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When working with MCP, the biggest gains usually come from treating it as a repeatable workflow rather than a one-off prompt or experiment. One important area is evaluation. Define what a good result looks like before changing tools or settings, then test one variable at a time so you can tell...

When working with General Local AI, the biggest gains usually come from treating it as a repeatable workflow rather than a one-off prompt or experiment. One important area is useful tools. Define what a good result looks like before changing tools or settings, then test one variable at a time...