System design, AI engineering, databases, networking, concurrency and more, written for engineers building real trading and fintech systems — part of the Algomi Suite.
The object-oriented vocabulary and the handful of design patterns that machine-coding rounds actually use, explained like you are five through one tea shop, then shown in short runnable Java.
Created 2026-09-29 · Updated 2026-10-15 · System Design
One busy restaurant kitchen explains race conditions, locks, deadlock, producer-consumer, thread pools, and thread-safe class design, with runnable Java 17 code and the Java-specific facts (memory model, volatile, ReentrantLock, ConcurrentHashMap, virtual threads) interviewers probe.
Created 2026-09-29 · Updated 2026-10-15 · System Design
Four classic machine-coding rounds solved in modern Java through one neighbourhood shopping mall: the basement parking lot, the front-shelf LRU cache, the food-court token bucket, and the snack vending machine, each with design reasoning and follow-ups.
Created 2026-09-29 · Updated 2026-10-15 · System Design
One weekend hotel trip, told in modern Java: expense sharing with debt simplification, a lift scheduler, tic-tac-toe with O(1) win checks, a pluggable trip diary (logger), plus class sketches for seat booking, notifications, a library, cab dispatch, food delivery, and chess.
Created 2026-09-29 · Updated 2026-10-15 · System Design
Prompts tell an agent what to do; a harness decides what it knows, what it may touch, and what counts as done. Five subsystems, the session lifecycle, and a working Java shift-handover model, told as a hospital night ward.
Created 2026-10-02 · Updated 2026-10-15 · AI Solutions Architecture & AI Engineering
How to turn repeated prompting into a controlled loop: goal loops, a separate checker, retry budgets, state kept outside the loop, reusable skills, and a tool gateway with permissions, timeouts and idempotency. Told as a child doing homework.
Created 2026-10-02 · Updated 2026-10-15 · AI Solutions Architecture & AI Engineering
When one loop is not enough: model the workflow as a graph, fan work out and back in, isolate parallel agents, roll back on failure, gate risky steps on a human, and measure the harness with ablation tests. Told as building a house.
Created 2026-10-02 · Updated 2026-10-15 · AI Solutions Architecture & AI Engineering
