Image created with Flux Pro v1.1 Ultra. Image prompt: Giant “100” as pure white negative‑space cutout dominating the frame; minimalist poster style; documents retrieving into a generator—arrows from vector bricks into the cutout; cyan‑slate backdrop; high contrast, crisp edges, soft studio light, no other text, no logos
There are 3 pervasive patterns in coding agent development that we deliberately avoid at Cline: 1. Multi-agent orchestration 2. RAG (via indexed codebases) 3. Instruction overloading Here’s why. <thread> https://x.com/cline/status/1960175630907306325
Command A Translate: Secure translation for global enterprises https://cohere.com/blog/command-a-translate
Introducing Command A Reasoning, our most advanced model for enterprise reasoning tasks. https://x.com/cohere/status/1958542682890047511
Try the model on our platform, deploy it privately, or for research use on @huggingface. Find more details in our blog: https://x.com/cohere/status/1961081787674763525
RAG isn’t just about answer generation. Most of the time, you want access to the original data sources too. Most AI chatbots today are stuck in a text-only world. You ask a question, you get a wall of text back. But that’s not how we naturally consume information, is it? https://x.com/weaviate_io/status/1960335442521346220
‘pip install elysia’ and ‘elysia start’ That’s literally all it takes to get the most advanced open source agentic RAG app running on your data. We just released 𝗘𝗹𝘆𝘀𝗶𝗮, our open source, agentic RAG framework and an app so cool needed a cool video to go with it. Watch https://x.com/victorialslocum/status/1961095661719359624
Today we’re launching “Agentic Knowledge Graph Construction,” a short course built in collaboration with @Neo4j and taught by Andreas Kollegger (@akollegger). RAG retrieves relevant text, and knowledge graphs complement it by modeling relationships and provenance so answers https://x.com/DeepLearningAI/status/1960726499419676861
