How’s your workweek starting off? I slogged through a full inbox while navigating an array of meetings. Not sure about you, but I also find myself firing off various “explore this” questions to my AI agent, and then reading the answers in batches during free moments. That happened a couple times today.
[blog] What I believe about the future of software development. Buckle up. I can’t see many flaws in this position. But it likely represents a radical change to how you’re doing technology and software now.
[article] Runtime: Jev is an LLM without the LL. Wow, Jev was everywhere this past weekend. It doesn’t code or reason. Jev is for fast, structured decision making. More here too, and here.
[blog] The agents are coming for the web and the web isn’t ready. I’d imagine this isn’t just crawlers. It’s all of us using personal agents that helpfully go out (async) and try to get answers.
[article] Popular isn’t a business model. “Open source” isn’t a business model. You have to do something with it. Ben lists out six proven options here.
[blog] Scaling Golang CI by Replacing actions/setup-go. If you’re doing continuous integration with Go on GitHub Actions, there’s a smarter way.
[article] Navigating the Modern Data Lexicon: A Working Vocabulary for the Semantic Era. It’s easy to pick up tech jargon, and then realize you barely know what that term means. Hill climbing, anyone? Here are seven data-related terms that you might want to understand better.
[blog] Accelerating the borderless Lakehouse: Announcing preview of cross-cloud caching. All that cross-cloud data movement isn’t cheap. We just added some smart caching that dramatically reduces how much data leaves each source.
[article] Meta’s AI agent has been blocked from using Amazon.com. And Shopify responded with an integration into this personal agent. Those who embrace the agentic consumer will quickly surpass those who do not.
[blog] Scale your AI workloads faster and more efficiently with GKE Pod snapshots. Wow, this makes a massive difference. In the examples provided, inference start-up time is down by nearly 90%.
[blog] SaaS platforms are surging despite the SaaSpocalypse. Looks like SaaS is doing fine? Platforms can differentiate well, even better, in the AI era.
[article] Do engineers still need to understand how LLMs work? Can you skip the effort to learn the plumbing of LLMs? Just call the API and get back to work? Sebastian Raschka thinks it’s still worth a deeper look.
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