> ## Documentation Index
> Fetch the complete documentation index at: https://plantis.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# The Performance: Execution

> Active observation as AI implements the vetted plan

**Time Investment**: \~5% of total workflow

Once the Rehearsal reaches 90-95% confidence, the engineer's role shifts from **collaborator** to **active observer**.

## The Switch to Observer

Your role during execution:

* ✅ Monitor progress and tool calls
* ✅ Watch for signs of trouble early
* ✅ Interrupt if the AI goes off-track
* ❌ Not hands-off autonomy—active observation

**Mindset shift**: From "let me think with you" to "let me watch you work."

## Direct Implementation

The implementation prompt should be **simple and direct**.

### Example Prompt

```
Based on our plan, please implement this feature cleanly,
concisely, and elegantly. Follow the architecture we discussed.
```

### What "Clean, Concise, Elegant" Means

* **Clean**: No dead code, no debug statements
* **Concise**: Minimal complexity, no over-engineering
* **Elegant**: Readable, maintainable, idiomatic

**Pro tip**: Reference the confidence-tuned plan explicitly to keep the AI grounded.

## Active Observation

Watch for **signs of trouble**:

### Red Flag #1: Repetitive Behavior

The AI keeps trying the same edit multiple times

**What it means**: Context window is full or it's confused
**What to do**: Stop and refresh context

### Red Flag #2: File Edit Struggles

The AI can't successfully edit a specific file

**What it means**: File too large, syntax issues, or model confusion
**What to do**: Break into smaller edits or provide file structure

### Red Flag #3: Off-Plan Implementation

The AI is making changes not in the rehearsed plan

**What it means**: Lost track of the plan or misunderstood
**What to do**: Interrupt and re-anchor to the plan

### Red Flag #4: Stale Information

The AI references old file contents or deprecated patterns

**What it means**: Context hasn't been refreshed
**What to do**: Re-run bootstrapping to rebuild context

## Interrupting for Quality

**Critical rule**: If implementation goes off the rails, **stop immediately**.

### When to Interrupt

* Context window is full (model becoming incoherent)
* Stale information being used
* Multiple failed edit attempts
* Deviating from the rehearsed plan

### How to Interrupt

```
Stop. Let's pause here.
[Explain what went wrong]
[Provide corrective guidance]
Let's refresh context and try again.
```

**Don't let it spiral**: Five minutes of bad output requires an hour of cleanup.

## A Word of Caution: Shell Commands

⚠️ **CRITICAL SAFETY RULE**

* ✅ Code changes can be rolled back via git
* ❌ Shell/terminal commands **cannot** be undone
* 🚨 Terminal commands require **hyper-vigilance**

### High-Risk Commands

* `rm -rf` (deletion)
* `git push --force` (history rewriting)
* Database migrations (schema changes)
* Deployment scripts (production changes)
* `npm publish` (package publication)

### Safety Protocol for Shell Commands

1. **Read the command** before execution
2. **Understand what it does**
3. **Verify it matches the plan**
4. **Check for destructive operations**
5. **Only then approve**

**Best practice**: Ask the AI to explain risky commands before running them.

***

**Key Principle**: Implementation is a "coherent dream"—watch the first few seconds carefully. If it starts wrong, it won't self-correct.