Across 101 enterprises, the context feeding AI agents is failing often and repeatedly. Sixty-eight percent have traced a confident but wrong agent answer to missing or inconsistent business context in [...]
A new framework from Stanford University and SambaNova addresses a critical challenge in building robust AI agents: context engineering. Called Agentic Context Engineering (ACE), the framework automat [...]
For all their superhuman power, today’s AI models suffer from a surprisingly human flaw: They forget. Give an AI assistant a sprawling conversation, a multi-step reasoning task or a project spanning [...]
Across 101 enterprises, the infrastructure that feeds AI agents their business context is being built faster than it can be trusted. Retrieval-augmented generation is already the default context sourc [...]
When startup fundraising platform VentureCrowd began deploying AI coding agents, they saw the same gains as other enterprises: they cut the front-end development cycle by 90% in some projects.However, [...]
An enterprise AI agent answers with total confidence, but the number is wrong. Nobody catches it until someone traces it back to a stale metric definition or a document the retrieval system never pull [...]
AI coding agents are rapidly accelerating data engineering by generating transformations, pipelines, orchestration workflows, validation tests, and infrastructure configurations from prompts. However, [...]
One employee at Vercel adopted an AI tool. One employee at that AI vendor got hit with an infostealer. That combination created a walk-in path to Vercel’s production environments through an OAuth gr [...]
Enterprise AI has largely been built around context engineering. Teams connect enterprise systems, generate chunks and embeddings, build retrieval pipelines, and assemble the context needed by individ [...]