<p>Most developers spent 2023 and 2024 experimenting with AI-assisted code completion and chat interfaces. Those tools were useful—but they were also passive. You typed a prompt.
<p>I still remember the exact moment.</p> <p>It was 11pm. My team had been sprinting for 3 weeks building <br /> a new payments feature. Deadline tomorrow. I handed the final <br
<p><em>The AWS Reliability Files, Part 1</em></p> <p>I told an AI a true fact about AWS. Then I had a second AI confidently insist it was wrong. Within one exchange, the first
<p>You've heard of DevOps. You've heard of AIOps. You've probably heard of MLOps.</p> <p>But there's a category that doesn't exist yet — and it's the one the AI industry needs
<p>Your AI system isn't going to crash. It's going to drift.</p> <p>A recommendation engine making 1.4 model calls instead of 1. A retrieval pipeline fetching 5 chunks instead of
<p>Even the most advanced enterprise systems are tethered to a costly paradox: manual bottlenecks that introduce critical errors, security risks, and slow innovation. These hidden
<p>Originally published in <a
<!-- SC_OFF --><div class="md"><p>I am curious how non-coders are currently using frontier ai models and capabilities. Specifically in technical fields.</p> <p>I am a mechanical
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