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Damilare Osibanjo — systems & software programmer

// BIO

I started programming by exploring mechanical limits and systems boundaries rather than just writing application code. At age 12, I was building environments in Roblox, writing Lua scripts that handled client-server replication, high-frequency physics ticks, event loop orchestration, and state synchronization. It taught me that all computing behaves according to precise rules.

By age 14, I moved to Python to build automation systems, non-blocking network scrapers, and data pipelines. Exploring concurrency led me to study the mechanics of OS threads, physical memory footprints, and the bottlenecks of the Python Global Interpreter Lock (GIL). I realized that high-level abstractions often hide the actual cost of execution.

To gain fine-grained control over execution, memory, and performance, I moved down the stack to Rust, Go, C, and Zig, while simultaneously building high-performance web applications using TypeScript and modern web architectures. Systems programming and web programming are not separate worlds to me; they require the same attention to mechanical sympathy, latency, and correctness.

Over the last few years, my work has focused on building foundational software:

  • operating system kernels: wrote Karion OS, an x86 kernel in Rust, implementing physical memory management, virtual paging, pre-emptive scheduling, and a custom virtual filesystem (VFS).
  • compilers & runtimes: built Carv (a systems language targeting ARM and x86 architectures compiling to C) and Track (a systems language compiler targeting LLVM 22 using linear types and compile-time borrow checking).
  • low-latency virtualization: upgraded Ignite into a hardware-isolated microVM sandboxing runtime in Rust utilizing KVM (Firecracker) and Virtualization.framework for secure execution of untrusted scripts.
  • deep learning & recommendations: built gnn-recommender, a graph neural network recommendation engine from scratch in PyTorch, integrating LightGCN, self-supervised learning, and knowledge graph augmentation.
  • distributed web backends: built brpc (a zero-dependency multiplexed TCP JSON-RPC library in C) and custom web tooling leveraging Bun, Node.js, and TypeScript.

I operate across the full stack. Whether I am writing kernel interrupt routines, optimizing LLVM intermediate representation (IR), configuring virtual block devices, training graph neural networks, or building responsive, animation-rich web UIs with React and Astro, my goal is to design software that is secure, correct, and performant by default.

// TECH STACK

languages: typescript, javascript, rust, go, c, assembly (x86/arm), python, lua, zig
web & rts: react, next.js, astro, tailwindcss, bun, node.js, webassembly
systems/infra: kvm, firecracker, virtualization.framework, linux kernel, docker, kubernetes, git
ai/ml: pytorch, tensorboard, graph neural networks (gnns), contrastive learning
databases: postgresql, redis, mongodb, custom block filesystems

// TIMELINE

2026 (present)
building xelvo & track
developing high-performance WebAssembly compiler (xelvo) and LLVM-backed linear type compiler (track)
2025 (age 17)
deep learning & compiler engineering
implementing gnn recommender engines from scratch, designing carv compiler, and building firecracker runtimes
2024 (age 16-17)
kernel engineering
writing Karion OS kernel in Rust: pre-emptive scheduler, custom VFS, GDT/IDT/PIC assembly setups
2023 (age 15-16)
distributed APIs & systems
high-concurrency web APIs, WebSocket servers, and zero-dependency logging architectures (zario)
2022 (age 14)
python journey
automation scripts, API integrations, backend-style experiments
2021 (age 13)
logic expansion
scaling game mechanics, event-driven loops, scripting complexities
2020 (age 12)
first experiments
roblox game development, lua scripting, learning conditional logic