#production-grade AI
517 related articles
·5 min
Complete Breakdown of Core Competencies for AI Agent Engineers: From Demo to Production-Grade Systems
Deep breakdown of 4 core AI Agent engineer competencies: business decomposition, multi-Agent architecture, quantitative evaluation, and engineering delivery—bridging the gap from Demo to production.
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Production-Grade LangGraph Template: A…
·2 min
Production-Grade LangGraph Template: A Practical Guide to Engineering AI Agents for Production
A deep dive into production-grade LangGraph templates covering state management, observability, error handling, and containerized deployment to bridge the gap from demo to production.
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·2 min
Agent Skills: Bringing Production-Grade Engineering Capabilities to AI Coding Agents
Google engineer Addy Osmani's open-source project agent-skills (76k+ GitHub stars) injects production-grade engineering skills into AI coding agents, covering performance, security, and code quality.
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·7 min
The Five Pillars of Production-Grade AI Agents: A Battle-Tested Guide from Demo to Deployment
Databricks tech lead Sandy shares a five-pillar framework for production-grade AI Agents—evaluation, observability, data foundation, orchestration, and governance—with a £85K retail banking failure case to bridge the demo-to-production gap.
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·3 min
Nexent Open-Source Platform: Zero-Code Auto-Generation of Production-Grade AI Agents
Deep dive into Nexent's open-source platform for zero-code production-grade AI Agent generation, covering Harness Engineering, built-in controls, use cases, and comparisons with AutoGen and CrewAI.
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·2 min
AI Agent Full-Stack Development: Architecture Principles and Production-Grade Project Implementation Guide
A comprehensive guide to AI Agent full-stack development covering LangChain, LangGraph, MCP protocol, and LLM deployment, with a hands-on Vue3 project demo showcasing the perception-decision-action loop.
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·2 min
v0 Integrates with Shopify: AI Conversations Generate Production-Grade E-Commerce Websites
Vercel's AI tool v0 announces deep Shopify integration, enabling users to generate production-ready e-commerce storefronts via natural language prompts.
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·3 min
Firebase Integrates with AI Studio: Four Core Capabilities for Production-Grade Agent Applications
Deep dive into Google Firebase's integration with AI Studio, covering four core capabilities—database auto-configuration, authentication, security rules drafting, and zero-config deployment—for production-grade AI agent apps.
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Tutorials·3 min
AI Agent Practical Development: A Complete Guide from Concept to Building Production-Grade Intelligent Agents
A deep dive into AI Agent core principles and practical development paths, covering perception-decision-execution capabilities, MCP protocol tool integration, and analysis of Manus and AutoGLM.
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·3 min
LLMOps Tool Selection Guide: An In-Depth Comparison of Tracing, Evaluation, and Governance Capabilities
In-depth analysis of LLMOps tool selection, comparing Langfuse, LangSmith, Helicone, and Orq.ai across tracing, evaluation, and governance capabilities with practical recommendations.
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·3 min
Implementing Zanzibar in Lean4: A Formally Verified Permission Engine for AI Projects
Deep dive into a Datalog permission DSL built on Google Zanzibar using Lean4 theorem prover. How formal verification strengthens AI permission management.
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·4 min
A Guide to Full-Stack Machine Learning Project Repository Structure: From Chaos to Convention
A detailed guide to organizing full-stack ML project repositories, covering directory structure design, data-code separation, and externalized configuration to help ML developers move from experimental code to production-grade engineering standards.
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·3 min
Gemini Managed Agents API Update: Environment Hooks and Free Tier Fully Explained
Google Gemini Managed Agents API introduces environment hooks, model selection, free tier support, and default model upgrades—empowering AI Agent developers with stronger execution control and lower barriers to entry.
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·3 min
From Demo to Production: The Real Challenges of Deploying LLM Systems
Deep analysis of deploying LLM systems from prototype to production: a real-world AI incident investigation assistant case study revealing key engineering challenges beyond the model.
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·3 min
From Demo to Production: The Real Challenges of Deploying LLM Systems
Deep analysis of deploying LLM systems from prototype to production: a real-world AI incident investigation assistant case revealing critical engineering challenges beyond the model.
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·3 min
ncnn Vulkan Cross-Platform Edge Inference in Practice: Solving the GPU Fragmentation Deployment Challenge
Facing GPU fragmentation on edge devices, the PostSlate team used ncnn's Vulkan backend for cross-platform ML inference, achieving 10× speedup on RTX 4070 with half the model size and zero runtime installation.
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·2 min
HuggingFace Open-Source Voice Assistant: A Complete Guide to Local Deployment
A deep dive into HuggingFace's speech-to-speech open-source project, covering its modular VAD, STT, LLM, and TTS pipeline architecture and the advantages of local deployment for privacy, cost, and latency.
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·4 min
Microsoft Open-Sources AI Agent Governance Toolkit: Comprehensive Coverage of OWASP Top 10 Risks
Microsoft open-sources agent-governance-toolkit covering all OWASP Agentic Top 10 risks through policy enforcement, zero-trust identity, execution sandboxing, and reliability engineering for production AI Agent deployment.
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·3 min
GitHub Daily · July 28: From Claude Code Skill-ification to AI Agent Governance, the Toolchain Matures
GitHub Trending July 28: Microsoft's agent-governance-toolkit covers OWASP Agentic Top 10, book-to-skill gains 366 stars showing Claude Code skill ecosystem potential, plus browser-based 3D and GIS tools.
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·2 min
Three Major Updates to Gemini API Managed Agents: Free Tier, Cost Controls, and Scheduled Triggers
Google Gemini API Managed Agents launches three key updates: Free Tier for universal access, Cost Controls for budget safety, and Scheduled Triggers for automated execution.
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