65 results found

Splitting Vitest test runs into parallel shards with GitHub Actions slashed continuous integration (CI) wait times from 15 minutes to just 4.5 per pull request. This article details the simple configuration changes and workflow optimizations that brought dramatic productivity gains for the whole team.

A visual guide to understanding where AI should run, including local LLMs, chat apps, coding agents, MCP, APIs, CLIs, AgentOS, and BYO LLM architectures. Learn how context, tools, permissions, and governance shape the right AI workflow.

Clarifies responsibilities across Skills, MCP servers, CLIs, and APIs for AI dev workflows—keeping auth, permissions, and audit boundaries clean.

Launch an AI-guided tool to migrate from Contentful to Contentstack, moving content and rewriting app code via deterministic CLI steps.

This article discusses the tension between rapidly expanding enterprise AI capabilities and the need for strong governance, introducing a two-layer architecture: off-platform AI for experimental reach and on-platform AI for trusted, governed execution. It explains how combining both layers allows organizations to benefit from flexible, distributed AI while maintaining oversight, brand integrity, and risk management.

Learn how Contentstack CMS, Lytics, and Personalize work together to deliver real-time personalization using structured content, user data, and edge decisions.

This article explores why generic SaaS dashboards are becoming outdated as modern APIs, SDKs, scaffolding, and AI-assisted development enable teams to quickly build bespoke interfaces tailored to their exact workflows. It discusses how platforms should provide core infrastructure while teams take ownership of the experience layer, and examines both the benefits and trade-offs of this new paradigm.

Learn how Mastra-style workspaces and markdown skills (SKILL.md + references) provide structured context for Agentic RAG agents and tools.

This article explores how advances in AI and automation have transformed programming from a required task for software production into an act of creative expression, much like knitting transitioned from necessity to craft. The author discusses the enduring value of foundational development skills and predicts a future where coding by hand is a rewarding choice rather than a job requirement.

This policy defines the minimum security requirements for building, publishing, and maintaining Agent Skills within the Contentstack ecosystem. It protects users, content, and systems from prompt injection, unsafe markdown rendering, and model hallucinations.

AI assistants are now part of every developer's workflow. This post covers why we built developers.contentstack.com to serve both humans and agents, and how to connect any MCP-capable client to start building on top of it in minutes.

This article explores how Codex, given a management token, API key, and precise schema documentation, imported content flawlessly and even built a custom CLI and skill to repeat the process, raising questions about the future relevance of MCP in content operations.

This article explores how AI has radically reduced the cost of producing things, shifting the real bottleneck from implementation to judgment. It argues that taste—the ability to decide what is truly worth building—and genuine rest are the new sources of leverage in a world of fast, cheap output.

This article challenges the common belief that AI will replace developers, suggesting instead that AI actually increases developers' value by boosting their productivity and exposing inefficiencies in non-technical roles. The real organizational shift is towards reducing layers between problems and code, making developers more essential than ever.

The Launch API does more than trigger deployments. It gives teams the building blocks to shape their own release workflow, from environments to logs to cache revalidation, in the tools they already use.

With AI agents capable of generating production-ready clients from well-designed APIs and OpenAPI specs, the traditional necessity of hand-crafted SDKs is being challenged. This article explores the shifting role of SDKs, the benefits of leveraging AI for client generation, and when vendor-maintained SDKs may still hold value.

Developer teams migrating from legacy systems to modern architecture often exacerbate technical debt by carrying over outdated patterns and habits. This article explores common pitfalls and offers guidance on how to successfully transition by embracing new paradigms and thorough discovery.

This article offers a pragmatic perspective on using AI agents for software development, emphasizing best practices such as clear task scoping, environment cleanliness, and practical workflow management. Learn how to avoid common pitfalls, structure effective collaborations, and maximize reliability from AI coding agents.

Explore context engineering in AI, how it enables adaptive digital experiences, and real-world examples of its implementation—including Contentstack's approach to context-driven operations and agent OS. Learn why context is vital for LLMs and how it shapes effective and intelligent AI agents in modern enterprises.

AI-powered development tools are making coding more accessible, but true success relies on understanding coding fundamentals. Learn why improving your coding skills dramatically increases the effectiveness of AI tools and helps you avoid common pitfalls like security vulnerabilities and deployment issues.