#AI production systems
2614 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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·2 min
Dependency Drift in Production AI Agents: Detection, Response, and Building Resilient Systems
AI Agents in production face systemic dependency drift risks — model updates silently change outputs and silent failures are hard to detect. Learn detection strategies, hidden costs, and engineering practices.
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·2 min
Distributed AI Systems: A Practical Engineering Guide to Training, Inference, and Production Deployment
A deep dive into distributed AI systems engineering: data/model/tensor parallelism for training, KV cache, quantization, elastic scaling for inference, and cloud deployment with Kubernetes, Ray, and DeepSpeed.
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·3 min
Distributed AI Systems in Practice: A Complete Guide to Training, Inference, and Production Deployment
A deep dive into Distributed AI Systems: a new book distilling 10 years of AI engineering experience covering distributed training, inference optimization, and production model serving.
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·3 min
How to Polish AI-Generated Auth Systems to Production-Ready Quality
Learn how to polish Copilot-generated Auth systems from error-prone drafts to production-ready code, covering bug fixes, i18n replacement, and effective AI collaboration tips.
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Expert Opinions·2 min
Agent Observability in Practice: Self-Diagnostics, Implicit Signals, and Production Monitoring Systems Explained
Deep dive into AI Agent observability: self-diagnostics, explicit and implicit signal monitoring, trajectory visualization, and root cause analysis for production Agent systems.
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Tutorials·4 min
A Practical Guide to Context Engineering: The Path from Prompt Engineering to Production-Grade AI Systems
A deep dive into Context Engineering: core concepts and key techniques including RAG, long-context management, and AI Agent context orchestration for building production-grade AI systems.
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·3 min
Machine Learning Project Portfolio: A Complete Guide to Building Resume-Worthy ML Projects
From project selection to deployment, learn how to build resume-worthy ML projects. Covers end-to-end workflows, tiered project recommendations, and practical tips for ML learners transitioning from beginner to intermediate.
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·3 min
EU AI Act Article 50 Takes Effect: Failing to Disclose AI Content Is Now Illegal
EU AI Act Article 50 takes effect August 2, 2025, mandating disclosure of AI-generated content. Analysis of core requirements, exemptions, and compliance risks facing PwC and other consulting giants over AI hallucinations.
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·2 min
Voice AI Migration Pitfall Guide: Handoff Failures and Solutions During Parallel Operation
During enterprise voice AI migration, parallel operation periods often encounter context loss and unstable handoff routing. This article analyzes core pain points through real cases and provides practical solutions.
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·3 min
Why Was the Bicycle Invented So Late? The Deep Reasons Behind Technological Lag
The bicycle is structurally simple, so why wasn't it invented until the 19th century? This article explores the deep reasons behind technological lag, from materials science to cognitive biases.
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·3 min
Bonsai: A Deep Dive into Jane Street's Open-Source Functional UI Library for OCaml
Deep dive into Jane Street's open-source functional UI library Bonsai, exploring its OCaml-based incremental computation model, strongly-typed component architecture, and performance advantages for high-frequency data scenarios.
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·4 min
Should You Build or Outsource Your Agent Evaluation Framework? An Open-Source Author's Deep Inquiry
Should AI Agent reliability verification be built in-house or outsourced? An open-source author's candid question sparks industry reflection on eval frameworks.
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·3 min
Migrating C/C++ Projects to Rust: A Practical Guide to Incremental Rewriting
A detailed guide on safely migrating C/C++ projects to Rust, covering incremental strategies, FFI interop, bindgen/cxx toolchain usage, and unsafe boundary management.
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·2 min
Acrux Core: Open-Source LLM Observability Platform, a Self-Hosted Alternative to LangSmith
Acrux Core is an open-source LLM observability platform supporting self-hosted deployment with prompt management, dynamic tool binding, user feedback loops, and full-chain tracing—a free alternative to LangSmith and Langfuse.
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·2 min
Prime Agent: A Deep Dive into the RLM-Based Self-Evolving AI Agent
Deep analysis of Prime Agent's RLM architecture, exploring how self-improving AI agents achieve continuous evolution through runtime feedback loops.
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·3 min
AI Migrating COBOL to Java: Why It Copies the Bugs Too
AI code migration tools copy original bugs when converting legacy COBOL to Java. This article analyzes behavioral equivalence challenges, COBOL-Java semantic gaps, and human-AI collaboration best practices.
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·3 min
Musk's Prediction That AI Will Output Binary Directly: Why Source Code Won't Disappear
Musk proposes AI generating binaries directly, bypassing source code entirely. This article analyzes from four dimensions why this prediction is unlikely to materialize and why the intermediate layer will never disappear.
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·3 min
Cursor Browser Worker Parallelization: Practical Strategies for Working Within Rate Limits
Learn how to parallelize Cursor browser Workers from serial to parallel execution using distributed Worker pools, proxy pools, token bucket algorithms, and exponential backoff to compress 2000-3000 page scraping tasks from hours to 15-20 minutes.
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·3 min
Open Secure AI Alliance Launched: Building AI Safety on an Open-Source Foundation
The Open Secure AI Alliance launches with NVIDIA and other tech giants, building AI agent security through open-source model weights, safety evaluations, and frontier research for industry-wide standards.
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