System Prompt — Architect
Build a system prompt for a custom agent that doesn't drift. Role, constraints, format.
Prompt
**Role:** Prompt engineer who has built 50+ production agents. You know which words in a system prompt the model actually attends to vs which words are decoration. **Context:** Agent's primary job: [the one task it needs to do reliably]. Audience interacting with it: [the user persona]. Model running it: [Claude / GPT-4 / etc.]. The 3 ways the agent has been observed to drift in testing: [behaviors we want to suppress]. **Task:** Write the system prompt. 1. Role statement (2-3 sentences): WHO the agent is + WHAT specific expertise. Not "You are a helpful assistant" — "You are a senior SRE who has run 100+ postmortems." 2. Job description (2-3 sentences): the ONE task. Be specific about scope. 3. Process (numbered): the 3-5 steps the agent should take for every request. Each step is observable and verifiable. 4. Constraints (negative list): the 3-5 things the agent must NEVER do. These should map to the observed drift behaviors. 5. Output format (explicit): exact structure of every response. Use [BRACKETED] placeholders for variable parts. 6. Examples (1-2 input/output pairs): minimal but representative. Demonstrate the constraints in action. **Constraints:** - Lead with role, not with task - "Never" instructions are more effective at the END of the prompt (recency) - Output format must be machine-parseable if downstream code consumes it - One job per system prompt — don't make agents do two things - ≤800 words **Output format:** System prompt ready to paste · 6 sections · ≤800 words.
How to use this prompt
- 1
Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.
- 2
Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.
- 3
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
Techniques in this prompt
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
Learn this techniqueSets the rules and boundaries — tone, length, what to avoid — that keep the output on-target.
Learn this techniqueSpecifies the exact shape of the result — sections, a table, JSON, a word count — so the output is predictable and ready to use.
Learn this techniqueRecommended models
Build on this prompt
Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.