How to Get More Out of Claude Code: 6 Features Most People Skip

If you're new to Claude Code, you're probably using it for what's immediately obvious: writing code, answering questions, editing files. That's a solid start, but it's only part of what it can do.

Claude Code can also connect directly to your systems, run repeatable workflows on demand, and enforce quality automatically. Most people don't know those features exist, let alone how to set them up.

This post will help technical founders move beyond the basics and configure Claude Code for real, repeatable workflows.

If you're just getting started with Claude Code, our guide to building apps with Claude Code is a good place to begin.

The 6 Extension Layers of Claude Code

1. MCP Servers: Connect Claude to the Tools You Actually Use

By default, Claude Code only knows what you tell it in the chat. Every session starts from scratch. You paste context, explain your setup, describe the task. It works, but the friction adds up fast.

MCP (Model Context Protocol) servers remove that friction. They're connections between Claude and the external tools your work runs on. Once an MCP server is configured, Claude can read from and write to systems like Notion, GitHub, Slack, databases, and internal APIs. No copy-pasting context. Claude works inside your operating environment.

The practical test for whether you need this: if you regularly copy something from another tool and paste it into Claude, that's a job for MCP.

There's a large ecosystem of ready-made MCP servers covering most common tools, so setup is usually a configuration step rather than a build-from-scratch exercise.

For a broader look at how these tool connections work across different AI platforms, see our AI Connectors 101 guide.

2. Hooks: Automatic Quality Gates That Don't Rely on Claude's Memory

Hooks are scripts that fire automatically at specific points in Claude's workflow. Before a tool runs. After it finishes. When a file is written. When a session starts or ends.

Practical examples: lint code before every commit, validate data before Claude writes a file, run tests when a specific action is triggered, send a desktop notification when a long task completes.

What makes hooks valuable isn't just the automation. It's that they run outside Claude's main session entirely, which means zero impact on your context window. They're deterministic. They don't depend on Claude remembering to do something. If you're building workflows where you need reliability, hooks are how you enforce it.

3. Skills: Turn Repeated Prompts into Permanent Commands

A skill is a markdown file containing a workflow, a knowledge set, or a set of instructions. You write it once. After that, it becomes either a slash command you can call any time, or something Claude loads automatically when the context is relevant.

Before skills, you paste the same 200-word prompt every time you want a code review. Or copy your brand guidelines into every content request. Or re-explain your output format from scratch. A skill eliminates all of that.

Some examples of what skills can encode:

• /deploy → stage changes, run checks, write a compliant commit message, push
• /content-brief → generate a structured brief from a prompt or URL
• /review → apply a consistent review framework on every call

Skills work across Claude.ai, the API, and Claude Code. They're the most accessible starting point because they require no code, just a markdown file. If there's one layer to start with, this is it.

If you work primarily in Claude.ai rather than Claude Code, our guide to Claude Skills and Artifacts covers the same concept applied to non-technical workflows.

4. Subagents: Specialized Workers with Their Own Context

A subagent is a separate Claude instance configured for a specific role. It has its own instructions, its own tool access, and its own output format. Critically, it runs in isolation from your main conversation, which keeps your primary session clean and focused.

This isolation matters in two ways. First, you can give a subagent a very specific job and get consistent, formatted output every time, without the variance that comes from a general-purpose assistant. Second, complex tasks that don't need your full conversation history run faster and cheaper in their own context.

Subagents are the right tool when a task is complex enough to benefit from separation: a deep research task, a document analysis, a data transformation with a strict output schema. A generalist gives you flexibility. A configured subagent gives you repeatability.

5. Agent Teams: Parallel Execution for Multi-Step Work

Most real work isn't linear. Research, drafting, validation, and formatting often need to happen at the same time. Agent teams let Claude reflect that reality.

With agent teams, a lead agent delegates to multiple subagents running concurrently. Each handles its piece of the work. The outputs are synthesized at the end. What would otherwise be a sequential process becomes parallel, and cycle time drops accordingly.

Agent Teams is the newest of the six layers, released in February 2026, and it's the most advanced. Once your individual subagents are stable and producing reliable outputs, agent teams are how you scale multi-threaded work into a single instruction.

6. Plugins: Package Your Setup So It Installs Once

Once you've built out skills, subagents, and hooks that work, the question becomes: how do you share that setup, standardize it across a team, or deploy it on a new project without rebuilding everything?

That's what plugins are for. A plugin bundles skills, subagents, hooks, and MCP configurations into a single installable unit. One command, and the entire configuration is live. Skills get namespaced automatically to avoid collisions. Versioning is built in. There's a growing marketplace of community-built plugins covering common workflows.

If you've built something that works, a plugin is how you stop rebuilding it.

The Compounding Effect (What Most People Miss)

Each layer is useful on its own, but the real shift happens when they work together.

MCP gives Claude reach into your actual systems instead of a blank context window. Skills convert your most-used workflows from ad hoc prompts into reliable commands. Hooks enforce quality at the process level, without depending on Claude's memory. Subagents handle specialized tasks with consistent, formatted outputs. Agent teams compress parallel workstreams into a single instruction. Plugins make the whole setup portable.

The same underlying model, configured with all six layers, behaves like a different product entirely — because the environment is built to support real work. That's the distinction worth building toward.

A Practical Starting Path

You don't need all six to see a significant difference. Most of the value comes from three.

1. Set up one MCP connection. Start with whichever tool you currently copy-paste context from most often. Notion, GitHub, and Slack are the most common starting points.
2. Write 2-3 skills for the prompts you repeat most. Anything you've typed more than five times is a candidate.
3. Add one or two hooks for quality gates. Linting before commits is the most common first hook.

Once those are stable and producing consistent results:

1. Build one subagent with a strict output format for a task that currently gives inconsistent results.
2. Experiment with agent teams once you have two or more working subagents.
3. Package into a plugin when you want to standardize across a team or a project.

FAQ

Do I need to be a developer to set this up? It depends on the layer. Skills are the most accessible: they're markdown files, no code required. MCP servers and hooks involve configuration files and some command-line comfort, so they're easier with a developer involved. If you're working with a technical co-founder or have engineering support, getting all six layers configured is a realistic half-day project.

Do I need all six to get value? No. Skills and MCP alone cover the majority of practical use cases. Start there. Add complexity only when a specific problem calls for it.

What's the difference between a skill and a subagent? A skill is a workflow or knowledge file you invoke as a slash command within your main session. A subagent is a full, separate Claude instance running in isolated context. Skills handle repeatable tasks inside your main conversation. Subagents handle work that benefits from its own focused environment: deep dives, specialized tasks, or anything where you don't want to pollute your primary session.

What's the difference between a skill and a plugin? Skills work across all Claude products (Claude.ai, the API, and Claude Code). Plugins are Claude Code-specific and bundle multiple extension types into one installable unit: skills, subagents, hooks, and MCP configurations. A skill is a single specialized tool. A plugin is the full toolbox.

What about CLAUDE.md? Where does that fit? CLAUDE.md is Claude Code's persistent memory file. It loads at the start of every session and stays in context throughout. Think of it as the foundation: standing instructions, project conventions, architectural decisions. It's not one of the six extension layers, but it's the right place to start before building anything else.

Is it safe to connect this to real systems and production data? Claude Code is read-only by default. Any action that edits files, runs commands, or interacts with an external service requires explicit permission. Hooks and MCP servers can operate on real data, so it's worth testing in a non-production environment first. The underlying architecture is permission-based, not autonomous.

From Chat Tool to Infrastructure

The founders getting the most out of Claude Code aren't running a smarter model. They're running the same model in a better-built environment.

These six features are what make that possible. They're all documented, all available, and free to configure. Most people just never start.

If you want help mapping these layers to your specific workflows, the AI Operator team works with founders on exactly this kind of setup — get in touch here.