Why MacroBytes Exists?
MacroBytes was created by Atharv Vasisht as a way to make sense of the increasingly complex world where finance, data, and technology intersect.
What began as a personal curiosity project—writing, charting, and breaking down systems to understand how things actually work—has evolved into a platform designed to promote clarity, micro-learning, and curiosity about the trends shaping our world.
As a data-driven problem solver fascinated by financial markets, corporate strategy, and the applications of emerging technologies in AI, quantum computing, and cybersecurity, I kept running into one challenge: the information was out there, but it was scattered, noisy, and siloed—hard to translate into a cohesive understanding of how systems interconnect.
MacroBytes is my preliminary (and very imperfect) attempt to bridge that gap—to take what’s complicated, and make it structured, approachable, and useful.
It’s not built for clicks, followers, or monetization.
It’s built for people who, like me, want to understand markets, business models, and technology deeply and critically.
While the platform is constantly evolving, if you’re someone passionate about shaping a future where financial markets, technology, and business leadership harmonize to make the world better, I invite you to join me in this journey.
Hi, I’m Atharv
I’m a data-driven problem solver with a deep interest in finance, emerging technology, and the systems that tie them together. Whether it’s understanding markets, decoding AI, or exploring strategy, I’ve always been drawn to clarity, and making data digestible. MacroBytes is where I share that journey — simplifying what’s complex, one topic at a time.
What Defines Me
MacroBytes FAQ
Everything you need to know about how we work, what we cover, and who this is for.
Topics
What topics does MacroBytes cover?
- LLMs & GPUs: architectures, training vs. inference economics, supply chains (fabs → HBM → networking).
- Data centers & energy: power density, cooling, siting constraints, grid realities, and capex.
- Markets & macro: narrative diffusion, what drives multiples, and where risk hides.
- Cyber risk: identity, control frameworks, data-plane security, and AI-augmented defense.
Every deep dive pairs the tech under the hood with the business reality.
Method
How do you approach a topic?
- Frame: Define the exact question and success criteria.
- Deconstruct: Map core drivers (math, systems, incentives, cost curves); separate facts from assumptions.
- Rebuild: Write it simply; add diagrams where they carry load; call out caveats.
- Apply: Translate into implications for pricing, product, strategy, or risk.
Outputs aim to be reusable frameworks—not just hot takes.
Goal
What is MacroBytes trying to achieve?
To translate complex finance and technology into digestible, actionable understanding—so students, builders, and operators can make better decisions faster. Content is treated as a public good: open, reusable, and compounding over time.
Values
What MacroBytes is—and isn’t
- Not-for-profit: learning-first; no ads or paywalls.
- Evidence over virality: accuracy, sources, and limitations are explicit.
- No hype treadmill: we publish when there’s something useful to add.
- Respect for time: tight writing, clean visuals, practical summaries.
Bridge
How do finance and technology connect here?
We intentionally interlock the sections—tech explains how things work; finance explains where value accrues and why.
- From FLOPs to $$: convert model/hardware metrics into unit economics and margins.
- Stress-test narratives against constraints: power, latency, memory, regulation, and talent.
- Trace the cash: follow value through stacks and supply chains.
Audience
Who is MacroBytes for?
- Builders & operators who need sober inputs for product and resource allocation.
- Investors & analysts who want frameworks that travel across cycles.
- Students & self-learners who prefer signal over noise and value first-principles thinking.
If you’re curious and respectful, you’re in the right place.
Roadmap
What’s next for MacroBytes?
- Series: LLM cost stacks; GPU supply chain; data-center siting & power; AI + cyber defense patterns.
- Finance deep-dives: valuation under compute constraints; capex cycles; pricing power in AI value chains.
- Visual briefs: one-page diagrams to summarize systems, market structures, and theses.
Have a request or correction? Join the discourse and help improve the work.