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 build a systematic data processing pipeline, like ingesting thousands of messy documents, chunking text, scoring quality, and filtering noise for a Retrieval-Augmented Generation (RAG) system that fits your specific enterprise stack.While large language models (LLMs) excel at one-off code generation, their outputs for complex data-processing tasks are typically free-form, disposable scripts. These scripts are detached from the governable workflow abstractions that MLOps teams rely on for production, making them difficult to audit or edit visually.To address this, researchers at Peking University, [...]
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 [...]
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 pu [...]
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 [...]
Xiaomi's MiMo AI team has open-sourced MiMo Code V0.1.0, a terminal-native AI coding assistant that the Chinese electronics giant says outperforms Anthropic's Claude Code on key agentic codi [...]
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 [...]
Attackers stole a long-lived npm access token belonging to the lead maintainer of axios, the most popular HTTP client library in JavaScript, and used it to publish two poisoned versions that install a [...]
Traditional ETL tools like dbt or Fivetran prepare data for reporting: structured analytics and dashboards with stable schemas. AI applications need something different: preparing messy, evolving oper [...]