<p><em>This is a submission for the <a href="https://dev.to/challenges/hermes-agent-2026-05-15">Hermes Agent Challenge</a></em></p> <blockquote> <p>A practical deep-dive for
<p><em>This is a submission for the <a href="https://dev.to/challenges/hermes-agent-2026-05-15">Hermes Agent <br /> Challenge</a>.</em></p> <p><a
<h3> For a more in-depth guide </h3> <p>Medium: <a
<p>I'm a huge fan of coding agents. My daily consumption is at about <strong>7 million tokens</strong> and growing. I started on Cursor, fell in love with OpenCode, got into
<p>If you're building AI agents in Python right now, two frameworks are competing for your attention: <strong>LangChain Deep Agents</strong> (launched March 15, 2026) and the
<p><strong>TL;DR:</strong> I built the same browser agent twice โ once with 500 lines of Python, once with 7 lines of JSON. The second one took 5 minutes. The agent harness layer
<p>Most developers who build AI agents make the same mistake: they spend weeks designing the orchestration layer, tuning the system prompt, and picking the right model โ then hand
<p>Everyone's talking about AI agents. But most explanations jump straight to frameworks โ LangChain, CrewAI, AutoGen โ without explaining what an agent actually <em>is</em> under
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