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🧠 Using ClaudeCode as Sage (Without API Costs)

Location: owl-strategy/strategy/claude_as_sage.md

This document explains how to leverage ClaudeCode (via Anthropic’s Claude Max plan) as a stand-in for the Sage agent during early development and testing of Promptable.ai and OWLStacks — without incurring additional API expenses.

🎯 Goal​

Enable rapid iteration and daily training of generative quests using ClaudeCode, while emulating the behaviors and architecture intended for the future Sage agent.

✅ Why Use ClaudeCode​

  • You already have access through Claude Max (no additional cost)
  • ClaudeCode supports large context windows
  • Excellent for prompt-based development, chaining, and in-editor reasoning
  • Can simulate agentic thinking with persistent context and structured prompts

🧩 Strategy for Treating ClaudeCode Like Sage​

1. Seed Prompt Simulation​

Use prompt_seed.md as your starting message in ClaudeCode. Include:

  • The full .quest/meta.yaml
  • The goals.md
  • Instructions to reason step-by-step and log in state.yaml
You are acting as a Promptable Sage agent. Begin with `.quest/goals.md`. You will work for 1–2 hours, updating state.yaml with your progress.

2. Manual Memory Injection​

Simulate agent memory by pasting:

  • Past state.yaml entries
  • Notes from docs/notes.md
  • Skill Set examples

This approximates retrieval-augmented generation until full memory pipelines are live.

3. Logging and Self-Reflection​

Ask ClaudeCode to:

  • Write reasoning steps in docs/notes.md
  • Output CWL to the CWL/ folder
  • Write tasks/report.md at the end summarizing its process

Use this to train the future Sage agent with real examples.

4. Simulate Runtime Constraints​

Include this context:

agent_role: "workflow engineer"
prompt_style: "cautious + test-driven"
time_budget_minutes: 120

Ask ClaudeCode to track its steps and checkpoint every 15–30 minutes.

🔄 Reusing Claude Work for Sage​

Once Sage is available:

  • Use ClaudeCode quest completions as training data
  • Replay prompt → output pairs
  • Compare behavioral drift across models

You’re building a synthetic memory base for Sage by treating Claude as a generative stand-in.

🔐 Best Practices​

  • Flag which quests were done via ClaudeCode in meta.yaml
  • Use notes.md to capture Claude-specific behaviors
  • Set a daily quota: e.g., 1 private + 1 public quest per day via ClaudeCode

✅ Summary​

ClaudeCode can act as a free, interactive stand-in for Sage with:

  • Prompt-based simulation of agent memory
  • Manual chaining and state updates
  • Test-driven CWL generation

This strategy supports bootstrapping the Promptable agentic layer with zero API cost while building valuable training examples and reuse patterns.