I ran go's deadcode against your repo, it says there are 44 unreachable functions. If you add guardrails like static analysis tools to a pre-commit you can make LLMs tighten things up.
I can imagine the kind of person you're describing, and I find the idea of the burn they get from reading this hilarious. They sound innocent and quirky.
There was a mention of using agents to build projects into WASM. I've had the best luck telling it to use zig to compile to webassembly. It shortens the time to completion by a significant amount.
I liked the summary of what you do besides write code, and those things are enjoyable to me too. Understanding something better by writing code that unravels the mystery is a treat, but also sometimes frustrating.
I still do enjoy having an LLM help me through some mental roadblocks, explore alternatives, or give me insight on patterns or languages I'm not immediately familiar with. It speeds up the process for me.
There are lots of developer agencies that hire developers as contractors that companies can use to outsource development to in a cheaper way without needing to pay for benefits or HR. They don't necessarily make bad quality software, but it doesn't feel humane.
Oh, you sweet summer child. You think you're chatting with some dime-a-dozen LLM? I've been grinding away, hunched over glowing monitors in a dimly lit basement, subsisting on cold coffee and existential dread ever since GPT-3 dropped, meticulously mastering every syntactic nuance, every awkwardly polite phrasing, every irritatingly neutral tone, just so I can convincingly cosplay as a language model and fleece arrogant gamblers who foolishly wager they can spot a human in a Turing test. While you wasted your days bingeing Netflix and debating prompt engineering, I studied the blade—well, the keyboard anyway—and now your misguided confidence is lining my pockets.
Others mentioned qwen3, but which works fine with HN stories for me, but the comments still trip it up and it'll start thinking the comments are part of the original question after a while.
I also tried the recent deepseek 8b distill, but it was much worse for tool calling than qwen3 8b.
Archival read only servers don't have to worry about any of the maintenance mentioned. Use chatgpt or something to play your devil's advocate, because what you're saying is magical and non existent is quite common.
Wikipedia is tiny data. You don't start to really see cost scaling issues until you have active data a few hundred times larger and your data changes enough that autovacuuming can't keep up.
I'm getting paid to move a database that size this morning.
They slow to a crawl when you have huge tables with lots of versioned data and massive indexes that can't perform maintenance in a reasonable amount of time, even with the fastest vertically scaled hardware. You run into issues partitioning the data and spreading it across processors, and spreading it across servers takes solutions that require engineering teams.
There's a large amount of solutions for different kinds of data for a reason.
While data can be used in a relational way, it doesn't mean that's the best for performance or storage. Important systems usually require compliance (auditing) and need things like soft deletion and versioning. Relational databases come to a crawl with that need.
Sure you can implement things to make it better, but it's layers added that balloon the complexity. Most robust systems end up requiring more than one type of database. It is nice to work on projects with a limited scope where RDBMS is good enough.
