131 related articles

Can you learn MLOps from scratch? This guide breaks down core skill requirements and offers a practical 4-phase, 24-month roadmap covering Python, ML, DevOps, and MLflow.
AI Costs Out of Control: Real-World St…
More enterprises are finding AI operational costs spiraling out of control. This article dissects token billing traps and blind flagship-model use, and maps out cost-reduction strategies like model routing, open-source self-hosting, and semantic caching.

A comprehensive analysis of ASP.NET Core's architecture and technical strengths: cross-platform deployment, high-performance Kestrel server, modular middleware, built-in DI, and modern web capabilities like Blazor, gRPC, and SignalR.

A deep dive into the five genuinely tough challenges of production MLOps: fault-tolerant training on Spot instances, cross-team GPU scheduling, data reproducibility, model observability, and inference cost optimization.

An in-depth look at Terraform's core principles and workflow, covering declarative configuration, the multi-cloud Provider ecosystem, IaC best practices, and license changes. Helps DevOps engineers master the industry-standard tool for infrastructure automation.

Microsoft open-sources dotnet/skills, packaging .NET/C# best practices as structured skills for AI coding agents. Bridges domain knowledge gaps in general LLMs, improving code quality for GitHub Copilot and other tools.

How can new graduates transition from software engineer to platform engineer? This article breaks down the path of joining as a Grad SWE first, then transferring internally, analyzes C# vs Python trade-offs, and offers a 14-month prep plan for AI/ML infrastructure.

GitHub trending project exercises-dataset features 433 fitness exercises with target muscles, equipment types, instructions, and animation demos—ideal for fitness apps, AI coaches, and RAG systems.

The full GPT-5.6 model lineup is live. How can domestic developers access it at low cost via API relay stations? This article explains the principles, registration, token setup, client integration, and key risks.

A developer's real case of building a dental clinic management system with GitHub Copilot and Azure SQL, revealing AI coding limits in cloud security config and how Human-in-the-Loop breaks through.

This article breaks down Azure SQL Database's progressive cost-optimization strategy from the free tier to Hyperscale, Serverless auto-scaling, and Elastic Pools, helping teams balance performance and budget.

July 11 GitHub Daily: Three Agent Skills projects surge on the same day, signaling AI programming's shift to skill standardization, with cross-platform open standards and local Agent memory leading the way.

Step-by-step guide to deploying Dify locally: Docker setup, Docker Compose installation, source code configuration, .env file setup, and container startup for Windows, macOS, and Linux.

Databricks open-sources Omnigent, a Meta-Harness for orchestrating Claude Code, Codex, and more AI coding assistants together—with built-in guardrails, cross-model workflows, and real-time collaboration. Get started in 10 minutes.

A deep dive into Anthropic's Agent Skills architecture — clarifying its difference from MCP, and how modular Skill packages enable scalable, maintainable enterprise agent development.

An in-depth walkthrough of deploying Dify 1.8.0 and building applications: three-step Docker deployment, five app types compared, and Workflow vs Chatflow use cases—build enterprise AI apps with zero code.

A deep dive into LangChain's positioning and value—why do LLMs need a middle layer? How does LangChain serve as the 'glue' unifying multi-model interfaces and supporting Agent development? Learn its core modules and learning path.

From Prompt Engineering to Harness Engineering, a deep dive into the core challenge of truly deploying AI Agents in enterprises. This article breaks down the six-layer architecture and shares real-world Hermes Agent practice.

Geosql is a geospatial SQL skill pack designed for AI coding assistants like Claude and Codex, enabling LLMs to accurately generate PostGIS queries and handle coordinate transformations and spatial analysis.

A must-read for test engineers: use Cursor's custom Skills to auto-generate test cases covering positive, negative, and boundary values from PRDs, output as Markdown linked to XMind, adapting to functional, interface, and performance testing.