Claude Code cheat sheet: how small teams actually use Anthropic's coding agent

There are now more AI coding tools than most people can keep straight, but one keeps coming up in small-business automation circles for a different reason than "it writes code": Claude Code, Anthropic's command-line agent, is increasingly used to build the internal tooling — lead scoring, Slack bots, invoicing scripts, outbound sequences — that used to require hiring a developer for a week. This guide explains what it actually is, how it's structured, and where it earns its keep for a small team.

What Claude Code actually is

Claude Code is a coding agent that runs in your terminal. You install it, type claude, and describe what you want in plain language — "read this CSV of leads and score them by fit," "build a Slack bot that posts a daily summary," "fix the bug where invoices don't total correctly." It reads your files, writes and edits code, runs commands, and iterates until the task is done, instead of you copy-pasting snippets out of a chat window.

The distinction that matters for a non-developer: a chat assistant tells you what code to write. Claude Code writes it, runs it, and checks whether it worked.

Getting it running

Setup is short: install Git and the GitHub CLI, install Claude Code itself (npm i -g @anthropic-ai/claude-code, or the one-line installer from Anthropic's site), then type claude in any project folder to launch it. No separate IDE is required — it runs alongside whatever editor you already use.

CLAUDE.md: the rulebook

The single most useful concept for a business context is CLAUDE.md — a plain markdown file at the root of a project that Claude reads at the start of every session. This is where you put the things a new hire would need to know: who your company is, what your product does, your brand voice, your tech stack, and any rules you don't want broken ("never delete a customer record," "always confirm before sending an email"). Written once, it's read every time, so Claude doesn't need to be re-briefed on every task.

Folder structure and skills

Larger setups organize this context into a folder — company overview, team roster, brand voice, a wiki of reference docs — so the project stays navigable as it grows. On top of that sit skills: reusable playbooks for a specific recurring task, like drafting outbound emails in your voice or handling a discovery-call follow-up the same way every time. You write the playbook once; Claude follows it on demand instead of you re-explaining the task each time.

Hooks: the safety net

Because an agent that can run commands and edit files is genuinely powerful, hooks matter more here than in a plain chat tool. Hooks are rules that intercept specific actions — sending an email, pushing code, deleting a database table — and require explicit approval before they run. For a small business, this is the setting that turns "an AI with terminal access" from a liability into something you can actually leave running.

Connecting it to other tools

Claude Code connects to outside services three ways, in increasing order of control: one-click OAuth connectors for common apps, MCP (Model Context Protocol) for services that expose an API, and direct CLI tools for the most efficient terminal-based integrations. In practice this means it can read your CRM, post to Slack, query a database, or trigger a workflow tool like n8n or Zapier — the same connections a human assistant would need, wired up once.

Slash commands worth knowing

A handful of built-in commands are worth learning immediately: /clear starts a fresh session to save tokens, /compact shrinks a long conversation before it fills up, /model switches which model you're paying for by the task, /plan makes Claude ask clarifying questions before acting instead of guessing, and /diff shows exactly what changed before you accept it. Starting any nontrivial task with /plan is the single habit that prevents the most wasted work.

Where this actually pays off for a small business

The realistic use cases aren't "replace your engineer." They're the tasks that fall in the gap between "too small to hire for" and "too tedious to do by hand":

• Content drafts — blog posts, LinkedIn posts, case studies, pulled from your own source material instead of written from scratch.
• Data enrichment — lead research, ICP scoring, cleaning a messy spreadsheet export.
• Light automation — Slack bots, webhook handlers, a script that syncs two tools that don't talk to each other natively.
• Sales ops — drafting outbound sequences, follow-ups, and proposals from a template and a contact list.
• Finance admin — bulk payment files, invoice generation, payroll exports, formatted the way your accountant actually wants them.

None of these need a full-time engineer. Most of them need someone who can describe the task clearly and review the output — which is a lower bar than it sounds.

The honest caveat

Claude Code is still an AI system: it will occasionally misread a requirement, write code that runs but does the wrong thing, or need a second pass. Hooks and /plan reduce this, but don't eliminate it — anything that touches customer data, money, or a production system should get a human review before it ships, the same rule that applies to every AI tool on this site. Treat it as a fast, tireless junior developer, not an autonomous one.

If you're deciding whether a tool like this belongs in your stack at all, that's exactly the kind of call our AI plan quiz is built to help with — two minutes, and you get a shortlist matched to what you actually need, not a generic top-ten list.