Future Brent – A Mental Model: A 1% Nudge Toward a Kinder Tomorrow

On Not Quite Random, we often wander through the intersections of the personal and the technical, and today is no different. Let me share with you a little mental model I like to call “Future Brent.” It’s a simple yet powerful approach: every time I have a sliver of free time, I ask, “What can I do right now that will make things a little easier for future Brent?”

ChatGPT Image Dec 9 2025 at 10 23 45 AM

It’s built on three pillars. First, optimizing for optionality. That means creating flexibility and space so that future Brent has more choices and less friction. Second, it’s about that 1% improvement each day—like the old adage says, just nudging life forward a tiny bit at a time. And finally, it’s about kindness and compassion for your future self.

Just the other day, I spent 20 minutes clearing out an overcrowded closet. That little investment meant that future mornings were smoother and simpler—future Brent didn’t have to wrestle with a mountain of clothes. And right now, as I chat with you, I’m out on a walk—because a little fresh air is a gift to future Brent’s health and mood.

In the end, this mental model is about blending a bit of personal reflection with a dash of practical action. It’s a reminder that the smallest acts of kindness to ourselves today can create a more flexible, happier, and more empowered tomorrow. So here’s to all of us finding those little 1% opportunities and giving future us a reason to smile.

Hybrid Work, Cognitive Fragmentation, and the Rise of Flow‑Design

Context: Why hybrid work isn’t just a convenience

Hybrid work isn’t a fringe experiment anymore — it’s quickly becoming the baseline. A 2024–25 survey in the U.S. shows that 52% of employees whose jobs can be remote work in a hybrid mode, and another 27% are fully remote.

Other recent studies reinforce the upsides: hybrid arrangements often deliver similar productivity and career‑advancement outcomes as fully on-site roles, while improving employee retention and satisfaction.

Redheadcoffee

In short: hybrid work is now normal — and that normalization brings new challenges that go beyond “working from home vs. office.”

The Hidden Cost: Cognitive Fragmentation as an Engineering Problem

When organizations shift to hybrid work, they often celebrate autonomy, flexibility, and freedom from commutes. What gets less attention is how hybrid systems — built around multiple apps, asynchronous communication, decentralized teams, shifting time zones — cause constant context switching.

  • Each time we jump from an email thread to a project board, then to a chat, then to a doc — that’s not just a change in window or tab. It is a mental task switch.

  • Such switches can consume as much as 40% of productive time.

  • Beyond lost time, there’s a deeper toll: the phenomenon of “attention residue.” That’s when remnants of the previous task linger in your mind, degrading focus and decreasing performance on the current task — especially harmful for cognitively demanding or creative work.

If we think about hybrid work as an engineered system, context switching is a kind of “friction” — not in code or infrastructure, but in human attention. And like any engineering problem, friction can — and should — be minimized.

Second‑Order Effects: Why Cognitive Fragmentation Matters

Cognitive fragmentation doesn’t just reduce throughput or add stress. Its effects ripple deeper, with impacts on:

  • Quality of output: When attention is fragmented, even small tasks suffer. Mistakes creep in, thoughtfulness erodes, and deep work becomes rare.

  • Long-term mental fatigue and burnout: Constant switching wears down cognitive reserves. It’s no longer just “too much work,” but “too many contexts” demanding attention.

  • Team performance and morale: At the organizational level, teams that minimize context switching report stronger morale, better retention, and fewer “after‑hours” overloads.

  • Loss of strategic thinking and flow states: When individuals rarely stay in one mental context long enough, opportunities for deep reflection, creative thinking, or coherent planning erode.

In short, hybrid work doesn’t just shift “where” work happens — it fundamentally alters how work happens.

Why Current Solutions Fall Short

There are many popular “help me focus” strategies:

  • The classic — Pomodoro Technique / “deep work” blocks / browser blockers.

  • Calendar-based time blocking to carve out uninterrupted hours.

  • Productivity suites: project/task trackers like Asana, Notion, Linear and other collaboration tools — designed to organize work across contexts.

And yet — these often treat only the symptoms, not the underlying architecture of distraction. What’s missing is a system‑level guidance on:

  • Mapping cognitive load across workflow architecture (not just “my calendar,” but “how many systems/platforms/contexts am I juggling?”).

  • Designing environments (digital and physical) that reduce cross‑system interference instead of piling more tools.

  • Considering second‑ and third‑order consequences — not just “did I get tasks done?” but “did I preserve attention capacity, quality, and mental energy?”

In other words: we lack a rationalist, engineered approach to hybrid‑work life hacking.

Toward Flow‑Preserving Systems: A Pareto Model of Attention

If we treat attention as a finite resource — and work systems as pipelines — then hybrid work demands more than discipline: it demands architecture. Here’s a framework rooted in the 80/20 (Pareto) principle and “flow‑preserving design.”

1. Identify your “attention vector” — where does your attention go?

List the systems, tools, communication modes, and contexts you interact with daily. How many platforms? How many distinct contexts (e.g., team A chat, team B ticket board, email, docs, meetings)? Rank them by frequency and friction.

2. Cull ruthlessly. Apply the 80/20 test to contexts:

Which 20% of contexts produce 80% of meaningful value? Those deserve high-bandwidth attention and uninterrupted time. Everything else — low‑value, context‑switch‑heavy noise — may be candidates for elimination, batching, or delegation.

3. Build “flow windows,” not just “focus zones.”

Rather than hoping “deep work days” will save you, build structural constraints: e.g., merge related contexts (use fewer overlapping tools), group similar tasks, minimize simultaneous cross-team demands, push meetings into consolidated blocks, silence cross‑context notifications when in flow windows.

4. Design both digital and physical environments for flow.

Digital: reduce number of apps, unify communications, use integrated platforms intelligently.
Physical: fight “always on” posture — treat work zones as environments with their own constraints.

5. Monitor second‑order effects.

Track not just output quantity, but quality, mental fatigue, clarity, creativity, and subjective well‑being. Use “collaboration analytics” if available (e.g., data on meeting load, communication frequency) to understand when fragmentation creeps up.

Conclusion: Hybrid Work Needs More Than Tools — It Needs Architecture

Hybrid work is now the baseline for millions of professionals. But with that shift comes a subtle and pervasive risk: cognitive fragmentation. Like a system under high load without proper caching or resource pooling, our brains start thrashing — switching, reloading, groggy, inefficient.

We can fight that not (only) through willpower, but through design. Treat your mental bandwidth as a resource. Treat hybrid work as an engineered system. Apply Pareto-style pruning. Consolidate contexts. Build flow‑preserving constraints. Track not just tasks — but cognitive load, quality, and fatigue.

If done intentionally, you might discover that hybrid work doesn’t just offer flexibility — it offers the potential for deeper focus, higher quality, and less mental burnout.


References

  1. Great Place to Work, Remote Work Productivity Study: greatplacetowork.com

  2. Stanford University Research on Hybrid Work: news.stanford.edu

  3. Reclaim.ai on Context Switching: reclaim.ai

  4. Conclude.io on Context Switching and Productivity Loss: conclude.io

  5. Software.com DevOps Guide: software.com

  6. BasicOps on Context Switching Impact: basicops.com

  7. RSIS International Study on Collaboration Analytics: rsisinternational.org


Support My Work

If this post resonated with you, and you’d like to support further writing like this — analyses of digital work, cognition, and designing for flow — consider buying me a coffee: Buy Me a Coffee ☕

 

* AI tools were used as a research assistant for this content, but human moderation and writing are also included. The included images are AI-generated.

Build Systems for Your Worst Days, Not Your Best

I’ve had those days. You know the ones: back-to-back meetings, your inbox growing like a fungal bloom in the dark, and just a single, precious hour to get anything meaningful done. Those are the days when your tools, workflows, and systems either rise to meet the challenge—or collapse like a Jenga tower on a fault line.

And that’s exactly why I build systems for my worst days, not my best ones.

Thinking

When You’re Running on Fumes, Systems Matter Most

It’s easy to fall into the trap of designing productivity systems around our ideal selves—the focused, energized version of us who starts the day with a triple espresso and a clear mind. But that version shows up maybe one or two days a week. The other days? We’re juggling distractions, fighting fatigue, and getting peppered with unexpected tasks.

Those are the days that test whether your systems are real or just aspirational scaffolding.

My Systems for the Storm

To survive—and sometimes even thrive—on my worst days, I rely on a suite of systems I’ve built and refined over time:

  • Custom planners for project, task, and resource tracking. These keep my attention on the highest-leverage work, even when my mind wants to wander.

  • Pre-created GPTs and automations that handle repetitive tasks, from research to analysis. On a rough day, this means things still get done while I conserve cognitive bandwidth.

  • Browser scripts that speed up form fills, document parsing, and other friction-heavy tasks.

  • The EDSAM mental model helps me triage and prioritize quickly without falling into reactive mode. (EDSAM = Eliminate, Delegate, Simplify, Automate, Maintain)

  • A weekly review process that previews the chaos ahead and lets me make strategic decisions before I’m in the thick of it.

These aren’t just optimizations—they’re insulation against chaos.

The Real ROI: More Than Just Productivity

The return on these systems goes well beyond output. It’s about stress management, reduced rumination, and the ability to make clear-headed decisions when everything else is fuzzy. I walk into tough weeks with more confidence, not because I expect them to be easy—but because I know my systems will hold.

And here’s something unexpected: these systems have also amplified my impact as a mentor. By teaching others how I think about task design, tooling, and automation, I’m not just giving them tips—I’m offering frameworks they can build around their own worst days.

Shifting the Culture of “Reactive Work”

When I work with teams, I often see systems built for the ideal: smooth days, few interruptions, time to think. But real-world conditions rarely comply. That’s why I try to model and teach the philosophy of resilient systems—ones that don’t break when someone’s sick, a deadline moves up, or a crisis hits.

Through mentoring and content, I help others see that systems aren’t about rigidity—they’re about readiness.

The Guiding Principle

Here’s the rule I live by:

“The systems have to make bad days better, and the worst days minimally productive—otherwise, they need to be optimized or replaced.”

That sentence lives in the back of my mind as I build, test, and adapt everything from automations to mental models. Because I don’t just want to do great work on my best days—I want to still do meaningful work on my worst ones.

And over time, those dividends compound in ways you can’t measure in a daily planner.

Support My Work

Support the creation of high-impact content and research. Sponsorship opportunities are available for specific topics, whitepapers, tools, or advisory insights. Learn more or contribute here: Buy Me A Coffee

 

* AI tools were used as a research assistant for this content, but human moderation and writing are also included. The included images are AI-generated.

The Dopamine Management Framework: A Rationalist’s Guide to Balancing Reward, Focus, and Drive

Modern knowledge‑workers and rationalists live in a gilded cage of stimulation. Our smartphones ping. Social apps lure. Productivity tools promise efficiency but bring micro‑interruptions. It all feels like progress — until it doesn’t. Until motivation runs dry. Attention flattens. Dissatisfaction sets in.

Yes, you already know that the neurotransmitter Dopamine is often called the brain’s “reward” signal. But what if you treated your dopaminergic system like budget, or like time—with strategy, measurement, and purpose? Not to eliminate pleasure (this isn’t asceticism) — but to reclaim control over what motivates you, and how you pursue meaningful goals.

MentalModels

In this post I’ll introduce a practical four‑step framework: Track → Taper → Tune → Train. One by one we’ll unpack how these phases map to your environment, habits, and long‑term motivation architecture.


Why This Matters

Technology has turned dopamine hijacking into default mode.
When you’re not just distracted — when your reward system is distorted — you may see:

  • shorter attention spans

  • effort‑aversion to sustained work

  • a shift toward quick‑hit gratification instead of the rich, long‑term satisfaction of building something meaningful
    And for rationalists — who prize clarity, deep work, coherent motivation — this is more than nuisance. It becomes structural.

In neuroscience terms, dopamine isn’t simply about pleasure. It plays a key role in motivating actions and associating them with value. PNAS+2PMC+2 And when we flood that system with high‑intensity, low‑effort reward signals, we degrade our sensitivity to more subtle, delayed rewards. Penn LPS Online+1

So: the problem isn’t dopamine. The problem is unmanaged dopamine.


The Framework: Track → Taper → Tune → Train

1. Track – Map Your Dopamine Environment

Key Idea: You can’t manage what you don’t measure.

What to do:

  • Identify your “dopamine hotspots”: e.g., social media scrolls, email pings, news bingeing, caffeine hits, instant feedback tools.

  • Categorize each by intensity (for example: doom‑scrolling social feed = high; reading a print journal = medium; writing code without interruption = low but delayed).

  • Track “dopamine crashes” — times when your motivation, energy or focus drops sharply: what preceded them? A 10‑minute feed of pointless info? A high‑caffeine spike?

  • Use a “dopamine log” for ~5 days. Each time you get a strong hit or crash, note: time, source, duration, effect on your focus/mood.

Why this works:
Neuroscience shows dopamine’s role in signalling future reward and motivating effort. PMC+1 If your baseline is chaotic — with bursts and dips coming from external stimuli — your system becomes reactive instead of intentional.

Pro tip: Use a very simple spreadsheet or notebook. Column for “stimulus,” “duration,” “felt effect,” “focus after”. Try to track before and after (e.g., “30 min Instagram → motivation drop from 8→3”).


2. Taper – Reduce Baseline Dopamine Stimuli

Key Idea: A high baseline of stimulation dulls your sensitivity to more meaningful rewards — and makes focused work feel intolerable.

Actions:

  • Pick one high‑stimulation habit to taper (don’t go full monk‑mode yet).

    • Example: replace Instagram scrolling with reading a curated newsletter.

    • Replace energy drinks with green tea in the afternoon.

  • Introduce “dopamine fasting” blocks: e.g., one hour per day with no screens, no background noise, no caffeine.

  • Avoid the pitfall: icy abstinence. The goal is balance, not deprivation.

Why this matters:
The brain’s reward pathways are designed for survival‑based stimuli, not for an endless stream of instant thrills. Artificially high dopaminergic surges (via apps, notifications, etc.) produce adaptation and tolerance. The system flattens. Penn LPS Online+1 When your brain expects high‑intensity reward, the normal things (writing, thinking, reflecting) feel dull.

Implementation tip: Schedule your tapering. For example: disable social apps for 30 minutes after waking, replace that slot with reading or journaling. After two weeks, increase to 45 minutes.


3. Tune – Align Dopamine with Your Goals

Key Idea: You can train your brain to associate dopamine with meaningful effort, not just passive inputs.

Actions:

  • Use temptation bundling: attach a small reward to focused work (e.g., write for 30 minutes and then enjoy an espresso or a favorite podcast).

  • Redefine “wins”: instead of just “I shipped feature X” (outcome), track process‑goals: “I wrote 300 words”, “I did a 50‑minute uninterrupted session”.

  • Break larger tasks into small units you can complete (write 100 words instead of “write article”). Each completion triggers a minor dopamine hit.

  • Create a “dopamine calendar”: log your wins (process wins), and visually see consistency over intensity.

Why this works:
Dopamine is deeply tied into incentive salience — the “wanting” of a reward — and prediction errors in reward systems. Wikipedia+1 If you signal to the brain that the processes you value are themselves rewarding, you shift your internal reward map away from only “instant high” to “meaningful engagement”.

Tip: Use a simple app or notebook: every time you finish a mini‑task, mark a win. Then allow yourself the small reward. Over time, you’ll build momentum.


4. Train – Build a Resilient Motivation System

Key Idea: Sustained dopamine stability requires training for delayed rewards, boredom tolerance — the opposite of constant high‑arousal stimulation.

Actions:

  • Practice boredom training: spend 10 minutes a day doing nothing (no phone, no music, no output). Just sit, think, breathe.

  • Introduce deep‑focus blocks: schedule 25‑90 minute sessions where you do high‑value work with minimal stimulation (no notifications, no tab switching).

  • Use dopamine‑contrast days: alternate between one “deep focus” day and one “leisure‑heavy” day to re‑sensitise your reward system.

  • Mindset shift: view boredom not as failure, but as a muscle you’re building.

Why this matters:
Our neurobiology thrives on novelty, yet adapts quickly. Without training in low‑arousal states and delayed gratification, your motivation becomes brittle. The brain shifts toward short‑term cues. Neuroscience has shown that dopamine dysregulation often involves reduced ability to tolerate low stimulation or delayed reward. Penn LPS Online

Implementation tip: Start small. Two times a week schedule a 20‑minute deep‑focus block. Also schedule two separate 10‑minute “nothing” blocks. Build from there.


Real‑Life Example: Dopamine Rewiring in Practice

Here’s a profile: A freelance developer found that by mid‑afternoon, her energy and motivation always crashed. She logged her day and discovered the pattern: morning caffeine + Twitter + Discord chat = dopamine spike early. Then the crash happened by 2 PM.

She applied the framework:

  • Track: She logged each social/communication/caffeine event, noted effects on focus.

  • Taper: Reduced caffeine, postponed social scrolling to after 5 PM. Introduced a 15‑minute walk + journaling break instead of Twitter at lunch.

  • Tune: She broke her workday into 30‑minute coding sprints, each followed by a small reward (a glass of water + 2‑minute stretch). She logged each sprint as a “win”.

  • Train: Added a daily 20‑minute “nothing” block (no tech) and scheduled two deep focus blocks of 60 minutes each.

Results after ~10 days: Her uninterrupted focus blocks grew by ~45 minutes; she described herself as “more driven but less scattered.”


Metrics to Track

To see if this is working for you, here are metrics you might adopt:

  • Focus duration without switching: how long can you work before you switch tasks or get distracted?

  • Number of process‑wins logged per day: the small completed units.

  • Perceived energy levels (AM vs. PM): rate from 1–10 each day.

  • Mood ratings before and after key dopamine events: note spikes and crashes.

Track weekly. Look for improvement in focus duration, fewer mid‑day crashes, and a more stable mood curve.


Next Steps

Here’s a roadmap:

  1. Audit your top 5 dopamine sources (what gives you quick hits, what gives you slow/meaningful reward).

  2. Pick one high‑stimulation habit to taper this week.

  3. Set up a simple win‑log for process goals starting today.

  4. Introduce a 5‑minute boredom session each day (just 5 minutes is fine).

  5. At the end of the week, reassess: What improved? What got worse? Adjust.

Remember: dopamine management is iterative. It’s not about perfection or asceticism — it’s about designing your internal reward system so you drive it, instead of being driven by it.


Closing Thought

Managing dopamine isn’t about restriction. It’s about deliberate design. It’s about aligning your reward architecture with your values, your goals, your energy rhythms. It’s about reclaiming autonomy.

When the world’s stimuli are engineered to hijack your motivation, the only honest defense is a framework: one that lets you track what’s actually happening, taper impulsive rewards, tune process‑based wins, and train your system for deep, sustained focus.

If you’re someone who cares about clarity, meaning, and control—this isn’t optional. It’s foundational.

Here’s to managing our dopamine, instead of letting it manage us.

 

 

* AI tools were used as a research assistant for this content, but human moderation and writing are also included. The included images are AI-generated.

The Dopamine Management Framework: A Rationalist’s Guide to Balancing Reward, Focus, and Drive

Modern knowledge‑workers and rationalists live in a gilded cage of stimulation. Our smartphones ping. Social apps lure. Productivity tools promise efficiency but bring micro‑interruptions. It all feels like progress — until it doesn’t. Until motivation runs dry. Attention flattens. Dissatisfaction sets in.

Yes, you already know that the neurotransmitter Dopamine is often called the brain’s “reward” signal. But what if you treated your dopaminergic system like budget, or like time—with strategy, measurement, and purpose? Not to eliminate pleasure (this isn’t asceticism) — but to reclaim control over what motivates you, and how you pursue meaningful goals.

MentalModels

In this post I’ll introduce a practical four‑step framework: Track → Taper → Tune → Train. One by one we’ll unpack how these phases map to your environment, habits, and long‑term motivation architecture.


Why This Matters

Technology has turned dopamine hijacking into default mode.
When you’re not just distracted — when your reward system is distorted — you may see:

  • shorter attention spans

  • effort‑aversion to sustained work

  • a shift toward quick‑hit gratification instead of the rich, long‑term satisfaction of building something meaningful
    And for rationalists — who prize clarity, deep work, coherent motivation — this is more than nuisance. It becomes structural.

In neuroscience terms, dopamine isn’t simply about pleasure. It plays a key role in motivating actions and associating them with value. PNAS+2PMC+2 And when we flood that system with high‑intensity, low‑effort reward signals, we degrade our sensitivity to more subtle, delayed rewards. Penn LPS Online+1

So: the problem isn’t dopamine. The problem is unmanaged dopamine.


The Framework: Track → Taper → Tune → Train

1. Track – Map Your Dopamine Environment

Key Idea: You can’t manage what you don’t measure.

What to do:

  • Identify your “dopamine hotspots”: e.g., social media scrolls, email pings, news bingeing, caffeine hits, instant feedback tools.

  • Categorize each by intensity (for example: doom‑scrolling social feed = high; reading a print journal = medium; writing code without interruption = low but delayed).

  • Track “dopamine crashes” — times when your motivation, energy or focus drops sharply: what preceded them? A 10‑minute feed of pointless info? A high‑caffeine spike?

  • Use a “dopamine log” for ~5 days. Each time you get a strong hit or crash, note: time, source, duration, effect on your focus/mood.

Why this works:
Neuroscience shows dopamine’s role in signalling future reward and motivating effort. PMC+1 If your baseline is chaotic — with bursts and dips coming from external stimuli — your system becomes reactive instead of intentional.

Pro tip: Use a very simple spreadsheet or notebook. Column for “stimulus,” “duration,” “felt effect,” “focus after”. Try to track before and after (e.g., “30 min Instagram → motivation drop from 8→3”).


2. Taper – Reduce Baseline Dopamine Stimuli

Key Idea: A high baseline of stimulation dulls your sensitivity to more meaningful rewards — and makes focused work feel intolerable.

Actions:

  • Pick one high‑stimulation habit to taper (don’t go full monk‑mode yet).

    • Example: replace Instagram scrolling with reading a curated newsletter.

    • Replace energy drinks with green tea in the afternoon.

  • Introduce “dopamine fasting” blocks: e.g., one hour per day with no screens, no background noise, no caffeine.

  • Avoid the pitfall: icy abstinence. The goal is balance, not deprivation.

Why this matters:
The brain’s reward pathways are designed for survival‑based stimuli, not for an endless stream of instant thrills. Artificially high dopaminergic surges (via apps, notifications, etc.) produce adaptation and tolerance. The system flattens. Penn LPS Online+1 When your brain expects high‑intensity reward, the normal things (writing, thinking, reflecting) feel dull.

Implementation tip: Schedule your tapering. For example: disable social apps for 30 minutes after waking, replace that slot with reading or journaling. After two weeks, increase to 45 minutes.


3. Tune – Align Dopamine with Your Goals

Key Idea: You can train your brain to associate dopamine with meaningful effort, not just passive inputs.

Actions:

  • Use temptation bundling: attach a small reward to focused work (e.g., write for 30 minutes and then enjoy an espresso or a favorite podcast).

  • Redefine “wins”: instead of just “I shipped feature X” (outcome), track process‑goals: “I wrote 300 words”, “I did a 50‑minute uninterrupted session”.

  • Break larger tasks into small units you can complete (write 100 words instead of “write article”). Each completion triggers a minor dopamine hit.

  • Create a “dopamine calendar”: log your wins (process wins), and visually see consistency over intensity.

Why this works:
Dopamine is deeply tied into incentive salience — the “wanting” of a reward — and prediction errors in reward systems. Wikipedia+1 If you signal to the brain that the processes you value are themselves rewarding, you shift your internal reward map away from only “instant high” to “meaningful engagement”.

Tip: Use a simple app or notebook: every time you finish a mini‑task, mark a win. Then allow yourself the small reward. Over time, you’ll build momentum.


4. Train – Build a Resilient Motivation System

Key Idea: Sustained dopamine stability requires training for delayed rewards, boredom tolerance — the opposite of constant high‑arousal stimulation.

Actions:

  • Practice boredom training: spend 10 minutes a day doing nothing (no phone, no music, no output). Just sit, think, breathe.

  • Introduce deep‑focus blocks: schedule 25‑90 minute sessions where you do high‑value work with minimal stimulation (no notifications, no tab switching).

  • Use dopamine‑contrast days: alternate between one “deep focus” day and one “leisure‑heavy” day to re‑sensitise your reward system.

  • Mindset shift: view boredom not as failure, but as a muscle you’re building.

Why this matters:
Our neurobiology thrives on novelty, yet adapts quickly. Without training in low‑arousal states and delayed gratification, your motivation becomes brittle. The brain shifts toward short‑term cues. Neuroscience has shown that dopamine dysregulation often involves reduced ability to tolerate low stimulation or delayed reward. Penn LPS Online

Implementation tip: Start small. Two times a week schedule a 20‑minute deep‑focus block. Also schedule two separate 10‑minute “nothing” blocks. Build from there.


Real‑Life Example: Dopamine Rewiring in Practice

Here’s a profile: A freelance developer found that by mid‑afternoon, her energy and motivation always crashed. She logged her day and discovered the pattern: morning caffeine + Twitter + Discord chat = dopamine spike early. Then the crash happened by 2 PM.

She applied the framework:

  • Track: She logged each social/communication/caffeine event, noted effects on focus.

  • Taper: Reduced caffeine, postponed social scrolling to after 5 PM. Introduced a 15‑minute walk + journaling break instead of Twitter at lunch.

  • Tune: She broke her workday into 30‑minute coding sprints, each followed by a small reward (a glass of water + 2‑minute stretch). She logged each sprint as a “win”.

  • Train: Added a daily 20‑minute “nothing” block (no tech) and scheduled two deep focus blocks of 60 minutes each.

Results after ~10 days: Her uninterrupted focus blocks grew by ~45 minutes; she described herself as “more driven but less scattered.”


Metrics to Track

To see if this is working for you, here are metrics you might adopt:

  • Focus duration without switching: how long can you work before you switch tasks or get distracted?

  • Number of process‑wins logged per day: the small completed units.

  • Perceived energy levels (AM vs. PM): rate from 1–10 each day.

  • Mood ratings before and after key dopamine events: note spikes and crashes.

Track weekly. Look for improvement in focus duration, fewer mid‑day crashes, and a more stable mood curve.


Next Steps

Here’s a roadmap:

  1. Audit your top 5 dopamine sources (what gives you quick hits, what gives you slow/meaningful reward).

  2. Pick one high‑stimulation habit to taper this week.

  3. Set up a simple win‑log for process goals starting today.

  4. Introduce a 5‑minute boredom session each day (just 5 minutes is fine).

  5. At the end of the week, reassess: What improved? What got worse? Adjust.

Remember: dopamine management is iterative. It’s not about perfection or asceticism — it’s about designing your internal reward system so you drive it, instead of being driven by it.


Closing Thought

Managing dopamine isn’t about restriction. It’s about deliberate design. It’s about aligning your reward architecture with your values, your goals, your energy rhythms. It’s about reclaiming autonomy.

When the world’s stimuli are engineered to hijack your motivation, the only honest defense is a framework: one that lets you track what’s actually happening, taper impulsive rewards, tune process‑based wins, and train your system for deep, sustained focus.

If you’re someone who cares about clarity, meaning, and control—this isn’t optional. It’s foundational.

Here’s to managing our dopamine, instead of letting it manage us.

 

 

* AI tools were used as a research assistant for this content, but human moderation and writing are also included. The included images are AI-generated.

The Dopamine Management Framework: A Rationalist’s Guide to Balancing Reward, Focus, and Drive

Modern knowledge‑workers and rationalists live in a gilded cage of stimulation. Our smartphones ping. Social apps lure. Productivity tools promise efficiency but bring micro‑interruptions. It all feels like progress — until it doesn’t. Until motivation runs dry. Attention flattens. Dissatisfaction sets in.

Yes, you already know that the neurotransmitter Dopamine is often called the brain’s “reward” signal. But what if you treated your dopaminergic system like budget, or like time—with strategy, measurement, and purpose? Not to eliminate pleasure (this isn’t asceticism) — but to reclaim control over what motivates you, and how you pursue meaningful goals.

MentalModels

In this post I’ll introduce a practical four‑step framework: Track → Taper → Tune → Train. One by one we’ll unpack how these phases map to your environment, habits, and long‑term motivation architecture.


Why This Matters

Technology has turned dopamine hijacking into default mode.
When you’re not just distracted — when your reward system is distorted — you may see:

  • shorter attention spans

  • effort‑aversion to sustained work

  • a shift toward quick‑hit gratification instead of the rich, long‑term satisfaction of building something meaningful
    And for rationalists — who prize clarity, deep work, coherent motivation — this is more than nuisance. It becomes structural.

In neuroscience terms, dopamine isn’t simply about pleasure. It plays a key role in motivating actions and associating them with value. PNAS+2PMC+2 And when we flood that system with high‑intensity, low‑effort reward signals, we degrade our sensitivity to more subtle, delayed rewards. Penn LPS Online+1

So: the problem isn’t dopamine. The problem is unmanaged dopamine.


The Framework: Track → Taper → Tune → Train

1. Track – Map Your Dopamine Environment

Key Idea: You can’t manage what you don’t measure.

What to do:

  • Identify your “dopamine hotspots”: e.g., social media scrolls, email pings, news bingeing, caffeine hits, instant feedback tools.

  • Categorize each by intensity (for example: doom‑scrolling social feed = high; reading a print journal = medium; writing code without interruption = low but delayed).

  • Track “dopamine crashes” — times when your motivation, energy or focus drops sharply: what preceded them? A 10‑minute feed of pointless info? A high‑caffeine spike?

  • Use a “dopamine log” for ~5 days. Each time you get a strong hit or crash, note: time, source, duration, effect on your focus/mood.

Why this works:
Neuroscience shows dopamine’s role in signalling future reward and motivating effort. PMC+1 If your baseline is chaotic — with bursts and dips coming from external stimuli — your system becomes reactive instead of intentional.

Pro tip: Use a very simple spreadsheet or notebook. Column for “stimulus,” “duration,” “felt effect,” “focus after”. Try to track before and after (e.g., “30 min Instagram → motivation drop from 8→3”).


2. Taper – Reduce Baseline Dopamine Stimuli

Key Idea: A high baseline of stimulation dulls your sensitivity to more meaningful rewards — and makes focused work feel intolerable.

Actions:

  • Pick one high‑stimulation habit to taper (don’t go full monk‑mode yet).

    • Example: replace Instagram scrolling with reading a curated newsletter.

    • Replace energy drinks with green tea in the afternoon.

  • Introduce “dopamine fasting” blocks: e.g., one hour per day with no screens, no background noise, no caffeine.

  • Avoid the pitfall: icy abstinence. The goal is balance, not deprivation.

Why this matters:
The brain’s reward pathways are designed for survival‑based stimuli, not for an endless stream of instant thrills. Artificially high dopaminergic surges (via apps, notifications, etc.) produce adaptation and tolerance. The system flattens. Penn LPS Online+1 When your brain expects high‑intensity reward, the normal things (writing, thinking, reflecting) feel dull.

Implementation tip: Schedule your tapering. For example: disable social apps for 30 minutes after waking, replace that slot with reading or journaling. After two weeks, increase to 45 minutes.


3. Tune – Align Dopamine with Your Goals

Key Idea: You can train your brain to associate dopamine with meaningful effort, not just passive inputs.

Actions:

  • Use temptation bundling: attach a small reward to focused work (e.g., write for 30 minutes and then enjoy an espresso or a favorite podcast).

  • Redefine “wins”: instead of just “I shipped feature X” (outcome), track process‑goals: “I wrote 300 words”, “I did a 50‑minute uninterrupted session”.

  • Break larger tasks into small units you can complete (write 100 words instead of “write article”). Each completion triggers a minor dopamine hit.

  • Create a “dopamine calendar”: log your wins (process wins), and visually see consistency over intensity.

Why this works:
Dopamine is deeply tied into incentive salience — the “wanting” of a reward — and prediction errors in reward systems. Wikipedia+1 If you signal to the brain that the processes you value are themselves rewarding, you shift your internal reward map away from only “instant high” to “meaningful engagement”.

Tip: Use a simple app or notebook: every time you finish a mini‑task, mark a win. Then allow yourself the small reward. Over time, you’ll build momentum.


4. Train – Build a Resilient Motivation System

Key Idea: Sustained dopamine stability requires training for delayed rewards, boredom tolerance — the opposite of constant high‑arousal stimulation.

Actions:

  • Practice boredom training: spend 10 minutes a day doing nothing (no phone, no music, no output). Just sit, think, breathe.

  • Introduce deep‑focus blocks: schedule 25‑90 minute sessions where you do high‑value work with minimal stimulation (no notifications, no tab switching).

  • Use dopamine‑contrast days: alternate between one “deep focus” day and one “leisure‑heavy” day to re‑sensitise your reward system.

  • Mindset shift: view boredom not as failure, but as a muscle you’re building.

Why this matters:
Our neurobiology thrives on novelty, yet adapts quickly. Without training in low‑arousal states and delayed gratification, your motivation becomes brittle. The brain shifts toward short‑term cues. Neuroscience has shown that dopamine dysregulation often involves reduced ability to tolerate low stimulation or delayed reward. Penn LPS Online

Implementation tip: Start small. Two times a week schedule a 20‑minute deep‑focus block. Also schedule two separate 10‑minute “nothing” blocks. Build from there.


Real‑Life Example: Dopamine Rewiring in Practice

Here’s a profile: A freelance developer found that by mid‑afternoon, her energy and motivation always crashed. She logged her day and discovered the pattern: morning caffeine + Twitter + Discord chat = dopamine spike early. Then the crash happened by 2 PM.

She applied the framework:

  • Track: She logged each social/communication/caffeine event, noted effects on focus.

  • Taper: Reduced caffeine, postponed social scrolling to after 5 PM. Introduced a 15‑minute walk + journaling break instead of Twitter at lunch.

  • Tune: She broke her workday into 30‑minute coding sprints, each followed by a small reward (a glass of water + 2‑minute stretch). She logged each sprint as a “win”.

  • Train: Added a daily 20‑minute “nothing” block (no tech) and scheduled two deep focus blocks of 60 minutes each.

Results after ~10 days: Her uninterrupted focus blocks grew by ~45 minutes; she described herself as “more driven but less scattered.”


Metrics to Track

To see if this is working for you, here are metrics you might adopt:

  • Focus duration without switching: how long can you work before you switch tasks or get distracted?

  • Number of process‑wins logged per day: the small completed units.

  • Perceived energy levels (AM vs. PM): rate from 1–10 each day.

  • Mood ratings before and after key dopamine events: note spikes and crashes.

Track weekly. Look for improvement in focus duration, fewer mid‑day crashes, and a more stable mood curve.


Next Steps

Here’s a roadmap:

  1. Audit your top 5 dopamine sources (what gives you quick hits, what gives you slow/meaningful reward).

  2. Pick one high‑stimulation habit to taper this week.

  3. Set up a simple win‑log for process goals starting today.

  4. Introduce a 5‑minute boredom session each day (just 5 minutes is fine).

  5. At the end of the week, reassess: What improved? What got worse? Adjust.

Remember: dopamine management is iterative. It’s not about perfection or asceticism — it’s about designing your internal reward system so you drive it, instead of being driven by it.


Closing Thought

Managing dopamine isn’t about restriction. It’s about deliberate design. It’s about aligning your reward architecture with your values, your goals, your energy rhythms. It’s about reclaiming autonomy.

When the world’s stimuli are engineered to hijack your motivation, the only honest defense is a framework: one that lets you track what’s actually happening, taper impulsive rewards, tune process‑based wins, and train your system for deep, sustained focus.

If you’re someone who cares about clarity, meaning, and control—this isn’t optional. It’s foundational.

Here’s to managing our dopamine, instead of letting it manage us.

 

 

* AI tools were used as a research assistant for this content, but human moderation and writing are also included. The included images are AI-generated.

The Mental Models of Crypto Compliance: A Hacker’s Perspective on Regulatory Risk

Let’s discuss one of the most complex and misunderstood frontiers in tech right now: cryptocurrency regulation.

This isn’t just about keeping up with new laws. It’s about building an entire mental framework to understand risk in an ecosystem that thrives on decentralization but is now colliding head-on with centralized enforcement.

Thinking

I recently gave some thought to the current state of regulation in the industry and came up with something crucial that has been missing from mainstream discourse: how we think about compliance in crypto matters just as much as what we do about it.

Data Layers and the Devil in the Details

Here’s the first truth bomb: not all on-chain data is equal.

You’ve got raw data — think: transaction hashes, sender/receiver addresses, gas fees. Then there’s abstracted data — the kind analysts love, like market cap and trading volume.

Regulators treat these differently, and so should we. If you’re building tools or making investment decisions without distinguishing between raw and abstracted data, you’re flying blind.

What struck me was how clearly this breakdown mirrors infosec risk models. Think of raw data like packet captures. Useful, granular, noisy. Abstracted data is your dashboard — interpretive and prone to bias. You need both to build situational awareness, but you’d better know which is which.

Keep It Simple (But Not Simplistic)

In cybersecurity, we talk a lot about Occam’s Razor. The simplest explanation isn’t always right, but the most efficient solution that meets the requirements usually is.

Crypto compliance right now? It’s bloated. Teams are building Byzantine workflows with multiple overlapping audits, clunky spreadsheets, and policy documents that look like the tax code.

The smarter play is automation. Real-time compliance tooling. Alerting systems that spot anomalies before regulators do. Because let’s be honest — the cost of “too late” in crypto is often existential.

Reverse Engineering Risk: The Inversion Model

Here’s a mental model that should be part of every crypto project’s DNA: Inversion.

Instead of asking “What does good compliance look like?”, start with: “How do we fail?”

Legal penalties. Reputation hits. Token delistings. Work backward from these outcomes and you’ll find the root causes: weak KYC, vague policies, and unauditable code. This is classic hacker thinking — start from the failure state and reverse engineer defenses.

It’s not about paranoia. It’s about resilience.

Structured Due Diligence > FOMO

The paper references EY’s six-pillar framework for token risk analysis — technical, legal, cybersecurity, financial, governance, and reputational. That’s a solid model.

But the key insight is this: frameworks turn chaos into clarity.

It reminds me of the early days of PCI-DSS. Everyone hated it, but the structured checklist forced companies to at least look under the hood. In crypto, where hype still trumps hard questions, a due diligence framework is your best defense against FOMO-driven disaster.

Global Regulation: Same Storm, Different Boats

With MiCA rolling out in the EU and the US swinging between enforcement and innovation depending on who’s in office, we’re entering a phase of compliance relativity.

You can’t memorize the rules. They’ll change next quarter. What you can do is build adaptable frameworks that let you assess risk regardless of the jurisdiction.

That means dedicated compliance committees. Cross-functional teams. Automated KYC that actually works. And most importantly: ongoing, not one-time, risk assessment.

Final Thoughts: The Future Belongs to Systems Thinkers

Crypto isn’t the Wild West anymore. It’s more like the early days of the Internet — still full of potential, still fragile, and now squarely in regulators’ crosshairs.

The organizations that survive won’t be the ones with the flashiest NFTs or the most Discord hype. They’ll be the ones who take compliance seriously — not as a bureaucratic burden, but as a strategic advantage.

Mental models like inversion, Occam’s Razor, and structured due diligence aren’t just academic. They’re how we turn regulatory chaos into operational clarity.

And if you’re still thinking of compliance as a checklist, rather than a mindset?

You’re already behind…

 

 

* AI tools were used as a research assistant for this content, but human moderation and writing are also included. The included images are AI-generated.

Tool Deep Dive: Mental Models Tracker + AI Insights

The productivity and rational-thinking crowd has long loved mental models. We memorize them. We quote them. We sprinkle them into conversations like intellectual seasoning. But here’s the inconvenient truth: very few of us actually track how we use them. Even fewer build systems to reinforce their practical application in daily life. That gap is where this tool deep dive lands.

MentalModels

The Problem: Theory Without a Feedback Loop

You know First Principles Thinking, Inversion, Opportunity Cost, Hanlon’s Razor, the 80/20 Rule, and the rest. But do you know if you’re actually applying them consistently? Or are they just bouncing around in your head, waiting to be summoned by a Twitter thread?

In an increasingly AI-enabled work landscape, knowing mental models isn’t enough. Systems thinking alone won’t save you. Implementation will.

Why Now: The Implementation Era

AI isn’t just a new toolset. It’s a context shifter. We’re all being asked to think faster, act more strategically, and manage complexity in real-time. It’s not just about understanding systems, but executing decisions with clarity and intention. That means our cognitive infrastructure needs reinforcing.

The Tracker: One Week to Conscious Application

I ran a simple demo: one week, one daily journal template, tracking how mental models showed up (or could have) in real-world decisions.

  • A decision or scenario I encountered
  • Which models I applied (or neglected)
  • The outcome (or projected cost of neglect)
  • Reflections on integration with MATTO

You can download the journal template here.

AI Prompt: Your On-Demand Decision Partner

Here’s the ChatGPT prompt I used daily:

“I’m going to describe a situation I encountered today. I want you to help me analyze it using the following mental models: First Principles, Inversion, Opportunity Cost, Diminishing Returns, Hanlon’s Razor, Parkinson’s Law, Loss Aversion, Switching Costs, Circle of Competence, Regret Minimization, Pareto Principle, and Game Theory. First, tell me which models are most relevant. Then, walk me through how to apply them. Then, ask me reflective questions for journaling.”

Integration with MATTO: Tracking the True Cost

In my journaling system, I use MATTO (Money, Attention, Time, Trust, Opportunity) to score decisions. After a model analysis, I tag entries with their relevant MATTO implications:

  • Did I spend unnecessary attention by failing to invert?
  • Did loss aversion skew my sense of opportunity?
  • Was trust eroded due to ignoring second-order consequences?

Final Thought: Self-Awareness at Scale

We don’t need more models. We need mechanisms.

This is a small experiment in building them. Give it a week. Let your decisions become a training dataset. The clarity you’ll gain might just be the edge you’re looking for.

Support My Work

Support the creation of high-impact content and research. Sponsorship opportunities are available for specific topics, whitepapers, tools, or advisory insights. Learn more or contribute here: Buy Me A Coffee

 

* AI tools were used as a research assistant for this content, but human moderation and writing are also included. The included images are AI-generated.

🧠 Betting on Beliefs: Why Bayesian Thinking Belongs in Your Investment Toolbox

If you’ve ever made an investment decision that felt like a coin toss, welcome to the club. 📉📈 Uncertainty is baked into finance, no matter how many spreadsheets or models we throw at it. But here’s the good news: there’s a smarter way to deal with this unpredictability. It’s called Bayesian thinking—and it’s kind of like upgrading your brain with a statistics-powered GPS for navigating risky terrain.

ThinkingNotes

Let’s unpack this, not as a PhD thesis, but like we’re two old friends talking about the markets over coffee (and maybe some bourbon 🍸 if it’s been that kind of quarter).

What’s Bayesian Thinking Anyway?

Named after Thomas Bayes—a statistician and theologian with a knack for probability—Bayesian thinking is all about updating your beliefs as new data comes in. Imagine you’re sailing a boat in foggy weather. You can’t see much, but every ping from your radar helps you refine your course. That’s Bayesian logic at work: start with a guess (your prior), then update that guess as more info rolls in (your posterior).

In the world of investing, this isn’t just helpful—it’s survival gear.

Why This Matters More Than Ever

Markets today feel like riding a rollercoaster with no seatbelt. From crypto crashes to interest rate whiplash, traditional models often fail to keep up. Bayesian methods thrive in these situations because they:

Incorporate uncertainty (instead of pretending it’s not there)
Constantly learn and adapt as conditions change
Handle model errors and parameter guesswork with more nuance than rigid formulas

In other words, Bayesian tools are like having a financial weatherman who admits they don’t know everything—but gets more accurate every time it rains.

Real Talk: Why I Use This Stuff

Here’s a dirty little secret: no model gets it right all the time. But Bayesian approaches admit that up front. They say, “Hey, let’s not commit to one truth. Let’s explore a bunch of possibilities and adjust as we go.” That humility is powerful. Especially in markets where the only constant is change.

Plus, it fits with how humans actually think. We revise our opinions as we learn—why shouldn’t our investment models do the same?

Final Thought: Don’t Be a Dinosaur 🦕 in a Digital Jungle

If you’re still using old-school statistical tools that ignore uncertainty or can’t adapt on the fly, you’re setting yourself up to get blindsided. Bayesian methods aren’t just for math geeks—they’re for anyone serious about managing risk in the real world.

So next time you’re staring at your portfolio, wondering what the heck just happened, ask yourself this: “What do I believe now, and how should I change my mind based on what I just learned?”

That’s the Bayesian mindset.

Stay adaptive. Stay curious. Stay a little skeptical. And as always—question everything.

Coming up next: we’ll dive into how this plays out with real market chaos—from crypto crashes to the currency jungle. 🪙💱📊

 

* AI tools were used as a research assistant for this content, but human moderation and writing are also included. The included images are AI-generated.

 

Inversion Thinking: Solving Backward to Live Forward

I’ve always been a fan of breaking things down to figure out how they work—sometimes that means disassembling old electronics, other times it means turning a question on its head. That’s where inversion comes in.

InversionThinking

Inversion is this strange, elegant mental model—popularized by Charlie Munger but rooted in the mathematical mind of Carl Jacobi—built around a simple idea: if you want to solve something, try solving the opposite. Don’t just ask, “How can I succeed?” Ask, “How might I fail?” Then avoid those failures.

This flipped way of thinking has helped me untangle everything from tricky team dynamics to gnarly security architecture. It’s not magic. It’s just honest thinking. And it’s surprisingly useful—in life and cybersecurity.

Everyday Life: Living by Avoiding the Dumb Stuff

In personal productivity, inversion’s like having a brutally honest friend. Don’t ask how to be productive—ask what makes you waste time. Suddenly you’re cancelling useless meetings, setting agendas, trimming the invite list. It’s not about optimizing your calendar, it’s about not being a dumbass with your calendar.

When it comes to tasks, the question isn’t “How do I get more done?” but “What distracts me?” Turns out, for me, it’s that one open browser tab I swear I’ll close later. Close it now.

Even wellness gets better when you flip the lens. Don’t chase the best workout plan—just ask “Why do I skip the gym?” Too far away, crappy equipment, bad timing. Fix those.

Same with food. I stopped keeping junk in plain sight. I eat better now, not because I have more willpower, but because I don’t trip over the Oreos every time I pass the kitchen.

Inversion also made me rethink how I spend money. Don’t ask “How do I save more?” Ask “What makes me blow cash unnecessarily?” That late-night Amazon scroll? Canceled. That gym membership I never use? Gone.

Relationships: Avoiding Trust Bombs

In relationships—especially the ones you care about—you want to build trust. But instead of obsessing over how to build it, ask “What destroys trust?” Lying. Inconsistency. Oversharing someone’s private stuff. Don’t do those things.

Want better communication? Don’t start with strategies. Just stop interrupting, assuming, or trying to fix everything when people just want to be heard.

Cybersecurity: Think Like the Adversary

Now let’s pivot to my day job: security. Inversion is baked into the best security thinking. It’s how I do architecture reviews: don’t ask, “Is this secure?” Ask, “If I were going to break this, how would I do it?”

It’s how I approach resource planning: “What failure would hurt us the most?” Not “Where should we invest?” The pain points reveal your priorities.

Even in incident response, I run pre-mortems: “Let’s assume this defense fails—what went wrong?” It’s bleak, but effective.

Want to design better user behavior? Don’t pile on password rules. Ask “What makes users work around them?” Then fix the root causes. If people hate your training, ask why. Then stop doing the thing that makes them hate it.

The Big Idea: Don’t Try to Be Smart. Just Don’t Be Stupid.

“It is remarkable how much long-term advantage people like us have gotten by trying to be consistently not stupid, instead of trying to be very intelligent.” — Charlie Munger

We don’t need to be clever all the time. We need to stop sabotaging ourselves.

Inversion helps you see the hidden traps. It doesn’t promise easy answers, but it gives you better questions. And sometimes, asking the right wrong question is the smartest thing you can do.

Would love to hear how you’ve used inversion in your own life or work. Leave a note or shoot me an email. Always curious how others are flipping the script.

 

 

* AI tools were used as a research assistant for this content, but human moderation and writing are also included. The included images are AI-generated.