Content Type
Practical content you can use right away: prompting techniques, workflow setup, tool usage, and lessons learned the hard way.
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A Hugging Face author used ML Intern in HuggingChat to build six models over a few days for about USD 103 in total compute.
Why it matters: A first-hand account of prompting an agent to train six small models, with per-project budgets and costs.
Anthropic Engineering describes presenting MCP servers as code APIs instead of direct tool calls.
Why it matters: Anthropic's own walkthrough of turning MCP servers into code APIs, with the token math and the sandboxing tradeoff spelled out.