Search for a command to run...
Every processed story in chronological order, with the newest coverage first. Filter by tag, source, or score to drill in.
Watch this episode to understand how a large engineering organization is redesigning its entire software delivery pipeline — not just its code generation step — to keep pace with AI-speed development.
Developers and practitioners building AI for life sciences should note that Noetik's platform-licensing deal with GSK signals that pharma companies are beginning to pay for biotech AI as software infrastructure, not just as a path to drug co-development — validating a pure-tools business model in the space.
Understanding GraphRAG's tradeoffs — explainability and structured context vs. pure vector retrieval — helps AI/coding practitioners decide when to layer a knowledge graph into their retrieval pipelines.
AI/coding practitioners building RAG pipelines should evaluate GraphRAG as an alternative to pure vector retrieval — the explicit, traversable structure of a knowledge graph can make agent memory and document retrieval more accurate, debuggable, and auditable in production systems.
Teams building agentic products can apply Notion's hard-won lessons — on eval design, roadmap timing relative to model capabilities, and org structure — to avoid the same multi-year rebuild cycles Notion experienced.