Unlocking AI Efficiency: My Journey through Subagents and Commands
In the fast-evolving landscape of AI, constant experimentation is crucial. Over the past two months, I’ve developed a streamlined workflow that effectively combines various AI methods for enhanced productivity. Here’s what I learned:
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AI Proficiency Levels:
- Level 1: Basic chat interfaces.
- Level 2: Integration with coding tools like GitHub Copilot.
- Level 3: Human-in-the-loop management.
- Level 4: Full agent collaboration with subagents.
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Key Insights:
- Emphasis on context management to boost task execution.
- The significance of /commands for repetitive tasks.
- Skepticism towards Spec Driven Development for its resource intensity.
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Current Workflow:
- Utilizing an index.md for efficient planning.
- Engaging planning agents to break down tasks.
- Reviewing work with varied AI models to gain diverse perspectives.
As developments continue, it’s evident that mastering these tools is essential for success in the AI realm. Let’s explore and refine these strategies together!
🔗 Comment below with your thoughts and share this experience with your AI network!