Clarity before complexity
Code is read far more often than it is written. Obvious logic usually wins over cleverness.
The technologies I use will change over time. The principles I build around will not.
I enjoy solving problems that become more interesting as systems grow, especially around software engineering, AI, automation, and long-term system reliability.
I care about systems that stay dependable under pressure, teams that can reason clearly about trade-offs, and products that remain maintainable long after the first release.
Code is read far more often than it is written. Obvious logic usually wins over cleverness.
Systems should fail predictably. Boundaries, retries, and operational safety matter more than novelty.
If you cannot see what your system is doing, you cannot trust it. Telemetry is a feature.
Automation amplifies capabilities, but foundational engineering understanding still sets direction.
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Designing an AI-powered self-healing backend operations agent that helps production systems detect, diagnose, and recover from failures while keeping engineers in control.
The research explores how AI can improve reliability, observability, and operational resilience without sacrificing engineering judgement.
Strength training keeps me disciplined and grounded. The progression mindset maps well to engineering work.
Long-distance running gives me the mental space to think through complex systems problems away from the screen.
I care about learning with other builders, sharing ideas, and staying connected to people doing serious work.
I spend time studying systems, infrastructure, AI, and the mechanics behind reliable software.