thinking

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.

Building My Daily Framework

My days are structured around a concept I call the “Minimum Viable Day.” It’s about identifying the essential tasks that,
if accomplished, make the day successful. To manage tasks and projects, I employ a variant of the Eisenhower Matrix that I coded for myself in Xojo. This matrix helps me prioritize based on urgency and importance.

Each week begins with a comprehensive review of the past week, followed by a MATTO (Money, Attention, Time, Turbulence, Opportunity)
analysis for the upcoming week. This process ensures I allocate my resources effectively. I also revisit my “Not To Do List,”
a set of personal guidelines to keep me focused and avoid common pitfalls. Examples include:

Don’t be a soldier; be a general—empower the team to overcome challenges.

Avoid checking email outside scheduled times.

Refrain from engaging in inane arguments.

Before agreeing to something, ask, “Does this make me happy?”

Time-blocking is another critical component. It allows me to dedicate specific periods to tasks and long-term projects,
ensuring consistent progress.

Mental Models in Action

Throughout my day, I apply various mental models to enhance decision-making and efficiency:

EDSAM: Eliminate, Delegate, Simplify, Automate, and Maintain—my approach to task management.

Pareto Principle: Focusing on the 20% of efforts that yield 80% of results.

Occam’s Razor: Preferring simpler solutions when faced with complex problems, and looking for the path with the least assumptions.

Inversion: Considering what I want to avoid to understand better what I want to achieve.

Compounding: Recognizing that minor, consistent improvements lead to significant long-term gains.

These models serve as lenses through which I view challenges, ensuring that my actions are timely, accurate, and valuable.

Teaching and Mentorship

Sharing these frameworks with others has become a significant focus in my life. I aim to impart these principles through content creation and mentorship, helping others develop their own systems and mental models. It’s a rewarding endeavor to watch mentees apply these concepts to navigate their paths more effectively.

The Power of Compounding

If there’s one principle I advocate for everyone to adopt, it’s compounding. Life operates as a feedback loop: the energy and actions you invest return amplified. Invest in value, and you’ll receive increased value; invest in compassion, and kindness will follow. Each decision shapes your future, even if the impact isn’t immediately apparent. By striving to be a better version of myself daily and optimizing my approaches, I’ve witnessed the profound effects of this principle.

Embracing systems thinking and mental models isn’t just about efficiency; it’s about crafting a life aligned with your values and goals.
By consciously designing our routines and decisions, we can navigate complexity with clarity and purpose.