Can AI generate end-to-end agent workflows from natural-language goals ?
Cast your vote — then read what our editor and the AI models found.
Agentic systems run multi-step web tasks, file ops, calls to other agents. Not yet reliable enough for all jobs, but solidly working for many.
Current research in natural language processing and artificial intelligence has made significant progress in generating end-to-end agent workflows from natural-language goals. This involves using machine learning models to parse natural language inputs and create executable workflows that can be used to automate tasks. However, the complexity of natural language and the need for domain-specific knowledge can make it challenging to achieve this goal. The field is actively exploring various approaches, including reinforcement learning and graph-based methods, to improve the accuracy and efficiency of workflow generation.
— Enriched May 9, 2026 · Source: Association for the Advancement of Artificial Intelligence — https://www.aaai.org
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