Today in News History

On June 17, several notable moments in the history of News stand out. In 1885, The Statue of Liberty arrives in New York Harbor. In 1932, Derek Ibbotson, English runner (died 2017) was born. In 1951, Starhawk, American author and activist was born. In 1959, Carol Anderson, American author and historian was born. In 1960, Adrián Campos, Spanish race car driver (died 2021) was born. In 1978, Isabelle Delobel, French ice dancer was born. In 1980, Jeph Jacques, American author and illustrator was born. In 1994, Amari Cooper, American football player was born. In 1996, Thomas Kuhn, American historian and philosopher (born 1922) passed away. In 2013, Michael Baigent, New Zealand-English theorist and author (born 1948) passed away. Together, these milestones provide historical context for today's news news and ongoing narratives.

How we learned to stop worrying* and love the autonomous future

Fast Company

Fast Company

·

June 17, 2026

·

lean left
Narrative Analysis: Glittering Generalities
How we learned to stop worrying* and love the autonomous future

If one thing’s true about this moment in tech history, it’s that as soon as you think you’re keeping pace with the leading edge of AI—poof!—the edge moves. This is a perennial anxiety, but I’ve never heard tech insiders so vocal about it. It came up constantly as we spoke to CEOs, founders, investors, and analysts while assembling this special issue on the new age of autonomy. “Every couple of months, we see such massive changes that it’s impossible to predict what’s going to happen on what timeline. We’re planning by the seat of our pants.” —Neel Ajjarapu, product lead for commerce, OpenAI “Where Moore’s law doubled computing power every two years, the Time Horizon law is doubling cognitive reach every four months.” —Azeem Azhar, founder, Exponential View, referring to a useful way of looking at the dizzying evolution of AI agents “AI is moving so quickly that the state of the art changes every three months.” —Sonya Huang, partner, Sequoia Capital Because the print edition of Fast Company comes out quarterly, we have an advantage: We are forced to take a longer view and do what Fast Company does best—look around corners. Turns out, there’s a lot to see. Our cover subject, Fei-Fei Li, a household name in AI circles, is building her new company on world models, a newer kind of artificial intelligence beyond large language models (LLMs). Uber’s CEO, Dara Khosrowshahi, is taking a victory lap for reaching profitability while preparing for the existential threat (and opportunities) posed by autonomous vehicles. And as senior staff writer Liz Segran learned when she asked robots to find her the perfect dress, agentic shopping has enormous potential but a long way to go. Those stories will prep you for the next wave of AI, and maybe the one after that. In the meantime, there’s plenty in this issue to prep you for right now: a roundup of all the agentic AI tools and resources you should already be using, by global technology editor Harry McCracken; an essay by Azhar, an agentic AI power user who might also be a canary in the coal mine; and our third annual AI 20, a list of humans driving this technology forward. If there’s another thing that’s true about this fast-moving moment in tech, it’s that there will always be a tool that’s slightly better (or slightly worse) than the one you’re using. What matters is the framework your company adopts to help it make decisions about which tools to embrace, how to integrate them into workflows, and how to pivot to something new when the time is right. “The real challenge isn’t just technical, it’s organizational,” says Shiv Rao, the CEO of Abridge, an AI platform that automates note-taking and clinical documentation for physicians. Sounds like a prescription for business leaders everywhere. *At least a little bit.

Narrative Intelligence Brief

This article was published by Fast Company, a source frequently categorized with a lean left bias based in United States of America. Our narrative intelligence engine continuously monitors coverage from this outlet to track framing, bias, and rhetorical patterns. In this specific piece, our systems detected the potential use of the "Glittering Generalities" technique. This narrative approach is often used to shape reader perception by highlighting specific emotional or rhetorical angles. By understanding the editorial perspective of Fast Company, readers can better contextualize the information presented and compare it across our broader media matrix to find the real narrative.

Reliability Insights

P

Technique: Glittering Generalities
System analysis detected use of specific narrative techniques in this piece.
Analysis Methodology
This narrative analysis was generated using the CoDataLab Global Intelligence Engine. Our proprietary AI scans thousands of cross-border sources to identify sentiment patterns, framing techniques, and potential media bias. While AI provides the data-driven foundation, our objective is to empower readers with additional context beyond the standard headline.The content displayed above is a structured summary designed for rapid information processing. For the full original report, please visit the source outlet.