Not every company can or should build their own frontier AI language model. However, the harness controlling the model is something that most enterprises can and should customize for their specific purposes.Of course, this is easier said than done. Agent harnesses are still largely tuned through manual, ad hoc debugging — a process that relies heavily on intuition rather than systematic feedback loops, making it difficult to keep pace with rapidly evolving LLMs.To solve this challenge, researchers at the Shanghai Artificial Intelligence Laboratory have introduced “Self-Harness,” a new paradigm in which an LLM-based agent systematically improves its own operating rules. By examining its own execution traces to apply edits, the system trades manual guesswork for empirical evidence.Self [...]
As enterprise AI agents take on increasingly complex, long-horizon tasks, their performance is often restricted by their harness, the software scaffolding that connects the backbone LLM to its environ [...]
A joint research collaboration between researchers at the University of Illinois at Urbana-Champaign (UIUC), UC Berkeley, and the open source AI-native vector database platform Chroma unveiled Harness [...]
Creating self-improving AI systems is an important step toward deploying agents in dynamic environments, especially in enterprise production environments, where tasks are not always predictable, nor c [...]
Enterprise AI is facing an ROI paradox. While throwing more compute at the strongest foundation model works well in product experiments, the costs become unbearable when the product is deployed in pro [...]
If you ask an AI coding agent to write a standalone Python script to parse a single JSON file, it will likely give you a perfect answer in seconds. But the same agent often breaks if you ask it to bui [...]
One major challenge in deploying autonomous agents is building systems that can adapt to changes in their environments without the need to retrain the underlying large language models (LLMs).Memento-S [...]
“You can deceive, manipulate, and lie. That’s an inherent property of language. It’s a feature, not a flaw,” CrowdStrike CTO Elia Zaitsev told VentureBeat in an exclusive interview at RSA Conf [...]
Nimble, a New York City-based tech startup VentureBeat previously covered for its efforts to re-invent web search for enterprises by using multiple AI agents to improve accuracy and depth, is taking a [...]