Anthropic recently solidified its strategy within the Artificial Intelligence (AI) assisted software development ecosystem with the launch of Claude Code Web and the introduction of the Claude Skills feature. These tools not only aim to fill usability and competitive gaps (direct competition with Jules, Codex Web, and Cursor Web), but also to redefine the efficiency of context management for AI agents. Such additions confirm the trend for major market players to develop integrated ecosystems rather than isolated tools.
Claude Code Web (the web agent) was developed to make cloud software development more accessible, eliminating the need for deep knowledge of the Command Line Interface (CLI) or high-performance hardware. Notably, the beta version stood out for being less prone to initial bugs compared to competing solutions. The platform easily integrates with GitHub, allowing users to select repositories and create pull requests directly upon task completion.
From a technical standpoint, the Claude Code Web development environment utilizes virtual machines (VMs) for each code execution. This approach is fundamental for security control, allowing detailed configuration of network access (such as "custom access" or "verified sources") and the management of environment variables. These controls are crucial for developers working in corporate environments with strict security and data retention restrictions. Additionally, the web agent has a significant technical differentiator: the "open in CLI" function, which allows for the continuous migration of the web session to the local Claude Code CLI environment. This enables fine-tuning, such as manual selection of the LLM model (e.g., Opus 4.1 or Sonnet 4.5), which is not directly configurable during the web task execution.
The Claude Skills feature (Agent Skills) represents an advancement in context management and task standardization. A skill is a folder containing instructions, scripts, and resources, automatically triggered by the model (model invoked) when relevant to the task. They are ideal for lightweight, well-defined, and template-driven tasks, such as code formatting or applying brand guidelines.
The core value of skills lies in their token efficiency, achieved through the principle of Progressive Disclosure. In contrast to loading global rules into cloud.md files which can unnecessarily consume thousands of tokens, skills initially load only the metadata (name and description), which requires about 100 tokens. The remaining content of the skill (instructions and references, potentially reaching 5,000 tokens or more) is loaded only if the skill is invoked. This approach is significantly advantageous compared to Multi-Channel Plugins (MCPs), which often consume a large amount of irrelevant context tokens, regardless of immediate utility.
From the agentic architecture perspective, skills differ from Subagents. Skills operate within the main context window, facilitating follow up and context retention. Subagents, on the other hand, operate in an independent subcontext, discarding all their working context upon task completion and returning only the final output. Another difference is that subagents allow for the definition of a specific LLM model (Haiku, Opus, Sonnet) for the task, whereas skills are viewed as tools that the model utilizes cohesively.
The composable nature of skills allows developers to create Standard Operating Procedures (SOPs) for the agent. This may involve executing scripts in languages like Python or Node.js within the Claude Code VM, or applying specific code rules (for example, forcing variable declaration with VAR in Dart/Flut of labor between the developer and AI. The developer's role now focuses on review and architectural planning, while the AI specializes in consistent code generation and the execution of standardized tasks, utilizing skills to ensure greater speed and consistency in the daily workflow.ter projects, despite being poor practice). This specialization capability enables the agent to become a "self-improving agent," internalizing the company's codebase conventions into a skill for consistent future use.
In summary, the new Claude Code features—both the web agent that democratizes access and the Skills system that optimizes token usage—signal an evolution in the division of labor between the developer and AI. The developer's role now focuses on review and architectural planning, while the AI specializes in consistent code generation and the execution of standardized tasks, utilizing skills to ensure greater speed and consistency in the daily workflow.