Tech Events & Workshops

A practical two-hour session on Rust Data Processing with Polars, focused on CSV, Parquet, Joins, and Lazy Queries. Rust is used as the implementation context while the core lesson stays on software engineering fundamentals, reliability, testing, and operational clarity. Audience: entry-level and intermediate developers who want a practical engineering session, not a language tour. Outcomes: - Explain the practical boundaries of Rust Data Processing with Polars - Apply CSV in a small working example - Apply Parquet in a small working example - Apply Joins in a small working example Format: two hours with a short framing walkthrough, a concrete example, discussion of tradeoffs, and a closing checklist for practice.

We can now generate code faster than ever, but that creates a new problem: teams can also generate confusion, duplication, and fragile architecture faster than ever. In this session, we'll explore how to design software systems that help both humans and AI move faster safely. The focus is on clear module boundaries, reusable components, stable interfaces, validation contracts, and Polylith-inspired thinking from the Clojure ecosystem. ## What We'll Cover - **Modular Architecture for AI-Assisted Development:** Structure large systems so features have clear ownership and predictable boundaries. - **Interfaces as Guardrails:** Use narrow interfaces to make code easier to replace, test, and reason about. - **Contracts & Validation:** Treat validation rules and schemas as a shared source of truth between humans, tools, and AI agents. - **Multi-Project Reuse:** Learn how shared components can support multiple products without turning into a tangled framework. - **Metaprogramming & Automation:** Use macros, code generation, and declarative patterns to reduce repetitive implementation work. ## Why Attend? If you're using AI to build software, the real question is no longer "Can it write code?" The question is: **can your architecture absorb that speed without collapsing under complexity?** This talk is for developers who want to build larger systems faster while keeping the codebase understandable, testable, and adaptable.