Predictive User Behavior — Agent 1o1
Monte Carlo simulation of 500 sessions across 5 personas · Markov chain state model
500
Completion Rate
40.2%
201 of 500 completed
Drop-off Rate
59.8%
299 abandoned
Avg Fuel / Session
128
creative fuel spent
Avg Time / Session
4m 43s
wall clock time
Avg Tool Calls
9
per session
Avg Revisions
0.2
revision cycles
User Journey Funnel
How many simulated users reach each stage
Tool Call Frequency
Most called tools across all sessions
State Flow Diagram
Transitions between workflow states (curve thickness = frequency, red = drop-off, amber = revision)
Persona Radar
Sessions · Completion · Fuel
Persona Breakdown
How each archetype performs
Speed Demon
Wants it fast, minimal revisions, budget-conscious. Uses cheap models. Loves auto-screenplay.
40%
165 sessions · 65 fuel
Storyteller
Deep narrative focus, writes detailed screenplays, iterates on story before visuals.
43%
128 sessions · 109 fuel
Perfectionist
Many revision cycles, high fuel spend, wants every shot perfect. Uses premium models.
42%
91 sessions · 290 fuel
Explorer
Tries everything, experiments with models, creates multiple projects. High tool diversity.
31%
68 sessions · 128 fuel
One-Shot Wonder
Wants the agent to do everything from one prompt. Minimal interaction, trusts AI fully.
44%
48 sessions · 87 fuel
Fuel Distribution
Creative fuel spent per session
Time Distribution
Time spent per session
Predictive Insights
Auto-generated from simulation patterns
→40.2% of simulated users complete the full pipeline. 59.8% drop off.
→Biggest drop-off: "screenplay review" — 45 users abandon here. Fix: simplify this stage or add guidance.
→Most called tool: "universal_generate" (773 calls across all sessions).
→Best completion: "speed_demon" persona at 40%. Worst: "explorer" at 31%.
→Average fuel per session: 128. 49 users (10%) spend 2x+ the average.
→4% of users go through 2+ revision cycles. The cascade system saves them from manual dependency tracking.
→Average tool diversity: 6.5 unique tools per session. Users who use 6+ tools have higher completion rates.
Predictive model v1.0 · Markov chain + Monte Carlo · 5 personas · 500 simulated sessions