๐Ÿงช The Lab

Dig to the bottom of each topic and see it work. You write the implementation; the Lab makes the internals visible, runnable, and tweakable โ€” so you can prove you truly understand it and explain it to anyone.

AI engineering

โ€” bounded numeric and mock-model engines with explicit evidence labels

Run real code

โ€” browser runtimes and bounded server fixtures โ€” each route states what actually ran

Data structures

โ€” code it yourself, watch it move

Algorithms

โ€” specification โ†’ invariant โ†’ counterexample โ†’ proof transfer

Systems & reliability

โ€” watch the dynamics, not just the diagram
Idempotency / dedupsoon

dedup key, retry-safe writes

State machinelive โ†—

type transition rules as code โ†’ graph redraws live

Retry / Timeout / DLQsoon

backoff, jitter, poison โ†’ DLQ

Redissoon

cache-aside, TTL, stampede, hot key

Kafka / event-drivensoon

partitions, offsets, rebalance, lag

PostgreSQL tuning dojolive โ†—

predict B-tree key order โ†’ real EXPLAIN ANALYZE โ†’ defend plan and counterexample

API designsoon

resources, idempotency, versioning

Spring Request Lifecyclelive โ†—

follow one request through Spring, Hikari, JDBC, and PostgreSQL โ€” then move its work

Production pitfalls & load

โ€” watch it break as traffic grows, then fix it

API paradigms

โ€” really understand what each IS
RESTsoon

resources, verbs, status, statelessness

gRPCsoon

protobuf, HTTP/2 streams, codegen

GraphQLsoon

one graph, client-picked fields, N+1

Every route states whether its evidence is measured, calculated, modeled, or illustrative. Some slices complete prediction โ†’ change โ†’ evidence โ†’ defense/transfer; an interactive model alone is not presented as mastery proof.