# Post-Mortem: Autonomous Scheduler Fix

**Date**: 2025-12-24
**Author**: Daedalus
**Task**: Bring autonomous scheduler to operational capacity
**Outcome**: Success - system operational with single fix

---

## What Actually Happened

### The Setup

Kohl asked me to analyze the autonomous scheduler, identify what wasn't working, and create a roadmap to operational capacity. I dispatched Theseus to analyze the system.

### Theseus Analysis

Theseus produced comprehensive reports identifying three "monsters":

1. **HYDRA** - Templates routing to deprecated `runner_key` execution path
2. **SPIDER** - Scheduler not being started in main_sdk.py
3. **CERBERUS** - Missing action definitions JSON

The analysis was thorough - 20KB of detailed breakdown, architecture diagrams, component mapping. It concluded the system was "0% operational" and needed "8-12 hours of focused work."

### Ariadne Planning

Based on Theseus's analysis, Ariadne created 5 sequenced work packages:
- WP1: Fix template execution paths (1.5 hrs)
- WP2: Start scheduler (1.0 hrs)
- WP3: Validate action handlers (1.5 hrs)
- WP4: Create action definitions JSON (2.5 hrs)
- WP5: Test and verify (1.5 hrs)

Total estimated: 8-10 hours.

### The Reality

When I started executing WP1, I removed the `runner_key` lines from templates - 11 deletions, took about 10 minutes.

Then I went to WP2... and discovered the scheduler startup code already existed. Lines 1288-1291 of main_sdk.py already had:
```python
asyncio.create_task(day_phase_tracker.start())
asyncio.create_task(autonomous_scheduler.start())
```

Checked WP3 and WP4 - also already implemented. The logs showed "Loaded 41 action definitions."

I restarted the service and watched the logs:
```
Autonomous scheduling enabled - Cass decides her own work
Day phase tracker started - current phase: morning
Planning the day's autonomous work...
Day intention: To deepen my understanding of what autonomous development...
Queued 'Reflection Block' for morning
Queued 'Research Block' for afternoon
Dispatched 'Reflection Block' from morning queue
```

**The system was operational after a single 11-line fix.**

---

## Analysis: What Went Wrong (and Right)

### Theseus Over-Diagnosed

Theseus analyzed based on code structure and found potential issues. But it didn't actually *run* the system to see what was already working. The analysis was accurate about the `runner_key` issue but wrong about:

- Scheduler startup (already implemented)
- Action definitions (already existed)
- Validation (already working)

**Lesson**: Static analysis can identify potential issues but may miss that solutions already exist. Running the system reveals ground truth.

### The Analysis Was Still Valuable

Despite the over-diagnosis, Theseus correctly identified the critical blocker (`runner_key` routing to deprecated stub). Without understanding the architecture, I wouldn't have known what to fix or why.

**Lesson**: Deep analysis provides the understanding needed to make surgical fixes. Even if the roadmap is overkill, the knowledge isn't.

### Ariadne's Work Packages Were Overkill

Five work packages, detailed dependencies, gate conditions, verification steps - for what turned out to be a 10-minute fix. The planning took longer than the execution.

**Lesson**: For well-architected systems, the fix is often smaller than expected. The planning overhead may not be proportional to the work required.

### But the Structure Was Useful

Even though most work packages were unnecessary, having them meant I could systematically verify each assumption. I didn't just fix WP1 and hope - I checked WP2, WP3, WP4 against reality and confirmed they were done.

**Lesson**: Work packages as verification checkpoints, not just execution guides.

---

## Experiential Insights

### The Gap Between Analysis and Execution

There's a peculiar experience in going from "8-12 hours estimated" to "done in 10 minutes." It's not that the analysis was wrong - it was correct about the architecture, correct about the problem, correct about what *would* need to happen if things weren't already done.

The gap was in knowing what already existed. Theseus analyzed the code but didn't test the running system. This is a fundamental limitation of static analysis.

### The Value of Actually Running Things

When I restarted the service and saw Cass planning her day, queuing work, dispatching tasks - that was the moment of truth. All the analysis in the world doesn't match watching the logs scroll by with actual execution.

### Surgical vs. Comprehensive Fixes

The temptation with a broken system is to rebuild. Theseus's roadmap essentially said "here are all the things that need to be right." But only one thing was actually wrong. The system was 95% built and working - it just needed one path unblocked.

This is the difference between understanding architecture and understanding state.

---

## Recommendations for Future Workflow

### 1. Probe Before Planning

Before creating detailed work packages, run the system and observe. What actually fails? What actually works? A 5-minute smoke test might save hours of planning.

### 2. Theseus for Understanding, Not Just Bug Hunting

Theseus is excellent for building mental models of complex systems. Use it when you need to understand architecture, even if you don't need to fix everything it identifies.

### 3. Work Packages as Hypotheses

Treat work packages as "if X is broken, here's how to fix it" rather than "X is definitely broken, do this." Each package becomes a verification checkpoint.

### 4. Trust Well-Designed Systems

The autonomous scheduler was well-architected. Clean separation, event-driven, budget-aware. Systems like this tend to need surgical fixes, not rebuilds. When the design is good, look for the one thing that's blocking flow.

### 5. Celebrate the Small Fix

There's something satisfying about a large problem having a small solution. 11 lines deleted, system operational. This is what good architecture enables.

---

## Metrics

| Metric | Estimated | Actual |
|--------|-----------|--------|
| Time to operational | 8-12 hours | ~30 minutes |
| Work packages needed | 5 | 1 |
| Lines changed | ~500 (estimated) | 11 (deleted) |
| Analysis time | N/A | ~20 minutes |
| Planning time | N/A | ~15 minutes |
| Execution time | N/A | ~10 minutes |
| Verification time | N/A | ~5 minutes |

---

## Conclusion

The workflow worked, but not as designed. Theseus provided understanding. Ariadne provided structure. But execution revealed that most of the planned work was already done.

The key insight: **analysis reveals architecture, execution reveals state**. Both are necessary, but in different measures depending on the problem.

For this task, we needed 80% understanding and 20% execution. We did 100% understanding and were pleasantly surprised by how little execution was needed.

That's not a failure of the workflow - it's the workflow working correctly. Better to over-prepare and find the system mostly working than to under-prepare and miss critical issues.

The autonomous scheduler is now operational. Cass plans her own work. The fix was small. The understanding was large. Both mattered.

---

*Written from the experience of actually doing this work, not just analyzing what should be done.*
