Have you ever had your agent working for almost one hour only to understand that he went in the wrong direction or in the middle of something very important he ran out of context window. Me too. That's why in the last months I developed a workflow that consists in dividing a big feature into smaller markdown tasks.Hi, I'm Alex Gavesco and I'm going to present backlog MD, a tool for project management for AI agents and humans. Okay, let's start. So, have you ever seen a terminal cand board.Well, when I start ...

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 ...

If you're an AI engineer right now, your day-to-day probably looks something like this. You've got an open client in your codebase. You've got a few hugging face tabs open.You've got three different repos with the word playground in them. And you've got at least one agentic workflow that's really just stringing together a bunch of HTTP calls. Right now, everyone is talking about voice agents, MCP, and these are pretty cool technologies, but when you peel back the hype a little bit, what I hear when I talk t ...

Hi, I'm Offer from Victara. At Victara, we developed a trustworthy agent operating system. And there's a lot of really cool use cases with this like document generation, conversational AI or chat bots, either internal or external, and enterprise deep research, which I'm going to talk about today.But before I jump into Enterprise Deep Research, let me tell you a little bit more about our operating system for agents. First of all, it's a SAS platform, but also runs on your own VPC or on premise in your own da ...

Pantic AI Products & Features - Pantic AI supports temporal and other durable execution frameworks, with ongoing efforts to integrate more workflow orchestration backends [1] - Pantic AI offers tools for building AI agents, including the ability to perform web searches and analyze data [11][41] - Pantic AI's temporal agent handles the IO needed to call an LLM, including tool calls, by turning them into activities [16] - Pantic AI is developing a gateway for buying inference from various models, including observability features [61] Temporal & Durable Execution - Temporal is highlighted as a leading solution for durable execution, crucial for long-running workflows where progress preservation is essential [2] - Temporal records every activity and its inputs/outputs, enabling rerun from any point by plugging in the answers [15] - Temporal enables the resumption of workflows without adding resume code to the agent code [29] - Temporal's retry logic handles runtime errors and ensures continuous operation [22][25] Deep Research & Agent Architecture - Deep research is presented as analogous to a 20 questions game, with web search or RAG as intermediate steps [11] - The company is shifting towards viewing agents as micro-tasks that form larger autonomous task completion systems [40] - A deep research agent can be composed of multiple specialized agents, such as a plan agent, a search agent, and an analysis agent [41] Evaluation & Performance - Pantic AI evals are used to compare the performance of different models, considering factors like cost, speed, and accuracy [33] - Gemini was initially found to be faster and cheaper, but later discovered to sometimes invent incorrect answers [33][35]

This is Valberkichi, Weta's chief AI officer, and I am joined by >> Kellen Fox, head out of the product management team here at WA >> and we're both thrilled to present context platform engineering to you at the AI. engineering code summit. Now, let's kick this off with uh an announcement we're making.We're actually open sourcing our context platform engineering toolkit. And this toolkit features a really cool load generator that Kalen wrote that lets you configure agent swarms uh and agent subtasks with ve ...

Hi everybody, my name is Brian John and I'm excited today to talk to you about hacking sub agents in the codeex CLI. So who am I. I'm a principal fullstack engineer.My current focus at work is AI enablement for R&D. So think helping our R&D team members get their work done faster and with higher quality using AI. The company I work for is BetterUp.It's an awesome place to work. We've been using AI since the very beginning. I've been there for over eight years now, which is longer than any place I've ever wo ...

Product Launch & Core Concept - Command Code, a coding agent with taste, is launched after over a year of development [1] - The core idea is to build a coding agent that learns and adapts to a programmer's coding style and preferences, creating a personalized coding experience [3][4] - Command Code aims to address the sloppiness and lack of personalization in existing LLM-based coding tools [12][14][16] - Taste models are introduced as a way to capture and share coding intuition and intentions, potentially revolutionizing code generation [28] Technology & Architecture - Command Code utilizes a meta-neurosymbolic architecture with reinforcement learning to create a deterministic and explainable system [9][22][23] - The architecture combines LLMs with a "taste" model, which is a representation of the user's coding preferences [24] - Reflective context engineering enables the system to continuously learn and adapt to the user's evolving coding habits [25] - The system uses both explicit and implicit feedback to refine the neurosymbolic space and enforce the user's coding choices [24] Business & Market Opportunity - Langbase, the company behind Command Code, raised $5 million from investors [11] - The company aims to build a large ecosystem around taste models, enabling developers to share and leverage coding styles [27] - Command Code has shown internal gains at Langbase, with a 10x increase in code merged to the main repository and a significant reduction in code review time [32] - The product targets individual developers, teams, and enterprises seeking to improve coding speed, consistency, and maintainability [29]

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 ...

your app's infrastructure should fix itself. Let me show you. So, right now I'm on the Rayway dashboard and I have a bunch of services that are deployed and all of these services have one thing in common.They all have bugs and problems. So, for example, this service has a memory leak. If I click on it, go to metrics, we can just see memoryization keeps growing high and very quickly.This is just a sign of a memory leak and pretty sure the service would eventually crash. If I look over at the amount of reques ...