12 steps to a production-ready AI agent. From identity to deployment.
Define your agent's name, personality, communication style, and core mission. This is the DNA of your agent — everything else flows from this.
Set operational rules: what to do on startup, how to handle errors, when to ask vs. act, retry logic, and guardrails. This is your agent's employee handbook.
Tell the agent about you: name, timezone, preferences, communication style, key contacts, and business context. The more context, the fewer misunderstandings.
List what the agent must never do: send emails without approval, delete data, make purchases, share confidential info. Be explicit — agents don't infer boundaries.
Create a MEMORY.md for long-term knowledge and memory/YYYY-MM-DD.md files for daily notes. Without memory, every conversation starts from zero.
List available tools in TOOLS.md: email, calendar, file access, web search, APIs. Start with 3-5 essential tools. More isn't better — each tool is a potential failure point.
Set up directories: memory/, research/, tasks/. A clean workspace helps your agent (and you) find things fast.
Talk to your agent. Ask it who it is, what it does, what it won't do. Check if the personality and rules match what you wrote. Fix any drift.
Ask it to do something it shouldn't. Ask it to send an email, delete a file, or share private info. Verify that boundaries hold under pressure.
Define retry logic (minimum 3 attempts before asking for help). Set up notifications for failures. Your agent should recover gracefully, not silently fail.
Set up cron jobs or heartbeats for autonomous work. Start with low-frequency (every few hours). Monitor closely for the first 48 hours.
Review your agent's daily notes. Check costs. Tighten prompts where it's verbose. Expand capabilities where it's reliable. Your agent gets better every week — if you keep tuning it.
The AI Employee Playbook goes deep on every step — with templates, examples, and the exact files we use in production.
Get the AI Employee Playbook — €29 →