State of the software engineering jobs market, 2025: what hiring managers see
Pretty much what I imagined about why cold-applying to job isn’t working anymore.
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How Airbnb Runs Distributed Databases on Kubernetes at Scale
Distributed SQL databases are not magic boxes that will handle availability and reliability challenges without thoughtful engineering. Airbnb’s case study is a great example of such engineering: don’t let more than one node replacement run at a time (serialized replacement controlled by custom k8s controller logic), spread a database across data centers (AWS availability zones), and don’t store data on the same node as DB server (detachable AWS EBS volumes).
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- YouTube
As a long-time developer, I can completely related to CJ’s rants against AI coding tools. Are they really making us 10x productive when we have to spend a non-trivial amount of time understanding, reviewing, re-prompting, and fixing AI generated code?
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An Engineer's Guide To Cultivating Confidence
If there’s only one thing I am taking away from this article, it is to reverse the feeling-action order. Instead of waiting to feel confident before taking action, I’m going to take action to feel confident. Also love the 10% technique—overprepare for the critical 10% part for a confidence boost early on.
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Python, Go, Rust, TypeScript and AI with Armin Ronacher
Choice of a language doesn’t always have to be based on performance or familiarity. Often it’s influenced by problem space (aka the core task) - suitability and ecosystem. Also, it’s always intriguing to hear a pragmatic take on AI coding from a once hater of the paradigm. AI agents are great at bootstrapping and doing the legwork, but we’ll always need humans to be fully in control (and for the emotions).
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Why Anthropic’s MCP is a Big Deal
The deep dive into how a request travels across the MCP stack and how a response is transported back is the best damn example I’ve ever read about how MCPs work.
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How Grab’s Migration from Go to Rust Cut Costs by 70%
The correlation (or the lack of) between speed/latency and efficiency in the conclusion is confusing. Ideally, more efficient systems should offer better speeds with similar resources. Is the mentioned efficiency expressed purely in terms of scalability? Can someone enlighten me?
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The RAG Obituary: Killed by Agents, Buried by Context Windows
Great historical context about a key problem RAG was designed to solve and why there is a better solution now in agentic search - thanks to huge context windows in today’s LLMs. It’s also fascinating to learn how Claude Code cleverly uses decades-old filesystem tools to perform lightning fast navigation and regex searches without needing some sort of indexing.
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Your Ambition Is Not Enough
Validates my long-held belief about the dangers of hero culture our society idealizes. Behind every successful individual is a team - family, friends, mentors. Not only is it unfair to attribute all success to one person, it sets a false expectation about how you can replicate that success.
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How Claude Code is built
TIL React is no longer limited to UIs for the web and mobile. Claude Code (and several other agentic CLI tools) use React for command-line UIs, whatever UI means in that context. See https://term.ink/.