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Multilingual benchmarking project => Bazel for advanced engineering

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In her one year, Molly saw many more exciting places than I did until I was about 28. She does pretty well :-D

When working on performance experiments across C++ and Go, you obviously need a multilingual project structure. There were two paths forward: create separate build systems under a shared repository, or consolidate everything under a single, coherent framework. Bazel made that decision easy.

Using Bazel to unify builds isn’t just convenient—it should be the default choice for any serious engineering effort that involves multiple languages. It eliminates the friction of managing isolated tools, brings deterministic builds, and handles dependencies, benchmarking, and cross-language coordination with minimal ceremony.

Here’s why Bazel makes sense for performance-critical, multilingual projects like this one—no fragile tooling, no redundant setups, just clean integration that scales.

  • in Go, AI
  • 4 min read

AI, Software Engineering, and the Evolution of Code Generation

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From a weekend trip to a nearby gorge. Why is it here? Because I love the mountains of Kyrgyzstan!

Mark Zuckerberg recently made a bold statement: AI will soon take over the work of mid-level engineers (Forbes). While this may sound like another tech CEO hyping AI, my latest experience with OpenAI’s o3-mini-high model suggests he might not be too far off.

Thanks to DeepSeek, OpenAI was compelled to make o3-mini-high available in a regular ChatGPT subscription instead of locking it behind a steep $200 paywall. I would never pay original $200 for a model, but since I already have the regular ChatGPT subscription, it was an obvious choice to try it out. With this in mind, I decided to experiment: Could o3-mini-high generate a functional Go codebase for my GFSM library?

The experiment

For context, GFSM is my Go Finite State Machine library, and I needed a new generator to extract and save state machines in formats like PlantUML and Mermaid. Writing such a generator requires a solid understanding of Go’s Abstract Syntax Tree (AST) package, something I hadn’t used in years.

Returning to Rust: A Journey Through Tooling, Performance

When I started tackling the Maelstrom challenges, my initial thought was to use C++. It’s a language I know inside out, and its performance is hard to beat. However, as I contemplated setting up the project, I realized I couldn’t justify fighting with the C++ pipeline for free. Crafting a proper CMake or Bazel configuration might be worthwhile for large-scale projects or when compensated, but for personal experiments? It’s an unnecessary headache.

Why Go is My Default Choice

For most non-performance critical scenarios, Go is my default, no-brainer choice. It has a clean build system, excellent tooling, and a developer experience that doesn’t make me dread the setup process. Go’s simplicity allows me (and any level team) to focus on solving the problem rather than wrestling with the environment. Yet, this time, I decided to take a different path.

Minimal CI for Go library with GitHub actions

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Continuous Integration (CI) has become an essential part of modern software development, and for good reason. It ensures code quality, speeds up development, and catches potential issues early. However, you can get started without an elaborate CI setup. Even a minimal CI setup can significantly improve your workflow. Here's why every project should have at least minimal CI and how to implement it effectively using GitHub Actions.

What Constitutes Minimal CI?

For a project to benefit from CI without excessive complexity, it should include the following essential components:

  1. Project Compilation: Verify that the codebase is always in a buildable state.
  2. Unit Test Execution: Ensure the core functionality works as expected.
  3. Static Code Analysis: Catch bugs and enforce coding standards before they become an issue.

GFSM: A Simple and Fast Finite State Machine for Go

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Design patterns are not widely used in Go, as they can often lead to unnecessary complexity in the codebase. However, the Finite State Machine (FSM) is an exception that proves to be incredibly useful. When I set out to design GFSM, I aimed to create a fast and straightforward FSM implementation for Go.

I initially sought a quick and straightforward FSM solution for Go, but I couldn't find anything that met my needs. Drawing inspiration from the speed-focused and minimalistic principles of C++ while remaining true to Go's idioms, I developed GFSM to fill this gap. The outcome is GFSM—a library that distinguishes itself from alternatives like looplab/fsm by prioritizing speed and simplicity.

Whether orchestrating microservices, handling distributed systems, or designing embedded systems, GFSM brings the reliability and efficiency needed to keep things running smoothly.