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AI agents may know Haskell, Git, and CI, but they do not know how your team actually works. At Serokell, we turned our internal engineering guidelines into Claude Code skills so agents could follow the same conventions as our engineers. This post covers how those skills became a reusable plugin and what we learned from testing it on real repositories.

In 2023, Serokell launched the Haskell Certification Program with an ambitious goal: to create a reliable, industry-wide standard for evaluating Haskell expertise. We built and launched the platform, developed an open certification framework, and later transferred the initiative to the Haskell Foundation. Three years on, both the project and the broader software engineering landscape have changed. In this article, we look back at what the program achieved, how its direction evolved, and why Serokell is now concluding its active involvement in the initiative.

In this interview, we speak with Solana cofounder Greg Fitzgerald about why Rust ultimately proved to be the right fit. We discuss how his background in C++, LLVM, and Haskell shaped Solana’s architecture, what functional programming contributed to the design of a high-performance blockchain runtime, and why Rust’s combination of strong types, memory safety, and low-level control worked particularly well for BPF and virtual-machine development.

Most blockchains are built around transparency: smart contracts, transactions, and state changes are visible to everyone. That works well in many cases, but it becomes a problem when organizations need to coordinate without exposing sensitive data. The Canton Network takes a different approach. It is designed for privacy, data sovereignty, and interoperability, allowing participants to share only the information required for a given transaction. Canton applications are commonly built with Daml, a strongly typed functional smart contract language centered on parties, authorization, contracts, and multi-party workflows. In this article, we’ll introduce Canton and Daml, compare Daml with Solidity, and build a small banking application. Along the way, we’ll see how privacy and authorization requirements influence smart contract architecture.

For VC teams, valuable knowledge is everywhere: PDFs, inboxes, call transcripts, news feeds, and internal notes. The problem is getting the right context when you actually need it. We built a platform that brings all of this information into a single searchable knowledge base, with LLM agents on top that can: • prepare meeting briefings • research people and companies • answer questions across the firm’s internal knowledge • continuously ingest and structure new information In the article, we go under the hood and explain how the system works, including its storage architecture, seven-stage ingestion pipeline, Airflow automations, and the agent layer that we substantially redesigned after the first production release. We also cover a production incident that changed how we approached monitoring and reliability. If you’re building RAG systems, internal AI assistants, or agentic workflows on top of large amounts of unstructured company data, this one gets pretty technical.

In this interview, we discuss what needs to change for Haskell to reach more developers and companies, and where the Haskell Foundation can have the greatest impact. We also look at Haskell from the perspective of a large financial system at Bitnomial: how type safety and effect tracking help engineers manage correctness at scale, where the complexity budget for advanced types should be spent, and why technologies such as Servant remain powerful tools for moving guarantees from individual applications to entire systems.