1. **Analyze the Request:** * **Role:** News summarization expert. * **Task:** Summarize the provided article. * **Constraints:** * Concise. * 2-4 sentences. * Focus on the most important information. * DO NOT copy and paste. * DO NOT simply restate the title (add new info). * Answer in English. * **Input:** * Title: "Chasing the AI High: Clay, Kilns, and the Red Queen's Race" * Source: hackernews * Article Text: (The user provided the title, but the *text* appears to be missing or effectively cut off after the title in the prompt "Article Text: Chasing the AI High: Clay, Kilns, and the Red Queen's Race". Wait, looking closely at the prompt... the "Article Text" section just repeats the title and a "Summary:" heading. There is no actual body text provided.) 2. **Identify the Problem:** * The user has provided the *title* of a Hacker News article (likely a blog post submission), but has not provided the *content* of the article itself. * The prompt says "Article Text: [Title again] \n Summary:". * Without the actual article text, I cannot summarize it based on specific details, nor can I "add new information beyond the title." 3. **Determine the Strategy:** * *Hypothesis 1:* The user pasted the title thinking it was the text. * *Hypothesis 2:* The user made a mistake and didn't paste the full text. * *Hypothesis 3:* The user expects me to know this specific article because it's on Hacker News and I have
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Now, here, you see, it takes all the running you can do, to keep in the same place. If you want to get somewhere else, you must run at least twice as fast as that! - Red Queen, Through the Looking Glass, Lewis Carrol Cue up The Times They Are a-Changin'. The text predictor machines have begun predicting very valuable text. So valuable now that we think we don't need the inputters to the predictors. We just might have created the perpetual product machine of the future. Blessed be the generative transformers. Chasing the AI High At this point, I think a lot of us in the software industry have come across someone who finally got around to trying out an LLM coding agent to suddenly become obsessed with running multiple agents as close to 24/7 as possible. Some, we might even say, have succumbed to AI psychosis. They're convinced by the transformative nature of AI and that we will die out if we don't adopt it full force. As time goes on though, it seems like no amount of productivity feels sufficient. Why work with one agent at a time? Let's have dozens! Hundreds, hell why not thousands of agents! Destroy the backlog! Create agents to fill the backlog! Let the customers fill the backlog! No more tickets, just prompts. Speed up! Faster! Faster! Some people are more susceptible than others to become addicted to things. Designing and writing software was something that could be very challenging and tedious at times. So challenging and tedious that we created entire systems for how we would approach the process of writing said software. Waterfall, agile, scrum, Extreme Programming, all different ways just to coordinate how we could collectively build the things. So no wonder that when something comes along that blows that all up and allows individuals to Ralph Loop the backlog into a state that you might be able to interact with it, you immediately start worrying that you've run out of things to build. Your productivity high is coming down and you don't want to crash. You need to keep this going, you need to put more things in the backlog. The Red Queen's Race The AI induced anxiety sets in and you're worried about your agents and your loops and whether they got stuck or you need to adjust them. Any time tokens aren't flying is time lost, productivity down. You're a 10x, nay 100x engineer now, so one hour lost is actually a thousand hours lost! It might be too late now though, as you're already Through the Looking Glass. There certainly feels as though there are some interesting parallels in the themes of Through the Looking Glass (like how software engineers are Alice grieving the end of their childhood, thanks to AI), but I like to focus on the Red Queen's Race. This take was initially inspired by reading The Red Queen problem and the issues that arise in measuring scientific progress in the advent of AI. Nicklas Lundblad and Dorothy Chou articulated in the article that some crude approaches to measuring of scientific progress could be looking at the number of patents obtained, papers published, or funding in a certain area. Each one of these falls wildly short for various reasons, but most of it has to do with muddied or misguided signals/incentives tied to them. This crude measurement issue became more pertinent as my previous company got particularly interested in the number of PRs that software engineers were shipping every week. Many of us internally pointed to Goodhart's Law, which as you can imagine, didn't do shit because that would make leadership look like they were wrong for using a metric as a goal. I want to zoom out from this a little bit though, as Lundblad and Chou did regarding scientific process. Basically all of us have access to frontier models. All of us should be capable of prompting the models or integrating with them in similarly sufficient ways (only the fool thinks they have some kind of prompting edge). It suddenly seems that because our competitors can use AI to build faster, we must use AI to build faster, but that also means that we must move a LOT faster just to stay competitive. Now we're running in the Red Queen's Race. But so what? We have the models to help us run faster. The problem becomes complexity and entropy. Everyone is grabbing AI and running the fastest race they can, not even thinking about running a marathon. Your codebase is growing faster than your team can comprehend it (even with AI). You want to believe that you can eventually declare bankruptcy and rebuild it all over again with the next smartest model. Again, this is being in the throes of addiction. Believing that next hit will make things better, but you're just trying to avoid coming down. Building With Clay but No Kiln AI built software is clay. Incredibly responsive, fast to shape, you can model something recognizable in minutes. That's genuinely powerful and not something to dismiss, because clay is useful for figuring out what you want to build or how you want something to look. But clay that never goes