OpenAI Just Showed Us What Comes After the Harness. Here's The Layer Almost Everyone's Missing.

OpenAI just open-sourced Symphony, their internal orchestration spec for scaling autonomous coding agents, and it highlights one of the biggest shifts happening in AI engineering right now. As coding agents become more capable, humans become the bottleneck, and the real work moves from writing code to building the scaffolding around the agents.

In this video, I break down the mental models behind agent harness engineering and show you how to think about building reliable autonomous systems at scale. Whether you're trying to scale Claude Code beyond a few chat sessions, or designing orchestration into your own AI powered apps, these frameworks will help you architect systems that actually work in production.

Alibaba's Metis agent cuts redundant AI tool calls from 98% to 2% — and gets more accurate doing it

One of the key challenges of building effective AI agents is teaching them to choose between using external tools or relying on their internal knowledge. But large language models are often trained to blindly invoke tools, which causes latency bottlenecks, unnecessary API costs, and degraded reasoning caused by environmental noise. 

To overcome this challenge, researchers at Alibaba introduced Hierarchical Decoupled Policy Optimization (HDPO), a reinforcement learning framework that trains agents to balance both execution efficiency and task accuracy. 

Metis, a multimodal model they trained using this framework, reduces redundant tool invocations from 98% to just 2% while establishing new state-of-the-art reasoning accuracy across key industry benchmarks.

Andrej Karpathy: From Vibe Coding to Agentic Engineering

Andrej Karpathy (co-founder of OpenAI, former head of AI at Tesla, and now founder of Eureka Labs) talks with Sequoia partner Stephanie Zhan at AI Ascent 2026 about what's changed in the year since he coined "vibe coding." He explains why he's never felt more behind as a programmer, why agentic engineering is the more serious discipline taking shape on top of vibe coding, and why we should think of LLMs not as animals but as ghosts: jagged, statistical, summoned entities that require a new kind of taste and judgment to direct. He also touches on Software 3.0, the limits of verifiability, and why you can outsource your thinking but never your understanding.

Mistral AI launches Workflows, a Temporal-powered orchestration engine already running millions of daily executions

Mistral AI, the Paris-based artificial intelligence company valued at €11.7 billion ($13.8 billion), today released Workflows in public preview — a production-grade orchestration layer designed to move enterprise AI systems out of proofs of concept and into the business processes that generate revenue.

The product, which launches as part of Mistral's Studio platform, is the company's clearest articulation yet of a thesis that is quietly reshaping the enterprise AI market: that the bottleneck for organizations adopting AI is no longer the model itself, but the infrastructure required to run it reliably at scale.

American AI startup Poolside launches free, high-performing open model Laguna XS.2 for local agentic coding

Poolside, founded in San Francisco in 2023. has launched its two new Laguna large language models, both of which offer affordable intelligence optimized for agentic workflows (AI that does more than just chat or generate content, but can, in this case, write code, use third-party tools, and take actions autonomously), as well as a new coding agent harness called (fittingly) "pool" and a new web-based, mobile optimized agentic coding development and interactive preview environment, "shimmer," which lets you write code with the Laguna models on the go.

As Poolside wrote in a blog post today, it's spent the last few years "focused on serving our government and public sector clients with capable models deployable into the highest-security environments," yet is now going open source "to support builders and the wider research community."

Open source Xiaomi MiMo-V2.5 and V2.5-Pro are among the
most efficient (and affordable) at agentic 'claw' tasks

Xiaomi, the Chinese firm best known for its smartphones and electric vehicles, has lately been shipping some incredibly affordable and high-powered open source AI large language models.

The trend continued today with the release of Xiaomi MiMo-V2.5 and Xiaomi MiMo-V2.5-Pro, both available under the permissive, enterprise-friendly MIT License, making them suitable for use in production in commercial applications.

The most notable attribute of these models besides the open source licensing is that, according to Xiaomi's published benchmarks, they are among the most efficient available for agentic "claw" tasks, that is, powering systems such as OpenClaw, NanoClaw and Hermes Agent, in which users can communicate with them directly over third-party messaging apps and have the agents go off and complete tasks on the human user's behalf, such as making and publishing marketing content, running accounts, organizing email and scheduling, etc.

MCP vs ACP: The Two Protocols Every AI Builder Needs to Know

Most people building with AI already know about MCP, but most people don't know about a different protocol that works alongside MCP: ACP.

In this video I break down everything you need to know about ACP whether you're technical or non-technical, how ACP works and how you can build applications using ACP today.