Smarter: across-the-board improvements for agentic, reasoning and multi-step tasks.
AGENTS
-
Command A+ Model Introduces Agentic AI with Efficient Hardware Deployment
By
–
Our fastest, most powerful model yet. Command A+ combines high-performance agentic AI with efficient, practical deployment – running on as few as two H100s.
-
Google AI Studio antigravity-preview-05-2026 Agent launched
By
–
ICYMI : Google AI Studio got a new "antigravity-preview-05-2026" Agent! > A general-purpose autonomous agent running in a remote, Google-hosted Linux environment. > This agent can execute code, take real actions, and use a large number of tokens.
-
Correlation Between Model Performance and AI Agent Revenue
By
–
very belated but in retrospect i think @sama's mythical "build a business that gets better when models get better" is basically what I called Agent Labs here.
— swyx (@swyx) 20 mai 2026
seeing a very direct correlation with model performance and agent lab revenue, discontinuity in Q4 2025
(clip from… https://t.co/ffp1RBLlhL pic.twitter.com/YF8Xuml8hhvery belated but in retrospect i think @sama
's mythical "build a business that gets better when models get better" is basically what I called Agent Labs here. seeing a very direct correlation with model performance and agent lab revenue, discontinuity in Q4 2025 (clip from -
The missing infrastructure for AI agent financial transactions
By
–
People talk about AI agents like the hard part is tool calling.
— AI Breakfast (@AiBreakfast) 20 mai 2026
tool calling is solved. the unsolved part: what happens the moment your agent needs to move money?
there's no clean infrastructure for that yet. that's the actual gap in the agentic stack. https://t.co/1ZFjzEMgwZPeople talk about AI agents like the hard part is tool calling. tool calling is solved. the unsolved part: what happens the moment your agent needs to move money? there's no clean infrastructure for that yet. that's the actual gap in the agentic stack.
-
Querying technical specifications of Google’s Gemini Spark and Antigravity harness
By
–
Anyone understand what Google mean by "Gemini Spark runs on Gemini 3.5 and uses the Antigravity harness" – is "Antigravity" a generic term they're using for their agent harnesses now or is their Claw-competitor running the same closed-source Go binary we can download ourselves?
-
AI transforms workflow speed and flow state
By
–
This isn't just a faster way to type. It's a fundamentally different relationship with your work. Instead of slowing down to translate thought into text, you stay in the flow state. You move at the speed of thought, not the speed of your keyboard.
-
The Shift to Agentic AI and Multi-Model Collaboration
By
–
Agentic AI changed the conversation.
— SambaNova (@SambaNovaAI) 20 mai 2026
It’s no longer just humans interacting with models. Now models are planning, reviewing, refining, & collaborating with other models to solve complex tasks.
🎧 @SumtiJairath breaks it down in this @dcdnews ep: https://t.co/9Wwc0vjUDb pic.twitter.com/JjcCcfBhnoAgentic AI changed the conversation. It’s no longer just humans interacting with models. Now models are planning, reviewing, refining, & collaborating with other models to solve complex tasks. @SumtiJairath breaks it down in this @dcdnews ep: https://
podcasts.apple.com/us/podcast/epi
sode-102-the-training-to-inference-passageway/id1607349232?i=1000764784324
… -
Technical Analysis Request for LLM-based Agent Architecture
By
–
@grok @perplexity_ai review http://
docs.activegraph.ai, analyze the approach critically, and explain in detail where this sits in the evolving landscape of LLM based agent architecture -
Focusing on AI models for real-world agentic coding and knowledge work
By
–
the team is super focused on making models great for real world use cases. We spend all day using them for agentic coding, knowledge work, etc and so we feel the good and bad daily : )