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For Local LLMs, it helps to think in terms of inputs, constraints, verification, and iteration. One important area is beginner tips. Define what a good result looks like before changing tools or settings, then test one variable at a time so you can tell what actually improved the outcome...

For Reinforcement Learning, it helps to think in terms of inputs, constraints, verification, and iteration. One important area is setup choices. Define what a good result looks like before changing tools or settings, then test one variable at a time so you can tell what actually improved the...