Stop Treating AI Agents Like a Web Chat

Most people treat AI agents like a web chat. They open Claude Code, Antigravity, or another workspace agent, start a conversation, and keep it running for hours.

By the time they reach 800k tokens in the context window, every simple question like "did you finish?" costs them a massive chunk of their daily limit. They are literally burning money, waiting for slow responses, and getting degraded results.

Here is the shift: An AI agent is not a chat. It is an operator.

Think of it like a CNC machine. The operator spends 80% of the time preparing the setup. Once the setup is right, the machine executes the task from A to Z with a single command.

With agents, context is your setup. You need to invest in it, clean it, and manage it.

Because agents can read, write, and edit files directly in your workspace, they do not need to hold your entire historical chat in memory. They just need the current state of the project.

To manage this, I built a simple workflow that I use daily: pause-session and resume-session.

When a conversation gets long or I need to switch context, I do not drag it out. I just run pause-session.

My agent automatically:

• Analyzes the session context to identify key decisions and modified files.
• Generates a sharp summary file in my workspace (using a lighter model like Haiku).
• Registers it in a running session log index.

Then I clear the terminal or start a clean session with a fresh context window.

When I am ready to return, I run resume-session.

The agent reads the latest summary file, restores the exact state, checks where we left off, and asks if there are any urgent updates.

Within seconds, I am back to work in a completely clean session with zero token bloat.

This simple habit keeps the agent fast, accurate, and cheap.

The Workflows

Here are the exact workflow files I use. You can copy these directly into your agent's system prompt or workflow directory.

The Pause Session Workflow

Copy this file to your agent's workspace configuration to define how to pack up a session.

# /pause-session workflow

<objective>
Create a concise, high-quality summary of the session's context, decisions, next steps, and relevant files to ensure a smooth return later.
</objective>

<process>
1. **Analyze Session**: Review the conversation to identify key decisions, pivots, and tasks.
2. **Generate Summary**: Write a sharp, technical summary of the current project state, modified files, and next actions.
3. **Save File**: Write the summary to a new markdown file named `session-handoff-XXXX.md` in your project's `session-handoffs/` directory.
4. **Update Index**: Append a row to `session-handoffs/index.md` listing the new handoff file and a one-sentence summary.
</process>

The Resume Session Workflow

Copy this file to define how to restore the project context in a new session.

# /resume-session workflow

<objective>
Quickly bring the agent back to the exact point where the last session ended.
</objective>

<process>
1. **Find Latest Handoff**: List the `session-handoffs/` directory and find the file with the highest sequence number.
2. **Read and Present**: Load the file, read the summary, and print it to the user.
3. **Validate**: Ask the user: "We are starting from this point. Has anything changed since this handoff?"
</process>

Stop managing infinite chats. Start managing sessions.