👋🏻 GM frens, it’s Leo here. I’m the co-founder of ChainHire — your trusted Web3 job board & info hub.
Welcome to the very first edition of our new series: Builder Spotlight 🎙️ Every week, we’ll be sitting down with the minds behind the most interesting Web3 and crypto projects — not just the brands, but the actual humans building the future.
This series is all about real conversations with real builders. Beyond the buzzwords, we’re here to unpack what actually goes into building Web3 — from cryptography and infrastructure to community, culture, and conviction. We want to know what drives these folks, what problems keep them up at night, and what they see coming next.
Whether you’re already deep in the trench or just peeking in from the edge, we hope these spotlights inspire you — to build, to ask better questions, or to find your own way into Web3.
I hope you’ll enjoy reading this series — and if you’re building something exciting in Web3 and want to chat about it, DM me here!
For our very first spotlight, I caught up with Dylan Kawalec, Head of Developer Relations at Phala Network — a team pioneering privacy-first cloud computing in Web3.
How it all started: One random night, I was deep in a rabbit hole reading about Web3 privacy when I stumbled on Dylan’s post about DStack — Phala’s open-source confidential computing toolkit. I cold-messaged him — zero warm intro. Fast forward: we traded contacts and ended up having a 90-minute deep dive about trustless AI, cryptography, and why devs shouldn’t just be “coding monkeys.”
🧑💻 Dylan Kawalec — Head of DevRel at Phala Network
Dylan is the Head of Developer Relations at Phala Network — a Web3 computing cloud that supports data privacy while staying trustless.
He’s been in the trenches for years: building secure crypto exchanges, wallets, decentralized custody tools, and quantum-resistant frameworks (lattice crypto, ZK proofs, homomorphic encryption). He’s helped shape real, resilient infrastructure for teams like GOAT Network, Osmosis, and now Phala — where he’s pushing the frontier of privacy-first AI.
In short? If you care about secure, verifiable AI that doesn’t leak your brain to the cloud — Dylan’s your guy.
✅ Key Summary
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Phala Network is building the “zero-trust cloud” for Web3 — A decentralized computing layer that keeps sensitive workloads private while staying verifiable and trustless.
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Trusted Execution Environments (TEEs) are like secure black boxes for your code — they keep data private even from the host and generate cryptographic proofs that everything ran as promised.
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Web3 privacy is still early, but Dylan sees it as the backbone for trustless AI - From Facebook to AI chatbots, we keep paying with our data — the next generation of apps should make privacy the default, not an afterthought.
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Combining TEEs and Zero-Knowledge Proofs is the missing link for Safe AGI - The hardware keeps your data safe; ZK keeps it provable. Together, they unlock AI you don’t have to blindly trust.
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Good devs don’t just code — they research, benchmark, translate, and sell - Dylan’s big on the idea that you have to know your stuff, make sure people know you know your stuff, and make sure they know the right stuff you want them to know.
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Going to dev conferences, pitching real use cases, and educating others is real DevRel work. - It’s not just about hype — it’s about giving people a clear direction and showing why what you’re building matters.
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What Pulled You Into Crypto and Web3 Privacy?
Dylan’s north star is simple: trust and resilience
“I saw how fragile trust was in traditional tech — single points of failure, centralized servers, your data getting siphoned off without you even knowing. Crypto and Web3 flip that. You own your keys, your data stays yours, and you don’t have to trust a middleman who might fail you.”
For him, it’s all about solving real problems and making sure you can clearly explain what you’re building and why — that’s the mark of a good dev.
So… What Is Phala Network?
Phala is a Web3 computing cloud that runs private, trustless workloads. In Web2, you’d trust AWS or Azure to keep your data safe. With Phala, your workload runs inside a Trusted Execution Environment (TEE) on a decentralized network of nodes — so no single operator can snoop.
- TEE + Blockchain: The TEE keeps your data private; the blockchain verifies it ran as promised.
- Powered by DStack: Phala now runs on DStack — its own decentralized confidential computing layer. Built around containerized workloads and Trusted Execution Environments (TEEs), DStack makes it easy to deploy secure off-chain compute that connects directly to on-chain logic — without needing to manage your own enclave infrastructure.
- Trustless by design: Remote attestation provides verifiable, hardware-level proofs that your AI workloads are executing inside trusted, tamper-resistant environments.
- Tailored for AI: Phala lets you launch AI agents that run privately, hold their own keys, and prove they’re acting honestly.
- Strong ecosystem: Phala works with researchers across multiple leading organizations to pioneer applications in confidential AI, multi-TEE setups, and ZK-enhanced trust layers. In short? Phala is the “zero-trust cloud” for Web3 — private, verifiable apps, no single point of failure
From Facebook to AI: The Same Old Trap (and Why TEEs Matter)
“Back then, people got their data used by Facebook for free. Now they pay for ChatGPT or Grok — and still hand over their most sensitive and private data without blinking. Meanwhile these systems AI Security is still overlooked. We need to fix that”
Dylan’s point: privacy and security can’t be bolted on later — they have to be built in from day one.
One piece of that puzzle is the TEE:
It’s like a secure, isolated “black box” in your CPU. When you run code inside it, no one — not even the server host — can peek or tamper with it. Big banks and cloud providers (Intel TDX is a classic) use TEEs in Web2 — but in Web3? It’s still early.
That gap = huge opportunity for privacy-first builders on Phala.
📚 Want more? Read our explainer: What is a TEE and Why It Matters for Web3
Dylan’s Dream Use Case of Phala: Safe AGI
“Imagine an AI clone that learns from your data — your messages, your preferences — but never exposes it. You get hyper-personalization and powerful AI, but all your data stays private thanks to a TEE. Add on-chain verifiability or validation support, and now you’ve got a Confidential AI layer that doesn’t leak your secrets to “cough” OpenAI “cough” Grok. This is how we get to Safe AGI.”
- You get personalization
- Your data stays private
- TEE + Blockchain = trustless verification
Sounds sci-fi? It’s already happening.
🧩 ZK + TEE: The Next Milestone
“TEEs make private compute practical. ZK proofs make the results verifiable — without leaking secrets. Together, they’re used to link information from users to build Safe AGI.”
This is Dylan’s “zero-trust Verification” — the hardware + cryptography do the proving. No more blind trust.
🔒 What Makes Phala Stand Out?
Sure, Azure Confidential Computing is great — but at the end of the day, it’s still centralized. You’re just trusting Microsoft not to peek or flip a switch.
Phala’s network?
- ✅ Permissionless applications, like autonomous AI
- ✅ Blockchain-native Key Management System.
- ✅ Decentralized TEE nodes with on-chain attestation.
- ✅ No single point of failure.
- ✅ Verifiable workloads — hardware + software quotes.
⚙️ What You Should Know Before You Start Building
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✅ Not a Layer 1 — it’s a decentralized confidential compute network - Runs on dstack security
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✅ DStack + Docker: Package your app as a container, run it inside a TEE, and connect to smart contracts in a verifiable manner. Host the application with domain router to connect to your Rust, Python, or even JS applications in the Phala container.
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✅ Jupyter Notebook tutorial: Try it out with their Docker Compose guide — benchmark your code, learn how it works.
What’s your advice for someone who wants to be a DevReL
“Whether you’re a developer, a researcher, or in Developer Relations — you can’t just be a ‘coding monkey.’ Great devs educate others, give people direction, and help teams see why the work matters. But the biggest skill? You have to know how to share what you’re doing — and why it matters, who it’s for, and why people should care. If you can’t explain that, your work will never get the traction it deserves. Being great in DevRel is a mix of deep technical work and clear storytelling.”
Dylan’s daily mantra:
🔬 Research deeply: Understand the complex stuff — inside and out.
🧭 Map out real-world use cases: Think hard about how this tech can solve real problems — design actual applications, not just abstract theory.
✍️ Translate complex tech clearly: Break down the deep tech so other devs, founders, and even non-technical folks actually get it.
💡 Sell the vision: Don’t underestimate this — selling is the most important skill.
If you can’t explain why it matters, your work won’t stick. So in short? Good builders code. Great builders research, pitch, teach, and sell — then hit the road and do it again. That’s the real DNA of DevRel, and that’s how you help reshape an industry from the inside out.
📣 Ready to Dive In?
✅ Check out Phala: Phala Network
✅ Follow Along the Jupyter Notebook Guide: Deploying an MCP Server on Phala Cloud: A Step-by-Step Guide for Developers
✅ Learn More on Dstack: DStack Documentation
✅ Check out grants and event from Phala Ecosystem: Ecosystem Partner
