A practitioner's guide to getting more value out of AI coding: agent quality & token optimization
A practitioner's guide to getting more value out of AI coding agents — drawn from a GitHub workshop on agent quality and token cost optimization.
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A practitioner's guide to getting more value out of AI coding agents — drawn from a GitHub workshop on agent quality and token cost optimization.
A couple of months ago I made the zig parts of my game’s codebase hot reloadable. A few people have asked me about challenges and issues with doing that, so I wrote a blog post about it. Not a how-to tutorial, but rather “this is what I did”. Hoping it will be useful to someone trying to do the same thing :) submitted by /u/unvestigate [link] [留言]
Sergiu Petean discusses the strategic journey of evolving DevOps into platform engineering within heavily regulated enterprise environments. He explains how to maximize efficiency using dynamic reference architectures, align platform KPIs directly with board-level business goals, reduce cognitive load via custom team topologies, and maintain innovation sovereignty through open-source technology. By Sergiu Petean
Over the weekend, I attended an event hosted by Cursor Kenya, bringing together developers, builders,...
Cake is still welcome. submitted by /u/Adept_Signature3352 [link] [留言]
Introduction Last week I was at Vueconf US. It's one of my favorite conferences and I try...
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I've had 3 weeks off work and I've used the time to rekindle my passion for coding (the old way, by hand). Stumbled upon this alternative to consistent hashing called rendezvous hashing (or highest random weight) and did a little deep dive. It ended up turning into a basic library, including the basic algorithm, a couple of variations, and the skeleton pattern for O(log n) access. It performs similar to ExHashRing for node counts <20, and with the skeleton optimization is competitive even in the tens of thousands of nodes, but it uses no NIFs or stateful processes, and the basic algorithm is essentially a one-liner. Anyway, it was fun to learn about, hope you enjoy it too! https://jola.dev/posts/highest-random-weight-in-elixir submitted by /u/joladev [link] [留言]
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submitted by /u/imbev [link] [留言]
Travel back to 1998 and use Lovable on Windows 98 Discussion | Link
After temporarily banning LLM-related content over April , and asking you for feedback on that ban , we've decided to bring about an end of the temporary, I-can't-believe-it's-still-April ban on AI-related posts. Replacing the trial rule is a new shiny rule that refers to our new shiny AI policy . In short: Content about AI and LLMs are considered off-topic with the sole exclusion of deeply technical content about implementation. And if you want more detail than that, go read the policy, that's what it's there for. In addition, when writing that rule, I realized the rules weren't listed on the old.reddit.com sidebar, so that's been updated. For those of you who are seeing those rules for the first time, everything there is not new. We've been enforcing those rules as best we can for ages. You can click the link above those to get to the old.reddit rules page, with plenty of info that doesn't exactly read well when crammed into a sidebar. submitted by /u/ChemicalRascal [link] [留言]