<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Software Architecture on MacWorks</title><link>https://macworks.dev/tags/software-architecture/</link><description>Recent content in Software Architecture on MacWorks</description><generator>Hugo</generator><language>en</language><atom:link href="https://macworks.dev/tags/software-architecture/index.xml" rel="self" type="application/rss+xml"/><item><title>2026-04-13</title><link>https://macworks.dev/docs/week/tech/tech-2026-04-13/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://macworks.dev/docs/week/tech/tech-2026-04-13/</guid><description>&lt;details&gt;
&lt;summary&gt;Sources&lt;/summary&gt;
&lt;div class="markdown-inner"&gt;
&lt;ul&gt;

&lt;li&gt;&lt;a href="https://medium.com/feed/airbnb-engineering"&gt;Airbnb Engineering&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://aws.amazon.com/blogs/machine-learning/feed/"&gt;Amazon AWS AI Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://aws.amazon.com/cn/blogs/architecture/feed/"&gt;AWS Architecture Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://aws.amazon.com/blogs/opensource/feed/"&gt;AWS Open Source Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://brett.trpstra.net/brettterpstra"&gt;BrettTerpstra.com&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blog.bytebytego.com/feed"&gt;ByteByteGo&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blog.cloudflare.com/rss/"&gt;CloudFlare&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://dropbox.tech/feed"&gt;Dropbox Tech Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://engineering.fb.com/feed/"&gt;Facebook Code&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://github.blog/engineering.atom"&gt;GitHub Engineering&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blog.google/innovation-and-ai/technology/ai/rss/"&gt;Google AI Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://deepmind.google/blog/rss.xml"&gt;Google DeepMind&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="http://feeds.feedburner.com/GoogleOpenSourceBlog"&gt;Google Open Source Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.hashicorp.com/blog/feed.xml"&gt;HashiCorp Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://feed.infoq.com/?token=XQ47eEiAJqUtN8043NhEqJ6kZB8XallO"&gt;InfoQ&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://engineering.atspotify.com/feed/"&gt;Spotify Engineering&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.microsoft.com/en-us/research/feed/"&gt;Microsoft Research&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://hacks.mozilla.org/feed/"&gt;Mozilla Hacks&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://netflixtechblog.com/feed"&gt;Netflix Tech Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="http://feeds.feedburner.com/nvidiablog"&gt;NVIDIA Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="http://feeds.feedburner.com/oreilly/radar/atom"&gt;O&amp;#39;Reilly Radar&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://openai.com/news/rss.xml"&gt;OpenAI Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://developers.soundcloud.com/blog/blog.rss"&gt;SoundCloud Backstage Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://stripe.com/blog/feed.rss"&gt;Stripe Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://rsshub.bestblogs.dev/deeplearning/the-batch"&gt;The Batch | DeepLearning.AI | AI News &amp;amp; Insights&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blog.dropbox.com/feed"&gt;The Dropbox Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://github.blog/feed/"&gt;The GitHub Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://medium.com/feed/netflix-techblog"&gt;The Netflix Tech Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blogs.microsoft.com/feed/"&gt;The Official Microsoft Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://vercel.com/atom"&gt;Vercel Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://engineeringblog.yelp.com/feed.xml"&gt;Yelp Engineering and Product Blog&lt;/a&gt;&lt;/li&gt;

&lt;/ul&gt;
&lt;/div&gt;
&lt;/details&gt;


&lt;h1 id="engineering--scale--2026-04-13"&gt;Engineering @ Scale — 2026-04-13&lt;a class="anchor" href="#engineering--scale--2026-04-13"&gt;#&lt;/a&gt;&lt;/h1&gt;
&lt;h2 id="signal-of-the-day"&gt;Signal of the Day&lt;a class="anchor" href="#signal-of-the-day"&gt;#&lt;/a&gt;&lt;/h2&gt;
&lt;p&gt;When using large language models for recommendation systems, passing raw numerical counts ruins the signal because the model processes digits as text tokens rather than magnitudes. By converting raw engagement counts into percentile buckets wrapped in special tokens (e.g., &lt;code&gt;&amp;lt;view_percentile&amp;gt;71&amp;lt;/view_percentile&amp;gt;&lt;/code&gt;), LinkedIn increased the correlation between popularity and embedding similarity 30x, offering a highly reusable pattern for safely encoding structured numerical data into transformer contexts.&lt;/p&gt;</description></item><item><title>Engineer Reads</title><link>https://macworks.dev/docs/week/blogs/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://macworks.dev/docs/week/blogs/</guid><description>&lt;h1 id="engineering-reads--week-of-2026-04-02-to-2026-04-10"&gt;Engineering Reads — Week of 2026-04-02 to 2026-04-10&lt;a class="anchor" href="#engineering-reads--week-of-2026-04-02-to-2026-04-10"&gt;#&lt;/a&gt;&lt;/h1&gt;
&lt;h2 id="week-in-review"&gt;Week in Review&lt;a class="anchor" href="#week-in-review"&gt;#&lt;/a&gt;&lt;/h2&gt;
&lt;p&gt;This week&amp;rsquo;s reading reflects a fundamental inflection point: raw LLM intelligence is no longer the bottleneck in software development. Instead, the industry is pivoting toward the hard systems engineering required to constrain probabilistic models—whether through strict data ledgers, living specifications, or formal verification harnesses. The dominant debate centers on how we preserve architectural taste, mechanical sympathy, and system ethics as the mechanical act of writing code becomes increasingly commoditized.&lt;/p&gt;</description></item><item><title>Tech Company Blogs</title><link>https://macworks.dev/docs/week/tech/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://macworks.dev/docs/week/tech/</guid><description>&lt;h1 id="engineering--scale--week-of-2026-04-03-to-2026-04-10"&gt;Engineering @ Scale — Week of 2026-04-03 to 2026-04-10&lt;a class="anchor" href="#engineering--scale--week-of-2026-04-03-to-2026-04-10"&gt;#&lt;/a&gt;&lt;/h1&gt;
&lt;h2 id="week-in-review"&gt;Week in Review&lt;a class="anchor" href="#week-in-review"&gt;#&lt;/a&gt;&lt;/h2&gt;
&lt;p&gt;This week, the industry rapidly shifted from conversational AI paradigms to formal &amp;ldquo;Agentic Infrastructure,&amp;rdquo; prioritizing strict deterministic guardrails over massive, unstructured context windows. Top organizations are aggressively fracturing monolithic processes—whether it is breaking down massive LLM prompts into specialized sub-agents, federating sprawling databases, or shifting compute-heavy security mitigation entirely to the network edge—to manage the unbounded scaling demands of machine actors.&lt;/p&gt;</description></item><item><title>2026-04-11</title><link>https://macworks.dev/docs/week/tech/tech-2026-04-11/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://macworks.dev/docs/week/tech/tech-2026-04-11/</guid><description>&lt;details&gt;
&lt;summary&gt;Sources&lt;/summary&gt;
&lt;div class="markdown-inner"&gt;
&lt;ul&gt;

&lt;li&gt;&lt;a href="https://medium.com/feed/airbnb-engineering"&gt;Airbnb Engineering&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://aws.amazon.com/blogs/machine-learning/feed/"&gt;Amazon AWS AI Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://aws.amazon.com/cn/blogs/architecture/feed/"&gt;AWS Architecture Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://aws.amazon.com/blogs/opensource/feed/"&gt;AWS Open Source Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://brett.trpstra.net/brettterpstra"&gt;BrettTerpstra.com&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blog.bytebytego.com/feed"&gt;ByteByteGo&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blog.cloudflare.com/rss/"&gt;CloudFlare&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://dropbox.tech/feed"&gt;Dropbox Tech Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://engineering.fb.com/feed/"&gt;Facebook Code&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://github.blog/engineering.atom"&gt;GitHub Engineering&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blog.google/innovation-and-ai/technology/ai/rss/"&gt;Google AI Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://deepmind.google/blog/rss.xml"&gt;Google DeepMind&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="http://feeds.feedburner.com/GoogleOpenSourceBlog"&gt;Google Open Source Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.hashicorp.com/blog/feed.xml"&gt;HashiCorp Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://feed.infoq.com/?token=XQ47eEiAJqUtN8043NhEqJ6kZB8XallO"&gt;InfoQ&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://engineering.atspotify.com/feed/"&gt;Spotify Engineering&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.microsoft.com/en-us/research/feed/"&gt;Microsoft Research&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://hacks.mozilla.org/feed/"&gt;Mozilla Hacks&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://netflixtechblog.com/feed"&gt;Netflix Tech Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="http://feeds.feedburner.com/nvidiablog"&gt;NVIDIA Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="http://feeds.feedburner.com/oreilly/radar/atom"&gt;O&amp;#39;Reilly Radar&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://openai.com/news/rss.xml"&gt;OpenAI Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://developers.soundcloud.com/blog/blog.rss"&gt;SoundCloud Backstage Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://stripe.com/blog/feed.rss"&gt;Stripe Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://rsshub.bestblogs.dev/deeplearning/the-batch"&gt;The Batch | DeepLearning.AI | AI News &amp;amp; Insights&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blog.dropbox.com/feed"&gt;The Dropbox Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://github.blog/feed/"&gt;The GitHub Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://medium.com/feed/netflix-techblog"&gt;The Netflix Tech Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blogs.microsoft.com/feed/"&gt;The Official Microsoft Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://vercel.com/atom"&gt;Vercel Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://engineeringblog.yelp.com/feed.xml"&gt;Yelp Engineering and Product Blog&lt;/a&gt;&lt;/li&gt;

&lt;/ul&gt;
&lt;/div&gt;
&lt;/details&gt;


&lt;h1 id="engineering--scale--2026-04-11"&gt;Engineering @ Scale — 2026-04-11&lt;a class="anchor" href="#engineering--scale--2026-04-11"&gt;#&lt;/a&gt;&lt;/h1&gt;
&lt;h2 id="signal-of-the-day"&gt;Signal of the Day&lt;a class="anchor" href="#signal-of-the-day"&gt;#&lt;/a&gt;&lt;/h2&gt;
&lt;p&gt;Moving bespoke internal logic to specialized infrastructure is a critical milestone for scaling platforms. Etsy&amp;rsquo;s migration of a 425 TB database off custom shard routing onto Vitess demonstrates how standardizing on mature orchestration layers unlocks dynamic resharding and operational flexibility without requiring massive application rewrites.&lt;/p&gt;</description></item><item><title>2026-04-09</title><link>https://macworks.dev/docs/week/blogs/engineer-blogs-2026-04-09/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://macworks.dev/docs/week/blogs/engineer-blogs-2026-04-09/</guid><description>&lt;h1 id="engineering-reads--2026-04-09"&gt;Engineering Reads — 2026-04-09&lt;a class="anchor" href="#engineering-reads--2026-04-09"&gt;#&lt;/a&gt;&lt;/h1&gt;
&lt;h2 id="the-big-idea"&gt;The Big Idea&lt;a class="anchor" href="#the-big-idea"&gt;#&lt;/a&gt;&lt;/h2&gt;
&lt;p&gt;AI is shifting the bottleneck of software engineering from writing syntax to exercising taste and defining specifications. Whether it&amp;rsquo;s iterating on high-level specs for autonomous agents, evaluating generated APIs, or ruthlessly discarding over-engineered platforms for boring architecture, the defining engineering skill is now human judgment, not raw keystrokes.&lt;/p&gt;
&lt;h2 id="deep-reads"&gt;Deep Reads&lt;a class="anchor" href="#deep-reads"&gt;#&lt;/a&gt;&lt;/h2&gt;
&lt;p&gt;&lt;strong&gt;&lt;a href="https://martinfowler.com/fragments/2026-04-09.html"&gt;Fragments: April 9&lt;/a&gt;&lt;/strong&gt; · Martin Fowler
Fowler&amp;rsquo;s fragment touches on several current events, but the technical meat lies in his analysis of Lalit Maganti&amp;rsquo;s attempt to build an SQLite parser using Claude. The core insight is that AI excels at generating code with objectively checkable answers, like passing test suites, but fails catastrophically at public API design because it fundamentally lacks &amp;ldquo;taste&amp;rdquo;. Maganti&amp;rsquo;s first AI-driven iteration produced complete spaghetti code; his successful second attempt relied heavily on continuous human-led refactoring and using the AI for targeted restructuring rather than blind generation. This exposes a critical tradeoff in the current AI era: coding agents can blast through long-standing architectural &amp;ldquo;todo piles,&amp;rdquo; but human engineers must remain tightly in the loop to judge whether an interface is actually pleasant to use. Engineers exploring AI-assisted development should read this to understand where to effectively deploy agents and where to stubbornly rely on their own architectural judgment.&lt;/p&gt;</description></item><item><title>2026-04-10</title><link>https://macworks.dev/docs/week/tech/tech-2026-04-10/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://macworks.dev/docs/week/tech/tech-2026-04-10/</guid><description>&lt;details&gt;
&lt;summary&gt;Sources&lt;/summary&gt;
&lt;div class="markdown-inner"&gt;
&lt;ul&gt;

&lt;li&gt;&lt;a href="https://medium.com/feed/airbnb-engineering"&gt;Airbnb Engineering&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://aws.amazon.com/blogs/machine-learning/feed/"&gt;Amazon AWS AI Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://aws.amazon.com/cn/blogs/architecture/feed/"&gt;AWS Architecture Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://aws.amazon.com/blogs/opensource/feed/"&gt;AWS Open Source Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://brett.trpstra.net/brettterpstra"&gt;BrettTerpstra.com&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blog.bytebytego.com/feed"&gt;ByteByteGo&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blog.cloudflare.com/rss/"&gt;CloudFlare&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://dropbox.tech/feed"&gt;Dropbox Tech Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://engineering.fb.com/feed/"&gt;Facebook Code&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://github.blog/engineering.atom"&gt;GitHub Engineering&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blog.google/innovation-and-ai/technology/ai/rss/"&gt;Google AI Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://deepmind.google/blog/rss.xml"&gt;Google DeepMind&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="http://feeds.feedburner.com/GoogleOpenSourceBlog"&gt;Google Open Source Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.hashicorp.com/blog/feed.xml"&gt;HashiCorp Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://feed.infoq.com/?token=XQ47eEiAJqUtN8043NhEqJ6kZB8XallO"&gt;InfoQ&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://engineering.atspotify.com/feed/"&gt;Spotify Engineering&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.microsoft.com/en-us/research/feed/"&gt;Microsoft Research&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://hacks.mozilla.org/feed/"&gt;Mozilla Hacks&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://netflixtechblog.com/feed"&gt;Netflix Tech Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="http://feeds.feedburner.com/nvidiablog"&gt;NVIDIA Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="http://feeds.feedburner.com/oreilly/radar/atom"&gt;O&amp;#39;Reilly Radar&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://openai.com/news/rss.xml"&gt;OpenAI Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://developers.soundcloud.com/blog/blog.rss"&gt;SoundCloud Backstage Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://stripe.com/blog/feed.rss"&gt;Stripe Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://rsshub.bestblogs.dev/deeplearning/the-batch"&gt;The Batch | DeepLearning.AI | AI News &amp;amp; Insights&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blog.dropbox.com/feed"&gt;The Dropbox Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://github.blog/feed/"&gt;The GitHub Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://medium.com/feed/netflix-techblog"&gt;The Netflix Tech Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blogs.microsoft.com/feed/"&gt;The Official Microsoft Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://vercel.com/atom"&gt;Vercel Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://engineeringblog.yelp.com/feed.xml"&gt;Yelp Engineering and Product Blog&lt;/a&gt;&lt;/li&gt;

&lt;/ul&gt;
&lt;/div&gt;
&lt;/details&gt;


&lt;h1 id="engineering--scale--2026-04-10"&gt;Engineering @ Scale — 2026-04-10&lt;a class="anchor" href="#engineering--scale--2026-04-10"&gt;#&lt;/a&gt;&lt;/h1&gt;
&lt;h2 id="signal-of-the-day"&gt;Signal of the Day&lt;a class="anchor" href="#signal-of-the-day"&gt;#&lt;/a&gt;&lt;/h2&gt;
&lt;p&gt;Cloudflare mitigates 31+ Tbps DDoS attacks without human intervention by distributing threat intelligence to every edge server via eBPF and XDP, entirely eliminating the need for centralized scrubbing centers and dropping malicious packets at the network interface before they consume a single cycle of application CPU.&lt;/p&gt;</description></item><item><title>2026-04-09</title><link>https://macworks.dev/docs/week/tech/tech-2026-04-09/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://macworks.dev/docs/week/tech/tech-2026-04-09/</guid><description>&lt;details&gt;
&lt;summary&gt;Sources&lt;/summary&gt;
&lt;div class="markdown-inner"&gt;
&lt;ul&gt;

&lt;li&gt;&lt;a href="https://medium.com/feed/airbnb-engineering"&gt;Airbnb Engineering&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://aws.amazon.com/blogs/machine-learning/feed/"&gt;Amazon AWS AI Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://aws.amazon.com/cn/blogs/architecture/feed/"&gt;AWS Architecture Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://aws.amazon.com/blogs/opensource/feed/"&gt;AWS Open Source Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://brett.trpstra.net/brettterpstra"&gt;BrettTerpstra.com&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blog.bytebytego.com/feed"&gt;ByteByteGo&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blog.cloudflare.com/rss/"&gt;CloudFlare&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://dropbox.tech/feed"&gt;Dropbox Tech Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://engineering.fb.com/feed/"&gt;Facebook Code&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://github.blog/engineering.atom"&gt;GitHub Engineering&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blog.google/innovation-and-ai/technology/ai/rss/"&gt;Google AI Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://deepmind.google/blog/rss.xml"&gt;Google DeepMind&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="http://feeds.feedburner.com/GoogleOpenSourceBlog"&gt;Google Open Source Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.hashicorp.com/blog/feed.xml"&gt;HashiCorp Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://feed.infoq.com/?token=XQ47eEiAJqUtN8043NhEqJ6kZB8XallO"&gt;InfoQ&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://engineering.atspotify.com/feed/"&gt;Spotify Engineering&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.microsoft.com/en-us/research/feed/"&gt;Microsoft Research&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://hacks.mozilla.org/feed/"&gt;Mozilla Hacks&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://netflixtechblog.com/feed"&gt;Netflix Tech Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="http://feeds.feedburner.com/nvidiablog"&gt;NVIDIA Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="http://feeds.feedburner.com/oreilly/radar/atom"&gt;O&amp;#39;Reilly Radar&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://openai.com/news/rss.xml"&gt;OpenAI Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://developers.soundcloud.com/blog/blog.rss"&gt;SoundCloud Backstage Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://stripe.com/blog/feed.rss"&gt;Stripe Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://rsshub.bestblogs.dev/deeplearning/the-batch"&gt;The Batch | DeepLearning.AI | AI News &amp;amp; Insights&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blog.dropbox.com/feed"&gt;The Dropbox Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://github.blog/feed/"&gt;The GitHub Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://medium.com/feed/netflix-techblog"&gt;The Netflix Tech Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blogs.microsoft.com/feed/"&gt;The Official Microsoft Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://vercel.com/atom"&gt;Vercel Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://engineeringblog.yelp.com/feed.xml"&gt;Yelp Engineering and Product Blog&lt;/a&gt;&lt;/li&gt;

&lt;/ul&gt;
&lt;/div&gt;
&lt;/details&gt;


&lt;h1 id="engineering--scale--2026-04-09"&gt;Engineering @ Scale — 2026-04-09&lt;a class="anchor" href="#engineering--scale--2026-04-09"&gt;#&lt;/a&gt;&lt;/h1&gt;
&lt;h2 id="signal-of-the-day"&gt;Signal of the Day&lt;a class="anchor" href="#signal-of-the-day"&gt;#&lt;/a&gt;&lt;/h2&gt;
&lt;p&gt;Meta&amp;rsquo;s escape from the WebRTC &amp;ldquo;forking trap&amp;rdquo; is a masterclass in modernizing massive legacy codebases without breaking billions of clients. By building a dual-stack architecture with automated C++ namespace rewriting and a dynamic shim layer, they managed to statically link two conflicting library versions, enabling safe, incremental A/B testing at an unprecedented scale.&lt;/p&gt;</description></item><item><title>2026-04-06</title><link>https://macworks.dev/docs/archives/tech/tech-2026-04-06/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://macworks.dev/docs/archives/tech/tech-2026-04-06/</guid><description>&lt;details&gt;
&lt;summary&gt;Sources&lt;/summary&gt;
&lt;div class="markdown-inner"&gt;
&lt;ul&gt;

&lt;li&gt;&lt;a href="https://medium.com/feed/airbnb-engineering"&gt;Airbnb Engineering&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://aws.amazon.com/blogs/machine-learning/feed/"&gt;Amazon AWS AI Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://aws.amazon.com/cn/blogs/architecture/feed/"&gt;AWS Architecture Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://aws.amazon.com/blogs/opensource/feed/"&gt;AWS Open Source Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://brett.trpstra.net/brettterpstra"&gt;BrettTerpstra.com&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blog.bytebytego.com/feed"&gt;ByteByteGo&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blog.cloudflare.com/rss/"&gt;CloudFlare&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://dropbox.tech/feed"&gt;Dropbox Tech Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://engineering.fb.com/feed/"&gt;Facebook Code&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://github.blog/engineering.atom"&gt;GitHub Engineering&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blog.google/innovation-and-ai/technology/ai/rss/"&gt;Google AI Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://deepmind.google/blog/rss.xml"&gt;Google DeepMind&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="http://feeds.feedburner.com/GoogleOpenSourceBlog"&gt;Google Open Source Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.hashicorp.com/blog/feed.xml"&gt;HashiCorp Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://feed.infoq.com/?token=XQ47eEiAJqUtN8043NhEqJ6kZB8XallO"&gt;InfoQ&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://engineering.atspotify.com/feed/"&gt;Spotify Engineering&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.microsoft.com/en-us/research/feed/"&gt;Microsoft Research&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://hacks.mozilla.org/feed/"&gt;Mozilla Hacks&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://netflixtechblog.com/feed"&gt;Netflix Tech Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="http://feeds.feedburner.com/nvidiablog"&gt;NVIDIA Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="http://feeds.feedburner.com/oreilly/radar/atom"&gt;O&amp;#39;Reilly Radar&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://openai.com/news/rss.xml"&gt;OpenAI Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://developers.soundcloud.com/blog/blog.rss"&gt;SoundCloud Backstage Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://stripe.com/blog/feed.rss"&gt;Stripe Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://rsshub.bestblogs.dev/deeplearning/the-batch"&gt;The Batch | DeepLearning.AI | AI News &amp;amp; Insights&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blog.dropbox.com/feed"&gt;The Dropbox Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://github.blog/feed/"&gt;The GitHub Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://medium.com/feed/netflix-techblog"&gt;The Netflix Tech Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blogs.microsoft.com/feed/"&gt;The Official Microsoft Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://vercel.com/atom"&gt;Vercel Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://engineeringblog.yelp.com/feed.xml"&gt;Yelp Engineering and Product Blog&lt;/a&gt;&lt;/li&gt;

&lt;/ul&gt;
&lt;/div&gt;
&lt;/details&gt;


&lt;h1 id="engineering--scale--2026-04-06"&gt;Engineering @ Scale — 2026-04-06&lt;a class="anchor" href="#engineering--scale--2026-04-06"&gt;#&lt;/a&gt;&lt;/h1&gt;
&lt;h2 id="signal-of-the-day"&gt;Signal of the Day&lt;a class="anchor" href="#signal-of-the-day"&gt;#&lt;/a&gt;&lt;/h2&gt;
&lt;p&gt;Meta flipped the AI assistant paradigm from runtime exploration to offline pre-computation, deploying a swarm of 50+ specialized agents to systematically map undocumented tribal knowledge into 1,000-token &amp;ldquo;compasses&amp;rdquo; — reducing agent tool calls by 40% and proving that rigidly structured context is far more valuable than massive token windows.&lt;/p&gt;</description></item><item><title>2026-04-06</title><link>https://macworks.dev/docs/archives/tech_news_cn/tech-news-cn-2026-04-06/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://macworks.dev/docs/archives/tech_news_cn/tech-news-cn-2026-04-06/</guid><description>&lt;h1 id="chinese-tech-daily--2026-04-06"&gt;Chinese Tech Daily — 2026-04-06&lt;a class="anchor" href="#chinese-tech-daily--2026-04-06"&gt;#&lt;/a&gt;&lt;/h1&gt;
&lt;h2 id="top-story"&gt;Top Story&lt;a class="anchor" href="#top-story"&gt;#&lt;/a&gt;&lt;/h2&gt;
&lt;p&gt;NetEase Youdao&amp;rsquo;s LobsterAI has successfully transitioned from an education-specific tool to a general-purpose AI assistant, gaining over 3,000 GitHub stars within a week of its open-source release. The 24/7 autonomous agent stands out by anticipating industry trends like the integration of a robust Skills system, cron-based task scheduling, and mobile remote control. This rapid pivot highlights the Chinese tech ecosystem&amp;rsquo;s aggressive push toward pragmatic, agentic AI solutions for non-technical office workers.&lt;/p&gt;</description></item><item><title>中文科技资讯</title><link>https://macworks.dev/docs/week/tech_news_cn/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://macworks.dev/docs/week/tech_news_cn/</guid><description>&lt;h1 id="chinese-tech--week-of-2026-04-04-to-2026-04-10"&gt;Chinese Tech — Week of 2026-04-04 to 2026-04-10&lt;a class="anchor" href="#chinese-tech--week-of-2026-04-04-to-2026-04-10"&gt;#&lt;/a&gt;&lt;/h1&gt;
&lt;h2 id="week-in-review"&gt;Week in Review&lt;a class="anchor" href="#week-in-review"&gt;#&lt;/a&gt;&lt;/h2&gt;
&lt;p&gt;This week, the Chinese tech ecosystem was dominated by the rapid maturation of &amp;ldquo;Agentic AI&amp;rdquo; workflows and the friction they cause across traditional infrastructure and business models. From the explosion of &amp;ldquo;vibe coding&amp;rdquo; apps reshaping software creation to severe open-source security breaches, the industry is grappling with both the democratization of tech and its escalating vulnerabilities. Concurrently, domestic Chinese models achieved massive breakthroughs in coding and video generation, signaling a highly competitive global landscape that no longer relies solely on Western foundational models.&lt;/p&gt;</description></item></channel></rss>