A personal reflection on transitioning from frontend development to roles such as product manager, project manager, and system operations: why the shift is considered, the differences between these roles, and what transferable skills were gained from past small-team experiences.
Starting from the differences between toC Agents and enterprise-level AI pre-sales bots, understand the applicable boundaries of Skill and RAG.
As AI becomes increasingly adept at writing code, the real differentiator will be the engineering system: context, tools, task orchestration, feedback mechanisms, and architectural guardrails.
From HTTP APIs, official SDKs, AI development frameworks, low-code platforms to AI programming tool SDKs, this article outlines 5 patterns of AI application development and a subsequent learning roadmap.
As AI makes coding increasingly affordable, programmers should prioritize enhancing their skills in requirement judgment, architectural trade-offs, and outcome accountability.
When AI-generated code logic reveals bugs days later, and you can't immediately spot the issue or even understand your own work, how do you optimize the development process? The approach: first align with the current state, then modify the code, and finally review and document decisions.
Using a real homepage redesign, this article explains what the frontend-design skill can do, how to use it, how to iterate, and exactly how far it can help.
A breakdown of how the provider layer is implemented in this project, explaining why heavy abstraction was avoided and how the text and image pipelines are consolidated.
Deconstructing the automated publishing pipeline of this site to reveal how English drafts and article covers are generated before submission.
Introduces the responsibility boundaries, adaptation scenarios, recommended combinations, and common pitfalls of Rule, Skill, and MCP in React frontend engineering.
A comprehensive guide from creation, writing, and invocation to implementation, explaining how to break down, write, and avoid turning Skill into a universal Prompt.
From creation and breakdown to writing and implementation, clarify where to place Rule, what to write, and how to ensure AI consistently adheres to it over time.
From recommending commonly used MCPs for frontend, configuring ready-made servers, to structuring, invoking, and implementing custom MCP Servers, this guide clarifies how to effectively implement MCP in practice.
