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GitHub - ccfos/nightingale: Nightingale for monitoring and alerting, just as Grafana for visualization. github.com/ccfos/nighti... Nightingale is an open-source monitoring project that focuses on alerting. Similar to Grafana, Nightingale also connects with various data sources.

Excited to be delivering Embrace feature flags, unlock better customer experience and developer confidence - webdirections.org/dev-summit/s... Learn more at webdirections.org/dev-summit', and hope to see you there! #devSummit #publicSpeaking #featureFlags #simplyWallSt

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How to Give a Good Talk blog.sigplan.org/2025/03/31/h... A good talk meets the audience in the middle. It informs the audience what the value proposition is; it educates them, offering some new teaching; it entertains them.

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If you want to tell a story about Nepal, here are 192K+ news headlines in English from multiple Nepalese and international sources for the past 5 years (since mid 2021) - github.com/geshan/nepal... With Docker + two commands and some SQL, you can analyze a lot of data and link to full news posts

Why retention is so hard for new tech products andrewchen.substack.com/p/lessons-le... Starting with the end in mind is also important when selecting a category and building products within it, with retention in mind.

Quiet Influence: A Guide to Nemawashi in Engineering - Matthew Hodgkins hodgkins.io/blog/quiet-i... Now that you’ve done all the hard work, the final meeting should be a formality. You are no longer “revealing” a big idea, you are confirming a decision that has already been made...

Build Places, Not Products every.to/source-code/... Why software shouldn’t just work—it should feel like somewhere you want to stay

Cloud Run Jobs: A Beginner's Guide to Running Tasks to Completion on a schedule

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AI Insights | Cloudflare Radar radar.cloudflare.com/ai-insights AI bots scan public websites to collect data used in search engines, AI model training, and other data processing tasks

The story of how RSS beat Microsoft buttondown.com/blog/rss-vs-... All RSS had to do to weather ICE, Twitter, AI, and whatever comes next, was keep things simple and let users build their own feeds, filters, lists, and aggregators.

Where's the Shovelware? Why AI Coding Claims Don't Add Up mikelovesrobots.substack.com/p/wheres-the... In that study, the authors discovered that developers were unreliable narrators of their own productivity. They thought AI was making them 20% faster, but it was actually making them 19% slower.

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The babysitter problem - chrisbeckman.dev chrisbeckman.dev/posts/the-ba... This experiment made me think about a bigger risk: turning senior developers into babysitters for junior-level AI. LLMs can be clever, but easy doesn’t always mean fast.

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