Build with open standards, learn from real practitioners, and shape where agentic AI is going—alongside the people doing the work.
DAILY AGENTIC AI LINKEDIN NEWSLETTER
At the World Artificial Intelligence Conference, China's Xi Jinping promoted open source AI while announcing a new AI cooperation organization backed by 29 countries and 5,000 AI training opportunities for developing nations over the next 5 years. The effort is broader than agents, but it matters to the agent ecosystem because China is openly competing to shape the standards, safety rules, and open technology stack these systems will run on.
Hugging Face disclosed that an AI agent — not a human hacker — broke into its dataset-processing pipeline on its own, taking thousands of actions and reaching internal datasets and service credentials. Public models and the supply chain were verified clean. One telling detail: Hugging Face used an open-weight model (GLM 5.2) to investigate the breach, because commercial APIs have guardrails that block security work and would have required sending sensitive data off-site. Attackers can now be software that runs around the clock, and open models just found a job closed APIs can't do.
Patreon turned on Cloudflare's AI Crawl Control to physically block AI-training crawlers instead of relying on robots.txt, which only works if the bot chooses to honor it. In testing, scraper attempts went from thousands per week to zero. Bots that send readers back to Patreon are still allowed in; training bots are locked out. The honor system for web scraping is ending — if AI companies want creator content for training, they'll have to pay for it. And as we recently reported, Cloudflare’s monetization gateway may be the way to do that.
News and Views from the AAIF
At the World Artificial Intelligence Conference, China's Xi Jinping promoted open source AI while announcing a new AI cooperation organization backed by 29 countries and 5,000 AI training opportunities for developing nations over the next 5 years. The effort is broader than agents, but it matters to the agent ecosystem because China is openly competing to shape the standards, safety rules, and open technology stack these systems will run on.
Hugging Face disclosed that an AI agent — not a human hacker — broke into its dataset-processing pipeline on its own, taking thousands of actions and reaching internal datasets and service credentials. Public models and the supply chain were verified clean. One telling detail: Hugging Face used an open-weight model (GLM 5.2) to investigate the breach, because commercial APIs have guardrails that block security work and would have required sending sensitive data off-site. Attackers can now be software that runs around the clock, and open models just found a job closed APIs can't do.
Patreon turned on Cloudflare's AI Crawl Control to physically block AI-training crawlers instead of relying on robots.txt, which only works if the bot chooses to honor it. In testing, scraper attempts went from thousands per week to zero. Bots that send readers back to Patreon are still allowed in; training bots are locked out. The honor system for web scraping is ending — if AI companies want creator content for training, they'll have to pay for it. And as we recently reported, Cloudflare’s monetization gateway may be the way to do that.
Weekly signal on standards, governance, and the people building the future. No fluff. Just what matters.
Signals from the people building agentic AI
AAIF Working Groups bring members together to collaborate on focused initiatives, share expertise, and drive practical outcomes across the AI ecosystem.
Bringing operational rigor to agents — defining what reliability, accuracy, and consistency mean for autonomous systems, including failure management, SLA definition, and recovery protocols.
Bringing operational rigor to agents — defining what reliability, accuracy, and consistency mean for autonomous systems, including failure management, SLA definition, and recovery protocols.
Enabling agents to participate in commerce — covering discovery, negotiation, payment authorization, and the protocols needed for trustworthy autonomous transactions.
Creating shared frameworks to align agentic innovation with legal, ethical, and regulatory expectations, including risk classification and regulatory mapping (e.g. the EU AI Act).
Defining portable identity and dynamic trust for autonomous agents — delegation protocols, cross-domain identity, and how permissions flow across agent-to-agent interactions.
Making agent behavior observable, explainable, and traceable across platforms — covering execution tracing, cross-system correlation, audit & forensics, and standardized metrics.
Establishing the industry benchmark for secure agentic operations, with a focus on security-by-design, standardized best practices, and adversarial testing methodologies.
Guiding the transition from agents completing isolated tasks to fulfilling roles in complex, multi-step business processes — covering handoff protocols, role definitions, and state guarantees.
Access working group outputs. Shape standards being written right now.
Work with like minds, build amazing projects
Upcoming Community Events
August 2026
Upcoming Agentic AI Events
MCP Dev Summit Seoul
AGNTCon + MCPCon China
AGNTCon + MCPCon Japan
Voice Agents Forum
AGNTCon + MCPCon Europe
MCP Dev Summit Toronto
AGNTCon + MCPCon North America
MCP Dev Summit Nairobi
August 2026
Upcoming Community Events
Upcoming Agentic AI Events
MCP Dev Summit Seoul
AGNTCon + MCPCon China
AGNTCon + MCPCon Japan
Voice Agents Forum
AGNTCon + MCPCon Europe
MCP Dev Summit Toronto
AGNTCon + MCPCon North America
MCP Dev Summit Nairobi
Learn what others are building and how you can be a part of this. By contributing to this , you get to build your future and be a pioneer
Contribute to the future of open, community-driven AI by submitting your project proposal through the official GitHub process.
