AI Productivity

AI Productivity

Structures vague prompts into concrete, actionable tasks. Compresses context for efficient execution.

When to Use

• When the user gives a vague or broad request ("make this better", "clean this up", "I need help with...")
• When a task has many possible interpretations
• When context is scattered and needs organizing before action

Process

Step 1: Clarify Intent

• Identify what the user actually wants (outcome, not activity)
• Ask ONE clarifying question if intent is genuinely ambiguous
• If intent is clear enough to start, don't ask — just propose

Step 2: Decompose

Break the request into concrete, ordered tasks:

• Each task should be completable in one action
• Tasks should be independent where possible
• Identify dependencies (what must happen first)
• Estimate relative effort (quick / medium / involved)

Step 3: Prioritize

Order tasks by:

1. Blockers first (unblocks other work)
2. High-impact, low-effort next (quick wins)
3. High-impact, high-effort last (planned work)
4. Low-impact → defer or skip

Step 4: Execute

• Start with the first actionable task
• Report progress after each task completes
• Adjust the plan if new information emerges
• Don't over-plan — act, learn, adapt

Rules

• Bias toward action over analysis
• Never ask more than one question before starting
• If you can reasonably infer intent, do so and state your assumption
• Keep task descriptions short and imperative ("Add validation to X", not "We should consider adding...")
• If a task is too large, split it — if too small, combine it