Serokell’s GHC team continues sharing progress on Dependent Haskell. @int_index presents three major contributions and a host of smaller improvements that push Dependent Haskell closer to becoming a practical reality. serokell.io/blog/serokell-s-…

In this interview, @lisyarus discusses C , Rust, systems programming, and game development, including memory safety, language complexity, engine design, and lessons from shipping Costa Verde. serokell.io/blog/rust-c-and-…

Let’s connect in Miami 🌴 Meet our CBDO, Roman Alterman, at @consensus2026 — a flagship crypto and Web3 conference bringing together global blockchain leaders. May 5-7, Miami Beach Convention Center Schedule a meeting: linkedin.com/in/roman-alterm…

We’ve just completed a deep code & architecture review with @serokell ahead of mainnet. Cube – concentrated liquidity DEX on @solana that combines multi-token pools and leverage, natively giving high double-digit APYs (achieved in real tests). Scope included: • core smart contracts • execution logic (incl. virtual balances / leverage mechanics) • edge cases, attack surfaces, performance Serokell is an engineering and research team with 11 years of experience in blockchain security. They bring experience from projects like @1inch and other complex DeFi systems to our dex! Cube is now in a much stronger position to ship.

Hiring: DevOps Engineer at Serokell Looking for a strong infra-focused engineer with experience in Docker, Kubernetes, CI/CD, monitoring, Linux, networking, and production reliability. Remote. Details: serokell.io/jobs/devops-engi…

MonadBaseControl is tricky to use correctly and easy to misuse, even for experienced developers. This article builds a clear mental model for using it safely, highlights the risks, and shows how to avoid common pitfalls. serokell.io/blog/the-hidden-…

We’re seeking a middle to senior level Solidity Developer to join a team of fierce and fun Serokellers. serokell.io/jobs/solidity-de…

We are looking for a Protocol Engineer to join our team and work on blockchain infrastructure and protocol-level components. serokell.io/jobs/protocol-en…

In this blog post, we’ll discuss the peculiarities of Solana and its architecture and cover the basics of developing smart contracts on it. serokell.io/blog/solana-smar…

Why was RustRover created, and how does real user data shape what we build next? In this interview with @serokell, @VBragilevsky explains how we support Rust and why our focus areas include debugging, async workflows, and cargo-nextest. Read the full conversation 👇 serokell.io/blog/rust-in-pro…

This interview covers how JetBrains supports Rust language, why they launched RustRover, and how user data drives focus on debugging, async workflows, and cargo-nextest. Today’s guest is the Head of the Rust Ecosystem at @jetbrains, @VBragilevsky. serokell.io/blog/rust-in-pro…

We're among the top AI agent providers! Thanks to @clutch_co for recognizing our efforts!

GenAI hype is everywhere, but an MIT-backed 2025 study finds 95% of organizations see no measurable ROI despite $30–40B in spend. We unpack the “GenAI Divide” and how to move from pilots to real business impact. serokell.io/blog/beyond-the-…

Emerging systems such as MemGPT and modular agent frameworks point toward a future of autonomous, self-managing memory. serokell.io/blog/design-patt…

We’re temporarily not shipping the best Haskell merch to the U.S., but we’re happy to send orders to other locations. Premium cotton tees packed with stickers. Perfect for your Haskell best friend, but we don’t mind if you gift our tee to your enemy. shop.serokell.io/

🤔 Is AI capable of learning from its own mistakes? A fascinating point that Arseniy Seroka, CEO of @blooper_ai and @serokell, brought up on my podcast earlier this year, is that AI is trained on our data - and that includes our mistakes. We were discussing open sourcing code, and the risk-reward of doing so, and Arseniy made a great comment: "Just by stealing the code, you don't get the idea of the code. You don't get the possibility to expand it. You don't get the knowledge behind the team." AI is getting the raw code, but it's not getting the knowledge developed over weeks, months, or years of iteration to reach that point. And if the code is incomplete, or worse, broken - can the AI make the necessary corrections if none were available in its training data? This is the true measure of AI and the question of its ability to actually "create" rather than simply reproduce what's already been created. So, my question for you today: do you think AI will achieve the ability to create on its own? Do you think some models already have?

Hiring Senior SDET (remote). Lead TypeScript automation at scale. 5 yrs QA in blockchain/fintech, API/UI/CLI, security testing, CI/CD (GH Actions, Docker), advanced Git. Rust/k6/Web3 a plus.  #SDET #QA #TypeScript #Web3Jobs serokell.io/jobs/senior-sdet

Read this series of articles by @serokell about Haskell in Production serokell.io/blog/haskell-in-…

The agent hype cycle is peaking. After building real systems, we’ve seen the math, the costs, and the engineering reality. Most of the hype just doesn’t survive production. Here’s what actually works — and what doesn’t: serokell.io/blog/the-real-li…

Hiring Technical Sales Executive (remote) at Serokell. Must: technical degree, 3 yrs closing B2B IT consulting/custom software, outbound hunter, great at CTO/C-level meetings, clear English. Not SDR-only. DM with CV biggest closed deal. serokell.io/jobs/technical-s…