#reasoning trace reuse
178 related articles
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AI Agent Ecosystem Weekly: Harness Plugin Explosion, GLM 5.3 Guardrail Controversy & Stripe's OpenRouter Acquisition
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From Backend to Agent Engineer: What P7 Interviews Really Test
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Reusing LLM Inference Across Users: Exploring the Feasibility of Knowledge Graph Caching
Exploring cross-user LLM inference reuse via knowledge graph caching, analyzing the boundaries of semantic caching, GraphRAG, KV-Cache, and the engineering challenges of reasoning process reuse.
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·3 min
DeepSeek Harness In-Depth Review: An AI Coding Agent Where Everything Is a Plugin
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Hermes Agent Meets Grafana: A Practical Guide to AI Agent Observability
Explore why AI Agents need observability and how Hermes Agent integrates with Grafana for metrics, tracing, and log analysis to build stable, production-ready agent systems.
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AI Agent Reliability: 10 Open-Source Projects Solving the 'Can Do the Work, Can't Prove It' Problem
10 open-source projects tackling AI Agent reliability—from prompt orchestration and visual evidence to sandboxes, memory management, and state persistence for verifiable coding Agents.
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Spring AI 2.0 in Practice: A Complete Guide to Building a Code Generation Agent from Scratch
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What Are Agent Skills? A Comprehensive Guide to the AI Agent Development Architecture Paradigm
Deep dive into Agent Skills architecture for AI agents, covering Skill framework definitions, MCP protocol, multi-agent collaboration, and practical applications for building enterprise-grade Agent systems.
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Taku AI: Turn Expert AI Workflows Into Your Desktop App with One Click
Taku AI hit #1 on ProductHunt, letting users borrow, remix, and run others' AI workflows as desktop apps without setup. Deep dive into its potential and open questions.
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AI Agent Testing in Practice: Five Core Focus Areas and Quantitative Evaluation Methods Explained
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Ballet: Codifying AI Workflows to Deliver Deterministic Results Every Time
Ballet converts natural language workflows into deterministic code execution, with audit logs, one-click rollback, simulation mode, and enterprise features to solve AI Agent reliability challenges.
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Yadda 3.0: A New BDD Testing Paradigm for the AI Agent Era
Explore how Yadda 3.0 combines BDD with AI Agents, using natural language test specs as human-AI acceptance contracts and redefining BDD's role in the AI era.
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CLI-Anything: The Open-Source Tool Making All Software Agent-Native
CLI-Anything is an open-source project from HKU that wraps software into CLI interfaces for Agent-Native access, enabling AI Agents to directly call various tools. With 47k+ Stars and its CLI-Hub ecosystem, it's redefining how software connects with AI Agents.
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34 Model Iterations in Review: Most Problems Were Actually in the Evaluation Pipeline
After 34 model iterations, an AIOps engineer found most gains came from evaluation bugs. This article details three critical evaluation pitfalls and solutions for MLOps practitioners.
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·5 min
Harness: The Operating System That Takes LLM Agents from Demo to Production
Deep dive into Harness technology: how context engineering, memory management, and multi-agent architecture transform LLM agents from stochastic demos into stable production systems.
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·3 min
Java Backend to AI: A Practical Guide to Multi-Agent Collaboration with Spring AI
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The Overlooked "Boring" Infrastructure Behind Production-Grade AI Agents
Exploring the core challenges of AI Agents moving from demo to production: idempotency, approval states, retries, action ledgers, audit tables, and other critical infrastructure design patterns.
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·6 min
Stimma: An Open-Source Creative Workbench Built on Top of ComfyUI, Solving Media Management and Multi-GPU Scheduling
A veteran user spent a year building Stimma, an open-source desktop app on top of ComfyUI that solves media asset management, multi-GPU load balancing, and agent-driven creation with local-first design.
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Mu: A Standardized Toolset Platform Designed for AI Agents
An in-depth analysis of Mu, a toolset platform built for AI Agents, exploring the importance of Agent tooling, Mu's design philosophy, competitive landscape, and its value in AI deployment.
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·4 min
Cursor Token-Saving in Practice: 8 Efficient Techniques to Reduce Usage
Learn 8 automatable techniques to reduce Cursor Token usage, including .cursorrules configuration, precise context control, model tiering, and more to cut AI coding costs.
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