Competent Jerks Lose: Why Teams Pick the Lovable Fool
A Harvard Business Review study of 10,000 work relationships found that people prefer the lovable fool to the competent jerk. Here is what that choice costs your innovation, and how to fix it.
A Harvard Business Review study of 10,000 work relationships found that people prefer the lovable fool to the competent jerk. Here is what that choice costs your innovation, and how to fix it.
May 10, 1954, Dayton. Experts say a silicon transistor is years away. Gordon Teal dips an amplifier into hot oil and the music keeps playing. An innovation story about the gap between inventing something and bringing it to market.
Robots can handle 34% of U.S. working hours, yet they are profitable for only 0.3% of tasks. Why the gap is so wide, what Anthropic’s study is really worth, and how to run the numbers in your own company before you buy.
Wearable brain-computer interfaces could go mainstream in 5 to 10 years, under one condition most articles will skip: fund the evidence, not the gadget. Here is what leaders should demand before equipping their teams.
Capote anglaise on one side, French letter on the other: each nation pins the condom on its neighbor. From the Minos myth to Falloppio’s 1564 treatise, here is the documented history of its invention, and what it reveals about how we handle uncomfortable topics.
A New Mexico jury found 26 of Meta’s 29 statements misleading. The result: $25 billion. How many of your data promises would survive a jury?
Disney is offering $20 million to license technology from bankrupt Character.AI and is hiring most of its staff. The deal shows how large companies buy innovation once someone else has paid for the risk.
Word, Excel and PowerPoint rebuilt by a single developer with Claude, a reverse engineering tool with 270,000 GitHub stars: cloning software has never been easier. What European and US law actually allow, and a five-step method before you start.
83% of companies make innovation a priority, yet only 3% are ready to innovate. An innovation culture assessment shows your executive team where to act first. Discover the QIIO and join our webinar.
Three air mattresses, three strangers, $80 a night. What the Airbnb story really teaches you about finding your first customers online.
With $50 and a workshop ritual nobody noticed anymore, Blendtec launched Will It Blend? in 2006. What this story teaches about marketing innovation, and what its numbers don’t prove.
Microsoft’s 2026 Work Trend Index links AI’s impact more to organizations than to individual skills. In France, only 20% of users see their leadership as aligned. A critical reading of a useful report, and what leaders can change on Monday morning.
One letter separates the HiPo, your high potential, from the HiPPO, the best-paid opinion that crushes your decisions. Here is how to spot the beast and tame it through process.
A company sells AI models with the guardrails removed. Here is why the real danger is human before it is technical, and the three moves an executive should make.
A 27-year-old engineer quits Anthropic, his AI warning tops 57 million views, and panic spreads through teams. Here is what a leader should actually do.
IKEA handed almost half of its customer requests to its AI Billie without cutting a single one of those 8,500 jobs. By training them as remote design advisors, the retailer created over a billion euros in sales. A look at a decision that replaces tasks and amplifies people.
In 2026, 67 % of French companies use generative AI, but only 31 % see a productivity gain. Why adoption is not enough, and how to measure the real gains.
AI doesn’t save time in workforce scheduling, it reveals what you do with it. Here are the 5 steps to a successful HR adoption, without the panic or the failure.
In 1984, Ken Thompson revealed an attack that no longer targeted code, but the trust placed in it. A story that quietly frames the question nobody has dared ask AI yet.
Anthropic launches Claude for Teachers, joining OpenAI, Google, and Microsoft in the race for classroom AI. Behind the announcement sits a question nobody is asking loudly enough: who corrects the machine when it gets something wrong about what our kids are learning?