AI 服务暂时不可用，以下为来源正文，待恢复后补全翻译。
AI agents are being widely deployed inside businesses today, but do they actually know how to get results? This is the fundamental question being asked in many boardrooms as enterprises implement AI strategies tied to agents performing key tasks. Impetus Technologies Inc. has built its value proposition on the belief that it can bridge the “context gap,” the space between what AI models know and the unique attributes of the organizations they serve. “We were in this world, and we knew what data is and where it sits,” said Deepak Khosla (pictured), chief growth officer and head of AI at Impetus. “We figured out the gap is not the large language models. The gap is the context and that’s why we want to fill that gap.” Khosla spoke with John Furrier during an exclusive conversation on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how Impetus builds an operational framework to bring context to agentic AI. (* Disclosure below.) Context engineering for AI agents To generate the necessary context, Impetus employs an enterprise AI operational framework to test and govern the data that agents use. The goal is to move beyond generic prompting and treat organizational context as managed infrastructure. “The old methodology of building IT solutions, AI solutions and agentic solutions is no longer going to work over here,” Khosla told theCUBE. “So, we have developed a new methodology, which is called CEDL, Context Engineering Delivery Lifecycle. You create the context for ‘C,’ you engineer the context, that’s for ‘E,’ then you have this whole learning model, which is basically you would learn what’s happening, what’s not. Then you bring back those signals and make those agents work again.” Impetus’ use of context engineering relies on modernizing legacy systems, organizing semantic meaning and orchestrating agents for real-world deployment. This involves building knowledge graphs to understand the relationships between entities, creating an ontology layer of business tools and formulating memory. “Memory is very important because you need to have short-term memory, long-term memory,” Khosla said. “Memory is even more important because of the way the LLM works. If they learn the wrong thing by mistake … that’s going to stick with you, that’s going to stay with all the actions that’s going to happen.” Impetus has developed a Leap AI suite of products to move AI into production. By framing Leap AI around context engineering, the company infuses agentic systems with software discipline and service flexibility. This requires a mix of data platform modernization and an understanding of the unique knowledge specific to a certain company or industry, according to Khosla. “We help them bring that context in while we are migrating and modernizing and building their data platform,” Khosla said. “We’ll start building the knowledge layer, the semantic layer upfront…we’ll basically bring the rest of that enterprise knowledge to those agents. It’s like a new hire, a new hire in the company, a smart person, and you don’t tell them anything about the company, the smart person is not going to do anything well. But if you tell the smart hire about your business, your rules and everything, the [person] will do good. We make those agents smarter by bringing the context there.” Here’s theCUBE’s complete video interview with Deepak Khosla: (* Disclosure: Impetus Technologies Inc. sponsored this segment of theCUBE. Neither Impetus nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.) Photo: SiliconANGLE