• What’s new in two: December 2025 edition.
• Redis 8.4 makes it easier to build with Redis streams and strings. Read how here.
• The Redis vector store node is now available in n8n, adding vector search to n8n workflows. Read more here.
• Redis vs. ElastiCache: What “support” actually means in production.
• Our VP of Product Management for AI, Manvinder Singh, discusses why memory is the missing piece for smarter AI agents. Read more here.
• Get hands-on with our new context engineering lab built in partnership with LangChain. Get started here.

The AI stack is getting noisier, but the direction is getting clearer, and our 2026 predictions reflect that. Apps that can’t deliver the right context will backfire, frameworks will converge around a few winners with strong ecosystems, and the pool of people who can build will expand fast as AI tools close the gap between ideas and shipped software. If you’re building AI apps that have to perform outside a demo, this is the set of predictions worth reading, and the conversation worth joining.

Context is what makes AI apps work, but more context isn’t automatically better context. As prompts swell, accuracy drops, costs climb, and agents drift as the signal gets buried in the noise. Our new guide breaks down what causes it, how to catch it in production, and how external memory keeps context useful without turning your prompt into a junk drawer.