The ALTK-Evolve framework allows AI agents to update their internal knowledge bases during active task execution. It uses a feedback loop to refine tool-use strategies without requiring full model retraining. This approach reduces errors in complex workflows. Practitioners can now deploy agents that adapt to environment changes in real-time, cutting manual prompt tuning.