Reference

Best Practices & Guides

Best practices for AI cost management: budget strategies, model selection, prompt optimization, team attribution, and monitoring workflows.

Budget Strategy

Set Daily Caps, Not Just Monthly

A runaway agent can burn your monthly budget in a single day. Set daily caps at 1/25th of your monthly budget (accounting for weekends).

Monthly budget: $2,500


Daily cap: $100 (with auto-stop)


Alert at: $50 (50%), $80 (80%), $100 (100% → auto-stop)

Budget Per Project

Don't use a single org-wide budget. Create per-project budgets so a spike in one project doesn't affect others.

Include a Buffer

Set your operational budget at 80% of your actual budget. The 20% buffer absorbs traffic spikes without triggering auto-stop.

Model Selection

The 80/20 Rule

80% of your requests probably work fine with the cheapest model. Identify the 20% that need premium models and route accordingly.

Benchmark Before Switching

Before migrating from GPT-4o to GPT-4o-mini:

  • Take 100 real production prompts
  • Run them through both models
  • Score outputs (automated or human)
  • Accept the switch only if quality stays above your threshold

    • Consider Latency

    Cheaper models are usually faster. GPT-4o-mini is 3-5x faster than GPT-4o. For user-facing applications, this speed improvement is a bonus on top of the cost savings.

    Prompt Optimization

    Compress System Prompts

    Audit every system prompt quarterly. Common bloat sources:

  • Restating default model behavior ("You are a helpful assistant")
  • Redundant formatting instructions
  • Example outputs that could be shorter

    • Use Structured Output

    Request JSON responses when you need structured data. This reduces output tokens and makes parsing reliable:

    Instead of: "Analyze this text and tell me the sentiment, key topics, and a summary."


Use: "Return JSON: { sentiment: positive|negative|neutral, topics: string[], summary: string (max 50 words) }"

    Cache Repeated Prompts

    If the same prompt produces the same output, cache it. Common candidates:

  • FAQ responses
  • Classification of known categories
  • Template-based generation with identical inputs

    • Team Attribution

    Tag Everything

    Use metadata tags consistently across your organization:

    project: "customer-support"


feature: "ticket-summary"


team: "support-engineering"


environment: "production"


userId: "user_123"

    Monthly Cost Reviews

    Schedule a 15-minute monthly review:

  • Total spend vs. budget
  • Cost per project — any surprises?
  • Model mix — are expensive models overused?
  • Top 10 most expensive features
  • Optimization opportunities from Autopilot

    • Monitoring Workflows

    Daily Check (2 minutes)

  • Glance at the dashboard widget
  • Check for any anomaly alerts

    • Weekly Review (15 minutes)

  • Cost trend: up, down, or flat?
  • Any budget alerts triggered?
  • Review Autopilot recommendations

    • Monthly Deep Dive (30 minutes)

  • Full cost report by project, model, and feature
  • Benchmark cheapest alternatives for top-3 expensive models
  • Update budgets based on actual usage
  • Implement top optimization recommendations