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...Jesse emphasizes structured outputs, safety boundaries, and explainable reasoning, helping users design agents that don’t just hallucinate responses but can coordinate steps, validate conditions, and interact with systems predictably. It also includes built-in support for evaluation, logging, and orchestration so developers can monitor, test, and improve agent behavior over time. Because it’s framework-agnostic with respect to model providers, Jesse can work with different LLM backends, giving teams flexibility in cost and capability trade-offs.

...Human interaction has never needed a middleman. The internet should work how real life works.

...Flexible sampling period and trade frequency - averages 1-2 trades/day with 1h period, 15-50/day with 5m period. Crypto-currency is still an experiment, and therefore so is Zenbot. Meaning, both may fail at any time. Running a bot, and trading in general requires careful study of the risks and parameters involved. A wrong setting can cause you a major loss.