Scalable products
I like to start with something that works, then evolve it under pressure. I’m interested in the invisible glue that holds systems together, queues that keep data moving, caches that smooth over latency, and APIs that stay solid under load. The challenge is always the same: build for scale without over engineering.
Good infrastructure should fade into the background. When it does its job, the product feels fast, predictable, and quietly powerful. That’s what I aim for.
Performance-minded Rust
Rust enforces clarity: ownership, lifetimes, and immutability are design choices, not just compiler constraints. I reach for it when performance, predictability, and correctness matter more than iteration speed.
Rayon and structured parallelism make it straightforward to scale workloads safely. Profiling, tracing, and property-based testing keep assumptions honest and feedback tight. Over time, I’ve learned that performance isn’t about clever tricks, it’s about removing uncertainty and trusting measurement.
Good Rust code should be straightforward to read and dependable in production: clear intent, stable behavior, minimal magic.
Tools for teams
The most meaningful leverage comes from helping teams move in rhythm. I care about the boring parts that make this possible: clean CI pipelines, fast feedback, well-tuned linters, and docs that people actually read.
I’ve been exploring AI-assisted development not as replacement but as augmentation, pairing bots with humans to reduce toil and surface insight faster. When used right, these tools act like good colleagues: attentive, consistent, and unoffended by repetition.
Ultimately, tools are about communication. Good ones make intent visible, friction low, and progress obvious. They let people focus on the work that actually matters. If you’re experimenting with AI pair flows, I’d love to compare notes.
