Consumer Software Industry Concerns - Consumer software CEOs are worried about agents taking over, leading to a paradigm shift away from web pages [1] - The rise of agents could make the traditional browser obsolete, reducing it to a glorified markup reader [6] Perplexity's Strategic Opportunities - Perplexity has the potential to replace Bloomberg in the financial information and data sector, a market worth $100 billion [4][5] - Focusing on a specific vertical and owning it is a good strategy for Perplexity, especially with unique data sources [10] Apple's Potential Acquisition of Perplexity - There is speculation that Apple might acquire or partner with Perplexity for distribution, given the Justice Department case against Google [9] - However, acquiring Perplexity may not solve Apple's AI challenges, as Apple has missed previous AI opportunities [10] Bloomberg's Weaknesses - Bloomberg's terminal is considered atrocious, terrible, and limited, presenting an opportunity for a better product [4] - Bloomberg's core usability and UI have not evolved, despite its messaging platform being valuable for trading [14]

Key Features of Stagehand - Bridges the gap between brittle traditional automation tools like Playwright and Selenium, and unpredictable full-agent solutions like OpenAI Operator [1][3] - Employs AI for navigating unfamiliar pages and code (Playwright) for executing known tasks [3] - Allows previewing AI actions before execution [3] - Caches repeatable actions to conserve tokens [3] - Compatible with SOTA computer use models with minimal code [3] - Available in both Python and TypeScript SDK [3] Stagehand Ecosystem - Includes an open-source MCP server [2] - Aims to provide a browser automation framework for Agents suitable for production environments [1]

RT Avi Chawla (@_avichawla)6 no-code LLMs, Agents, and RAG builder tools for AI engineers:(open-source and production-grade) ...

6 no-code LLMs, Agents, and RAG builder tools for AI engineers:(open-source and production-grade) ...

MCP Overview & Architecture - MCP (Micro Control Plane) is defined as a pluggable architecture for agents, contextualized within an enterprise cloud service [5][6] - Sentry's MCP server was initially built as a fun project and is biased towards Sentry's application monitoring services [4][5] - The industry views MCP as a potential solution for integrating services into various agents, enabling bug fixes and workflow enhancements within editors [7][8][25] Implementation & Challenges - Implementing MCP involves complexities around OAUTH 21%, requiring solutions like Cloudflare Shim for proxying OAUTH 2 API [16][17] - A key challenge is that MCP cannot simply sit on top of Open API; systems need to be designed around how agents and models react to provided context [19][20][21] - Current client support for native authentication is still evolving, with some clients like Cursor experiencing breakage [22] Security & Best Practices - Security is a major concern, particularly with the standard IO interface, and random MCP tools should not be allowed within organizations [27] - For B2B SaaS companies, focusing on OAUTH with remote environments is crucial for integrating services into agents [25] - Companies should avoid simply proxying Open API and exposing it as tools, as this yields poor results; intentional design and context provision are necessary [30] Agent-Centric Approach - The industry should focus on building agents, viewing MCP as a plug-in architecture to leverage the value of LLMs [39][40] - Exposing agents through the MCP architecture, particularly in B2B settings, is seen as a significant value unlock [42] - Optimizing for context in workflows and understanding data is crucial when designing agents, with a focus on providing structured information like Markdown for language models [31][50]

RT Avi Chawla (@_avichawla)After MCP, A2A, & AG-UI, there's another Agent protocol (open-source).ACP (Agent Communication Protocol) is a standardized, RESTful interface for Agents to discover and coordinate with other Agents, regardless of their framework (CrewAI, LangChain, etc.).Here's how it works:- Build your Agents and host them on ACP servers.- The ACP server will receive requests from the ACP Client and forward them to the Agent.- ACP Client itself can be an Agent to intelligently route requests to t ...

Context Engineering Overview - Context engineering is defined as the art and science of filling the context window with the right information at each step of an agent's trajectory [2][4] - The industry categorizes context engineering strategies into writing context, selecting context, compressing context, and isolating context [2][12] - Context engineering is critical for building agents because they typically handle longer contexts [10] Context Writing and Selection - Writing context involves saving information outside the context window, such as using scratch pads for note-taking or memory for retaining information across sessions [13][16][17] - Selecting context means pulling relevant context into the context window, including instructions, facts, and tools [12][19][20] - Retrieval-augmented generation (RAG) is used to augment the knowledge base of LLMs, with code agents being a large-scale application [27] Context Compression and Isolation - Compressing context involves retaining only the most relevant tokens, often through summarization or trimming [12][30] - Isolating context involves splitting up context to help an agent perform a task, with multi-agent systems being a primary example [12][35] - Sandboxing can isolate token-heavy objects from the LLM context window [39] Langraph Support for Context Engineering - Langraph, a low-level orchestration framework, supports context engineering through features like state objects for scratchpads and built-in long-term memory [44][45][48] - Langraph facilitates context selection from state or long-term memory and offers utilities for summarizing and trimming message history [50][53] - Langraph supports context isolation through multi-agent implementations and integration with sandboxes [55][56]

If you found it insightful, reshare it with your network.Find me → @_avichawlaEvery day, I share tutorials and insights on DS, ML, LLMs, and RAGs.Avi Chawla (@_avichawla):After MCP, A2A, & AG-UI, there's another Agent protocol (open-source).ACP (Agent Communication Protocol) is a standardized, RESTful interface for Agents to discover and coordinate with other Agents, regardless of their framework (CrewAI, LangChain, etc.).Here's how it works: https://t.co/q6xFvQKYgw ...

[Music] Hi, I'm Lizzie. I'm a developer advocate at Cloudflare. And I'm Nick. I'm a developer experience engineer at work OS. Yes. So, at Cloudflare, I make a lot of AI demos, AI MCP servers. Anyone here also making any of those? Yes. Agents. Nice. Of course, should have guessed because conference. So, I've been having fun making agents and MCP servers that act on behalf of me. I built an agent to auto vote in the NBA finals for me and then I got blocked eventually. Uh, anyways, like book tennis courts in S ...

AI Platform & Business Model - Poe平台提供用户通过订阅访问多种语言模型和代理的能力 [1] - Poe的Bot创建者每年收入数百万美元 (millions) [1] - 推理模型正在推动增长 [1] Consumer AI Usage - 揭示了消费者在使用AI方面的惊人模式 [1] AI Development Challenges - 在快速变化的AI领域中构建产品面临独特的挑战 [1] - 规划周期已从数年缩短至仅两个月 [1]