The ALTK-Evolve framework allows AI agents to update their internal knowledge bases during task execution. It replaces static prompting with a dynamic learning loop that corrects errors in real time. This approach reduces hallucination rates in complex workflows. Practitioners can now deploy agents that refine their own operational logic without requiring manual fine-tuning or new datasets.