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A developer shares their journey learning Go concurrency by building a CLI tool to count code statistics. Starting with a simple sequential implementation, they added goroutines for parallelism but accidentally created unbounded concurrency that overwhelmed their system. After implementing a semaphore-based thread pool and fixing deadlock issues, they achieved a 10x speedup on the Linux kernel codebase, with optimal performance at 50-100 workers. The experience taught practical lessons about resource limits, correctness, and ownership in concurrent systems.

From Naive Go to Thread Pools: A Tiny CLI That Taught Me Concurrency

A supportive squad for Go developers who want to dive deeper into what makes Go special. We focus on the language's clean simplicity, powerful concurrency, and reliable performance.