 A couple of weeks ago, my phone lit up from a group chat started by our editor-in-chief to survey the team on the consensus from the 500 CEOs, cabinet members, and other leaders we hosted at the Semafor World Economy in Washington, DC. Equally exhausted and energized from a supernova of high-level conversations, I had the sinking feeling our takeaways were skewed by adrenaline and vibes. There was a better way to do this. None of us had listened to all the interviews with more than 300 people who joined us on stage, let alone had the time to categorize every statement to get a true sense of the consensus. So, between shuttling my kids to hockey practices and birthday parties, I tapped Codex, OpenAI’s Mac app. Within an hour, I had a prototype of insights outlining who agreed with what — and who disagreed. “Government-funded worker training programs and even higher education don’t know the skills needed for today and tomorrow,” it quoted former Commerce Secretary Gina Raimondo saying, adding a thumbnail photo of her scraped from the web and telling me how the quote fit into a prevailing view that AI’s workforce transition would lag the technology shift. Just for fun, I tacked on a chat feature to the corpus of insights and sent it around to colleagues. “Wow Reed, this is gold,” texted Semafor CEO Justin B. Smith. Within minutes, we spun up a Slack channel where nearly a dozen people began turning the prototype I built into a real editorial product. Data lead Alastair Clements honed the underlying technology (you can read about his effort here) and product head Kellen Henry mocked up designs. The result: Semafor Intelligence, nine views distilled from the entire corpus of nearly 5,000 claims made across three stages over five days. This process was exhilarating, and not just because it highlighted how quickly Semafor’s team of tireless, talented people can spring into action when they spot an opportunity. The exercise was valuable because it gave me a chance to experience first-hand the AI wave I’ve been writing about almost since the day Semafor launched. It also validated some of my long-held contrarian views that AI will not make software engineers disappear. That the technology creates more demand for that skill, not less. By lowering the friction of building software, it becomes feasible to dream up more ideas and ship even more software. The better AI gets at building end-to-end programs, the more it encourages developers to build ever-complex and ambitious things. Launching Semafor Intelligence meant more work for humans across every department. Journalists had to distill the views offered up by the AI tool, gut-check the reporting and edit the words. Designers, marketers, and communications colleagues had to design, package and pitch the product. Now that we have a software backbone for something that can live and grow, the product will no doubt become more valuable over time and will probably result in us hiring more people — not fewer. For those of you who say, “in a year the technology will be so good that it won’t require any people to churn out Semafor Intelligence,” I hope you’re right. Because all of us here at Semafor have at least five other great ideas in the hopper we want to turn into reality. | 
