Today in AI ·

Google #GoogleLabs #Collaboration #Agents

Google launches Tabletop for collaborative AI-built planning spaces

Google introduced Tabletop on November 11, a Labs experiment that turns group prompts, links and files into shared interactive planning tools. Access is rolling out through a U.S. waitlist for adults, bringing real-time collaboration to activities such as itineraries and expense splitting.

Read at Google
Adobe #CreativeAI #MCP #DeveloperTools

Adobe previews local AI-agent integrations for Creative Cloud

Adobe previewed local MCP integrations on November 10 that let third-party agents edit Photoshop, Illustrator, Premiere and After Effects project files. Keeping layers, sequences and compositions editable could make agent-assisted work easier to revise within existing creative workflows.

Read at Adobe
n8n #Agents #OpenSource #Automation

n8n Labs releases Nod as a personal-agent research preview

n8n Labs released Nod on November 10 as an open-source research preview for Mac and Windows, separate from its core automation product. The desktop agent works across apps and websites using a chosen AI provider, offering another route to automating everyday tasks.

Read at n8n
Google Cloud #HealthcareAI #EnterpriseAI #Agents

Google previews Gemini for healthcare workflows

Google Cloud launched Gemini for healthcare in preview on November 10 for providers and health plans. The system coordinates tasks across clinical and administrative tools with access controls and human oversight, aiming to reduce fragmented record and coverage workflows.

Read at Google Cloud
Tether #OnDeviceAI #OpenWeights #Agents

Tether releases BotPsy for on-device tool use

Tether AI Research announced BotPsy on November 11, a 0.8-billion-parameter open-weight model specialized for tool calls on personal devices. Its compact design gives developers another option for local assistants, with applications supplying service connections and execution controls.

Read at Tether

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60-second Shorts and long-form deep dives on how real AI systems are built, how they break, and how to fix them: caching, RAG, agents, security and decision models.

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Five stages, from the edge of the network to the security of your agents.

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  1. 1 Foundations Edge & Caching Why far servers feel fast, where edge rendering backfires, and how one cache expiry can take down an AI app. 2 episodes · 2 coming 0 of 2 done
  2. 2 Core Decision Models When a typed decision beats generated text, and how to route between a decision model and an LLM. 3 episodes · 1 coming 0 of 3 done
  3. 3 Advanced Agents in Production Context, memory, cost guardrails and the workspace an autonomous coding agent needs. 9 episodes · 5 coming 0 of 9 done
  4. 4 Hands-on Hands-On: Coding Agents from Your Phone Step-by-step tutorials: build and ship real apps from the Claude app, with the prompts and the code for every step. 3 episodes · 2 coming 0 of 3 done
  5. 5 Hands-on AI Coding Agent Tips One practical tip per Short for Claude Code and the other coding agents, each one tested in a real run. 2 episodes 0 of 2 done
  6. 6 Extra Code Stories Picture-led stories from the history of programming, and what they say about where coding goes next. 3 episodes 0 of 3 done
  7. 7 Advanced AI Security Stolen tokens, poisoned tools and the other ways an AI system gets turned against its users. 5 episodes · 2 coming 0 of 5 done

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