Hi there, this is Christian from Lchain. If you build with coding agents like cursor, you probably recognize this. The first few turns with the agents are great.But then as you keep continuing talking to the agent in the same thread, the quality slides, the decision get more fuzzy and the overall code quality drops and then cursor drops this system line context summarized. That's the moment you know you've crossed the context boundary line. So why is summarization such a big deal for context engineering.Eve ...

To summarise, I'll leave you with the context engineering graphic.Also, here's an open-source stack for context engineering:- Memory: @zep_ai- Knowledge base: @milvusio- Agent orchestration: @crewAIInc- Observability & tracing: @deepeval https://t.co/qseVsjlXBr ...

Context engineering, clearly explained (with visuals):(an illustrated guide below) https://t.co/am97ee4vTA ...

Right. Hello everyone. Uh today I will present meta adaptive context engineering or meta AC for short which is a new framework designed to optimize AI agents beyond single dimension approaches.We will explore how orchestrating multiple adaptation strategies can overcome the limitations of existing context engineering methods. Now a little introduction about myself. Uh so I'm Alberto Romero.I'm the co-founder and CEO at jointly. And for context at jointly we build the main specialized agents for regulated in ...

Hello everybody and welcome to my session at a engineer code summit and I'm going to talk a bit about how you can connect the dots with graph technology and solve problems like context engineering um improving retrieval patterns and also agentic memory. So we're going to have a lot of fun. My name is Stephen Chin.I'm VP of developer relations at Neo Forj and you can find me at all the different social media outlets with my handle Steve on Java. So excited you're all here to join for the session today. And I ...

毫无疑问，Google最新推出的Gemini 3再次搅动了硅谷的AI格局。在OpenAI与Anthropic激战正酣之时，谷歌凭借其深厚的基建底蕴与全模态（Native Multimodal）路线，如今已从"追赶者"变成了"领跑者"。 此次Gemini 3不仅在多模态能力上实现了新的飞跃，更被视为谷歌对Scaling Law最极致的一次执行。 硅谷101在11月20日举办了一场直播，邀请了四位处于AI研发与应用最前线的嘉宾： 我们试图透过Gemini 3的发布，试图回答关于AI未来的几个关键问题：Gemini 3到底强在哪里？谷歌究竟做对了什么？全球大模型竞争格局将如何改变？ LLM的未来走向，以及在LLM之外，最前沿的AI实验室正在关注什么？ 以下是我们直播中的嘉宾浓缩观点，如果想收看完整直播内容，可以关注我们的YouTube和B站回放。 01 体验实测：Gemini 3到底强在哪里？ 在Gemini 3发布后的48小时内，各大榜单被迅速刷新。不同于以往模型仅在单一维度（如代码或文本）上的提升，Gemini 3被认为是真正意义 上的"全模态原生"模型。对于使用者而言，这种技术参数上的提升转化为怎样的实际体感 ...

Core Viewpoint - TRAE SOLO has officially launched, marking a significant advancement in AI coding tools, particularly for complex project development in the AI IDE sector [1][6][49]. Group 1: Product Features and Enhancements - The SOLO official version introduces several core capabilities, including the built-in intelligent agent SOLO Coder, multi-task lists, context compression, and code change functionalities, enhancing its ability to handle complex tasks [6][10]. - The new positioning of SOLO as "The Responsive Coding Agent" emphasizes its capabilities in real-time perception, task management, and multi-tasking [6][49]. - A limited-time free trial for all TRAE international version users is available until November 15, allowing users to experience SOLO Coder and SOLO Builder [7][8]. Group 2: Context Management and User Experience - The "Responsive Context" feature allows developers to maintain control over the development process by ensuring that context is trackable, retrievable, and uninterrupted, addressing common frustrations with AI programming [11][13]. - The updated Plan function provides clear task planning before coding begins, allowing for alignment between the developer and the AI model [13][41]. - The "Responsive Review" feature enhances transparency in the development process, allowing developers to see task progress and understand AI actions in real-time [16][20]. Group 3: Multi-Tasking and Collaboration - SOLO supports genuine multi-tasking, enabling developers to work on multiple projects or sub-tasks simultaneously without losing context [23][25]. - The integration of Sub-Agents allows for specialized tasks, reducing the need for manual handling and improving efficiency [25][40]. Group 4: Testing and Iteration - The testing of SOLO Coder demonstrated its ability to handle complex scenarios, such as recreating a chatbot project, showcasing its rapid development capabilities [27][28]. - The iterative process allows for continuous improvement, with SOLO Coder capable of understanding feedback and autonomously correcting issues [39][41]. Group 5: Industry Trends and Future Outlook - The evolution of TRAE from a simple AI coding assistant to a comprehensive coding agent reflects a broader industry trend towards intelligent systems that can manage complex projects [48][50]. - The future of AI programming tools is expected to focus on enhancing the capabilities of intelligent agents, allowing developers to shift from coding to architectural roles [56][57].

Hey, this is Lance from Langchain. I want to talk of a few general context engineering principles and how they show up in various popular agents like manis like cloud code and also in our recently released deep agents package and CLI. So first agent can be simply thought of as an LLM calling tools in a loop. An LLM kind of makes a tool call.Tool is executed. observation from a tool goes back to the LM and this continues until some termination condition. Now the length of tasks that AI agents can perform is ...

A Smarter Way to Talk to AI: Here's How to ‘Context Engineer’ Your Prompts► https://t.co/MZXESEAivM https://t.co/MZXESEAivM ...

AI Engineering Skill - Context engineering is rapidly becoming a crucial skill for AI engineers [1] - It's about the systematic orchestration of context, not just clever prompting [1] Context Engineering Workflow - The demo provides more information about what context engineering actually means [1] - Let's build a context engineering workflow, step by step [1]