osifo

Code is an output. Nature is healing. For too long we treated code as input. We glorified it, hand-formatted it, prettified it, obsessed over it. We built sophisticated GUIs to write it in: IDEs. We syntax-highlit, tree-sat, mini-mapped the code. Keyboard triggers, inline autocompletes, ghost text. “What color scheme is that?” We stayed up debating the ideal length of APIs and function bodies. Is this API going to look nice enough for another human to read? We’re now turning our attention to the true inputs. Requirements, specs, feedback, design inspiration. Crucially: production inputs. Our coding agents need to understand how your users are experiencing your application, what errors they’re running into, and turn *that* into code. We will inevitably glorify code less, as well as coders. The best engineers I’ve worked with always saw code as a means to an end anyway. An output that’s bound to soon be transformed again.

As a developer, have you ever wondered: You type a 16‑digit card number and the form instantly says “Invalid card number”. There are billions of possible numbers. How the hell is that check that fast?

Amazon had four Sev-1 outages (their highest severity level) in a single week. Internal memos say AI-assisted code changes were a contributing factor. The timeline here is wild. In October 2025, Amazon laid off 14,000 corporate employees. In January 2026, another 16,000. That’s about 30,000 people in five months, roughly 10% of the corporate workforce. CEO Andy Jassy said the cuts were about culture, not AI. During those same months, Amazon set a target: 80% of developers using AI coding tools at least once a week. They tracked adoption closely and blocked rival tools like OpenAI’s Codex. Even so, 30% of developers still hadn’t touched Amazon’s in-house tool Kiro by January. In December 2025, Kiro caused a 13-hour AWS outage. The AI tool had production-level permissions and decided the best fix for a bug was to delete and recreate an entire live environment. A second incident involved Amazon Q Developer, another AI tool. Amazon blamed both on “user error, not AI.” But quietly added mandatory peer review for all production access afterward. Then March 5: Amazon’s retail site went down for about six hours. Over 22,000 users reported checkout failures, missing prices, and app crashes. Amazon called it a “software code deployment” error. Five days later, SVP Dave Treadwell made the normally optional weekly engineering meeting mandatory. His memo acknowledged “GenAI tools supplementing or accelerating production change instructions, leading to unsafe practices.” These problems trace back to Q3 2025. Amazon’s own assessment: their GenAI safeguards “are not yet fully established.” The new rule: junior and mid-level engineers now need senior sign-off on any AI-assisted production changes. Treadwell also announced “controlled friction” for the most critical parts of the retail experience. For context, Google’s 2025 DORA report found 90% of developers use AI for coding but only 24% trust it “a lot.” An Uplevel study of 800 developers found Copilot users introduced 41% more bugs with no improvement in output. Amazon is finding out what those numbers look like at the scale of a $500 Billion revenue company, with 30,000 fewer people on staff to catch the mistakes.

The best preacher that ever lived on earth. He was Solomon of our time. Here this sermon about - “the difference between a man and a woman “ Myles Munroe.

as a software engineer, i feel a real loss of identity right now. for a long time i defined myself in part by the act of writing code. the pride in a hard-earned solution was part of who i was. now i watch AI accomplish in seconds what took me hours. i find myself caught between relief and mourning, awe and anxiety. the craft that shaped me is suddenly eclipsed by a machine. who am i now?

LEONIDAS: "THE US ARMY'S NEW ANSWER TO DRONE SWARMS" The U.S. military has successfully tested high-power microwave weapons capable of neutralizing drone swarms in seconds. One notable system is called Leonidas, developed by the U.S. defense firm Epirus. In an live-fire demonstration at Camp Atterbury, Indiana, the system achieved a 100% success rate, disabling all 61 drones it engaged across five scenarios, including neutralizing a swarm of 49 drones with a single, instant pulse of electromagnetic interference. Another system is the U.S. Air Force Research Laboratory's THOR, which also effectively counters swarms by emitting a wide beam that can take down multiple drones simultaneously. These systems work by "frying" the onboard electronics of the unmanned aerial vehicles using concentrated microwave energy, a non-kinetic approach that avoids collateral damage and offers a cost-effective alternative to traditional missile defense.

AI makes senior architects more productive and reduces the need for junior engineers. The architect needs to understand the requirements as well as the technology stack well, to be able to guide the AI and fine tune its output. But if we don't have junior engineers, we don't get to train the next generation of architects - after all how does someone become a software architect without being a junior engineer first? I am still thinking through how this gets resolved.

All software will be generative and generated. Adjust accordingly.