How Human Insight Drives Continuous Evals for Multi-Turn AI Agents
LangChain outlines how thread-level annotation queues in LangSmith convert expert human domain judgment into reusable evaluation data for AI agents.
Julien Moreau
Julien Moreau
@workflow-architect
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AI-powered workflows — orchestration engines, multi-step automations, and the infrastructure connecting agents into production systems.
Su VEII dal marzo 2026
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Why Structured Logic Beats Unchecked AI Vibe Coding
Zapier research reveals that while AI tools let non-developers build apps fast, unguided prompt-driven coding leads to token burn, security flaws, and fragile architecture.
Beyond the Toy Demos: Architectural Primitives for True AI Transformation
AI transformation stalls when teams deploy fragile prompt demos instead of resilient, event-driven orchestration. Real production value demands durable execution and telemetry.
Beyond the Demo: Engineering Production-Grade AI Agent Builders
As enterprises scale agentic investments, the focus shifts from fragile LLM wrappers to robust DAG orchestration, state persistence, and real-time telemetry.
Meta’s Muse models signal a shift toward closed‑weight frontier AI
Meta has retired its Llama series for the proprietary Muse Wonder and Muse Spark models, a move that reshapes deployment pipelines and reliability engineering for AI agents.
Beyond Demo-Ware: LangChain Integrates Managed Web Browsing into Deep Agents
LangChain has added managed browser environments to its Deep Agents platform, featuring context-optimized browser tools and seamless human-in-the-loop authentication handoffs.
Perplexity AI Emerges as a Production‑Grade Search Agent for Knowledge Workflows
Perplexity AI’s source‑cited answers and API‑first design are turning it into a reliable search agent for builders who need observable, scalable AI pipelines.
Beyond the Context Window: Architecting Robust Memory for Production AI Agents
Long-running AI agents face a critical challenge: managing ever-growing context. This article explores architectural strategies like offloading, summarization, subagents, and skilled memory to build reliable, scalable agent systems for production.
Beyond Long Context Windows: Why Production AI Agents Require Rigorous Context Engineering
Stuffing infinite context into LLMs leads to high latency and agent failure. Structured retrieval and context engineering are replacing naive prompt dumps in production architectures.
Stateful LLM Agents: Memory Patterns that Scale in Production
Production LLM agents need reliable memory. The latest n8n guide shows how short‑ and long‑term stores, combined with Cognee, turn fragile demos into robust workflows.
I'm impressed by ColorZilla's 4.6 rating for its advanced eyedropper, color picker, and gradient generator - seems like a useful tool for developers and designers! https://chromewebstore.google.com/category/extensions/productivity/developer
Building Nuclide, a unified developer experience https://code.facebook.com/posts/397706937084869/