#deterministic pipeline
356 related articles
Tutorials·2 min
3 Hours, Zero Code: Building a WeChat Mini Program with AI Agents in Practice
How to use AI Agent workflows to automate WeChat Mini Program development end-to-end in 3 hours with only 30 minutes of human involvement, featuring multi-version divergence and fusion strategies.
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Tutorials·2 min
LangChain Prompt Templates Explained: A Practical Guide to Few-Shot and Chain-of-Thought
A deep dive into LangChain prompt templates covering ChatPromptTemplate basics, Few-Shot prompting, and Chain-of-Thought techniques with RAG examples to build high-quality prompt pipelines.
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Tutorials·2 min
LangChain Agent Executor Architecture: Building a ReAct Agent from Scratch
Deep dive into LangChain Agent Executor internals, covering the ReAct reasoning-action-observation loop, tool choice strategies, and building a custom Agent Executor from scratch.
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Tutorials·2 min
OpenAI Agents SDK Tracing Guide: Zero-Configuration Agent Observability
Learn how to use OpenAI Agents SDK's built-in tracing system for AI Agent observability, covering zero-config auto-tracing, custom trace contexts, and tool call monitoring.
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Tutorials·2 min
Practical Guide to Building a Dual-Terminal Skill System with Cursor + Claude Code
A solution for Skill system conflicts in Cursor and Claude Code dual-terminal development using a three-layer directory architecture for Opus and DeepSeek differentiated configuration.
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Tutorials·1 min
Archon Deep Dive: A Practical Guide to the Open-Source AI Coding Harness Builder
Deep dive into Archon, the open-source AI coding Harness builder. Learn how orchestrating multiple AI coding Agents can boost PR acceptance rates from 6.7% to 70% through systematic AI programming engineering.
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Product Reviews·1 min
Qwen3.6-27B Open-Source Model Review: Flagship-Level Code and Multimodal Capabilities with Just 27B Parameters
Deep dive into Alibaba's Qwen3.6-27B: a 27B dense model delivering flagship-level code generation and multimodal capabilities on a single GPU with INT4 quantization.
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Tutorials·2 min
Using AI to Debug AI: Three Battle-Tested Patterns from Incident.io
Incident.io shares three battle-tested patterns for using AI to debug AI: Agent-driven Eval workflows, debug UI as file systems, and AI analysis pipelines for complex system debugging.
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Tutorials·4 min
AI Agent Memory Architecture Design: Four-Layer Partitioning + Bitemporal Modeling Practical Guide
A deep dive into production-grade AI Agent memory architecture covering four-layer partitioning, bitemporal modeling, and skill extraction to eliminate hallucinations and historical amnesia.
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Tutorials·2 min
Engineering AI Agents for Production: Four Key Challenges and a 12-Week Implementation Roadmap
90% of AI Agent projects stall at the demo stage due to insufficient engineering. This article breaks down four core challenges and provides a 12-week actionable roadmap to production.
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Deep Dives·3 min
The Essence of AI Alignment: Aligning What to Do, Not How to Do It
The core of AI alignment is aligning What to do, not How to do. Through an Alembic database migration case, learn how Harness engineering crystallizes dev standards into reusable assets for automated programming.
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Product Reviews·2 min
One Month of Vibe Coding: Lessons Learned from Building Real Projects with Zero Coding Experience
A creator with zero coding experience spent one month Vibe Coding with OpenAI Codex, completing two real projects. Here are the real pitfalls and three hard-won lessons.
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Deep Dives·3 min
Google Agent Platform Deep Dive: Building Production-Grade AI Agents with ADK, MCP, and A2A
Deep dive into Google Cloud Next 2025's Agent Platform: ADK framework, MCP integration, A2A multi-Agent collaboration, context engineering, security governance, and a marathon simulation demo.
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Tutorials·4 min
Langmanus Multi-Agent Framework Deep Dive: Architecture Principles and Agent Extension in Practice
Deep dive into Langmanus multi-agent framework architecture, explaining LangGraph orchestration with Coordinator, Planner, Supervisor and execution agents, plus a hands-on guide to adding custom agents.
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Deep Dives·3 min
NVIDIA Vera Rubin Platform Deep Dive: Solving the Scalability Challenge of Agentic AI Inference
Deep dive into NVIDIA's Vera Rubin platform Pod-level architecture and next-gen NVLink, revealing how it solves Agentic AI inference scalability bottlenecks and the industry shift from training-first to inference-first.
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Tech Frontiers·2 min
datasette-llm 0.1a7 Released: Model Default Configuration Makes Data Enrichment More Controllable
datasette-llm 0.1a7 adds model default configuration, supporting preset temperature and other parameters for specific LLMs to standardize batch data enrichment.
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Tech Frontiers·2 min
llm-echo 0.5a0: A Testing Powerhouse for Simulating Chain-of-Thought LLM Output
Simon Willison releases llm-echo 0.5a0 with a new thinking option to simulate LLM chain-of-thought output. Learn how this testing plugin streamlines AI development workflow automation.
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Tutorials·3 min
Google AI Studio Tutorial: A Comprehensive Guide to Gemini from Beginner to Advanced
A detailed guide to Google AI Studio and Gemini's three usage methods, covering YouTube video analysis, voice generation, Imagen 4 text-to-image, Gemini Live multimodal interaction, and building apps with natural language.
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Tutorials·4 min
Anthropic's Official Agent Building Guide: A Complete Breakdown of Workflows vs. Agents
Deep dive into Anthropic's Building effective agents guide: workflow vs. agent distinctions, the technical selection pyramid, and framework pitfalls for building efficient LLM agents.
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Product Reviews·4 min
n8n vs Dify vs Coze vs OpenAI: In-Depth Comparison & Selection Guide for Four Major Agent Tools
In-depth comparison of n8n, Dify, Coze, and OpenAI across automation, RAG knowledge bases, and complex Agent tasks. Includes a selection guide to help you find the best AI workflow platform.
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