The article discusses the potential downsides of Moltbook, a proposed platform aiming to connect AI agents directly with users, bypassing traditional agents. It argues that Moltbook could disintermediate human agents, leading to a 'revolt' and ultimately harming the AI ecosystem. Concerns include lack of quality control, potential for misuse, and the importance of human oversight in AI interactions.
OpenViking is an open-source context database designed specifically for AI Agents. It unifies the management of context (memory, resources, and skills) using a file system paradigm, enabling hierarchical context delivery and self-iteration.
This outlines the emergence of an "agentic economy" on Ethereum, powered by AI agents, and the infrastructure being built to support it. It details the potential for autonomous economic activity and the challenges of building a secure and reliable system.
A single developer built a powerful search and monitoring tool for the web using a simple SQLite database and a clever bot, highlighting the potential of individual creators to tackle complex problems.
>When deployed strategically, agents can empower SREs to offload low-risk, toilsome tasks so they can focus on the most critical matters.
Agents in practice include:
* **Contextual Information:** Providing SREs with details from previously resolved incidents involving the same service, including responder notes.
* **Root Cause Analysis:** Suggesting potential origins of an issue and identifying recent configuration changes that might be responsible.
* **Automated Remediation:** Handling low-risk, well-defined issues without human intervention, with SRE review of after-action reports.
* **Diagnostic Suggestions:** Nudging SREs towards running specific diagnostics for partially understood incidents and supplying them automatically.
* **Runbook Generation:** Automatically creating and updating runbooks based on successful remediation steps, preventing recurring issues.
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Agents in practice include:
* **Contextual Information:** Providing SREs with details from previously resolved incidents involving the same service, including responder notes.
* **Root Cause Analysis:** Suggesting potential origins of an issue and identifying recent configuration changes that might be responsible.
* **Automated Remediation:** Handling low-risk, well-defined issues without human intervention, with SRE review of after-action reports.
* **Diagnostic Suggestions:** Nudging SREs towards running specific diagnostics for partially understood incidents and supplying them automatically.
* **Runbook Generation:** Automatically creating and updating runbooks based on successful remediation steps, preventing recurring issues.
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This article details authentication and authorization mechanisms within the Model Context Protocol (MCP), covering transport layers like stdio and Streamable HTTP, OAuth flows, and security considerations for MCP servers.
The article discusses the evolution from RAG (Retrieval-Augmented Generation) to 'context engineering' in the field of AI, particularly with the rise of agents. It explores how companies like Contextual AI are building platforms to manage context for AI agents and highlights the shift from prompt engineering to managing the entire context state.
A guide to supercharging Claude Code with Skills and the Model Context Protocol (MCP), including running Claude Code in an IDE like Cursor or VS Code. It covers setting up Skills, connecting to MCP servers, and combining both for powerful workflows.
Vercel's research shows that embedding a compressed 8KB docs index in AGENTS.md achieves a 100% pass rate for Next.js 16 API evaluations, while skills maxed out at 79%, even with explicit instructions. This suggests that passive context provision via AGENTS.md is more effective than active retrieval with skills for framework-specific knowledge in AI coding agents.
MCP Apps are now live as an official MCP extension, allowing tools to return interactive UI components directly in conversations. This enables richer experiences like dashboards, forms, and visualizations within MCP clients such as Claude, Goose, Visual Studio Code, and ChatGPT.
