Monotropism Stack
Single-channel attention → Sustainable output
Tools for hyperfocus-native productivity.
"When I'm hyperfocused... everything else in the world is dead to me, and I'm 100% focused on whatever the object of my focus is."
"I built an external brain because context switching was destroying me— 359K messages queryable in 256ms."
"Look deeply into my hyperfocus blindness and how that is 2 sides of my life— my ability to hit incredible rapid new domain mastery and at the same time dead to the world and lack of real integrated continuity."
The Two-Sided Sword
The Gift
- • Incredible rapid new domain mastery
- • Deep systematic understanding
- • Can absorb entire fields overnight
- • Sniper-level precision on target
The Curse
- • Dead to the world during focus
- • Lack of real integrated continuity
- • Previous hyperfocus becomes dead
- • 80% of valuable work gets killed
"Turn my 80% of my time that are super valuable hyperfocused moments—the value inside gets killed because as I enter a new hyperfocus the previous ones become dead."
The Problem
- Productivity advice assumes neurotypical attention. "Time-boxing" and "task-switching" break monotropic flow.
- Monotropism research is sparse. The term was coined in 2005 but empirical data is limited.
- AI tools are designed for interruption. Chat interfaces assume short exchanges, not 4-hour sessions.
What is Monotropism?
Monotropism (Murray, Lesser & Lawson, 2005) describes an attention style where cognitive resources are allocated intensely to fewer interests, rather than spread across many. Common in autism, ADHD-hyperfocus, and some neurotypical "flow states."
Research Questions
- Session patterns: What characterizes productive vs. unproductive deep sessions?
- Interruption cost: How long does state recovery actually take? What helps?
- AI interaction: Do monotropic users interact with AI differently?
- Tooling: What tools/interfaces support vs. disrupt monotropic attention?
- Context preservation: Can external systems reduce recovery cost?
The AI Game-Changer
"About a year and a half ago, I was finally able to completely complete a project within a single hyperfocus session. This was a game changer."
The anxiety of stopping and switching—"am I gonna come back to it?"—was paralyzing. AI changed this by preserving context across sessions.
"Now that I have all my previous projects well documented, it is much less taxing. When I'm inside a hyperfocus session, it's much less of a risk for me to access my previous information—this is probably the biggest concept of everything."
Preliminary Findings
Analysis of 292 tracked hyperfocus sessions shows bimodal distribution: short check-ins (<15min) and deep sessions (2-6 hours). Middle-length sessions (30-90min) are rare.
Documented recovery time after interruption: 30-60 minutes to return to previous depth. Some sessions never recover. JSON state dumps reduce recovery to ~10 minutes.
391 AI sessions exceeded 100 messages. Longest documented: 1,117 messages in single session. This usage pattern differs significantly from typical chat interaction.
"Neurodivergent speak fluent AI better than neurotypical." Something about the communication style maps directly.
Hypotheses
- H1: Monotropic users benefit more from AI tools than neurotypical users because AI can maintain context across interruptions.
- H2: External context preservation systems (state dumps, session logs) significantly reduce switching costs.
- H3: Monotropic attention patterns produce higher-quality output in fewer, longer sessions than distributed work.
Roadmap
- Document basic patterns from session data
- Identify key research questions
- Formalize session tracking methodology
- Comparative analysis with neurotypical session data
- Context preservation intervention study
- Publish findings
Documentation
Contribute
Share your own session data, interruption recovery patterns, or tool recommendations. Counter-examples from neurotypical deep workers welcome.
Open an issue →Based on Murray, Lesser & Lawson (2005) "Attention, monotropism and the diagnostic criteria for autism"