift in AI agent design towards more constrained workflows to improve efficiency and reduce costs.

RANK_REASON Opinion piece from a developer on a tech platform discussing AI agent design.

Read on dev.to — MCP tag →

COVERAGE [1]

  1. dev.to — MCP tag TIER_1 · Alex Shev ·

    Your AI Agent Does Not Need More Context. It Needs a Smaller Workflow.

    <p>A lot of AI agent workflows are becoming expensive for a very boring reason:</p> <p>We keep giving the agent too much context and not enough direction.</p> <p>The usual pattern looks like this:<br /> </p> <div class="highlight js-code-highlight"> <pre class="highlight plaintex…