Problem · ChatGPT Is Not Automation

You use ChatGPT every day. Writing code, generating texts, debugging errors. It feels like AI is already integrated into your work. But look at what actually happens in practice:

Bottom line: you’re not eliminating work — you’re shifting it. Instead of writing code, you write prompts. Instead of debugging — you explain context. The workload hasn’t decreased. It changed shape.

Solution · Second Brain with Claude Code

Claude Code works differently. It runs inside your codebase. Terminal, file system, git — all directly accessible.

This is a fundamental difference. You don’t bring context to AI — AI is already in the context.

It’s not about which prompt to write. It’s about what context the model has. Prompt engineering is overrated. Context management is not.

Step 1 · Project Knowledge Base

The main technique is dead simple. After each working session, you tell Claude:

Update what we did today on the project.

Claude writes the results into local markdown files. Decisions, architecture choices, known bugs, coding conventions — all in a structured format.

Why this works

Compound effect. After a week, Claude has context from the last 5 sessions. After a month — a full project map. After three — Claude knows more about the project than most team members.

Each new session starts not from zero, but from an accumulated base. You don’t need to explain that UserService handles auth or that deploy.sh is the production script. Claude already knows.

How this looks in MILAGPT

In MILAGPT we use several files for different types of memory:

All of these are plain markdown files in the repository. You can see them, edit them, commit them to git. No black box.

Step 2 · Custom Skills

The knowledge base is memory. Skills are abilities. Together they provide full automation.

A skill is a saved workflow in markdown. A process description that Claude executes on command. The idea is simple:

1. You do the process manually once, with Claude
2. You say: “turn this into a skill”
3. Claude creates a reusable workflow
4. Next time: one command — and the process runs

The magic is in the combination

A skill without context is just a script. Context without a skill is just memory. But context + skill is when the assistant knows your project AND knows your processes.

Imagine: you say /ship-post. Claude:

• Checks the latest commits
• Knows your announcement format (from the knowledge base)
• Generates a post for Slack/Telegram
• Considers style and audience (from SOUL.md)

Zero prompts. Zero copy-paste. One command.

Examples · What You Can Automate

Four workflows we use every day:

Key Insight · Context > Prompt

Think about onboarding a new developer. On day one they ask basic questions. After a week — they understand the architecture. After a month — they solve tasks independently. After three — they explain the project to others.

You don’t write them a “prompt” every morning. You explained the context once — and then they work on their own. Knowledge compounds.

Claude Code works the same way. The difference is:

Stop optimizing prompts. Start building context. A prompt lives for one session. Context lives as long as the project exists.

Comparison · ChatGPT vs Claude Code

Getting Started · Three Actions Today

You don’t need to rebuild your entire workflow in a day. Start with three simple steps: