Innovation Articles from October 2025

Why Startups Fail: Patterns From $2 Billion in Startup Failures – Wildfire Labs 

• Research shows failure patterns are more consistent than success formulas. CB Insights’ analysis of startup failures revealed that 42% failed due to no market need, 29% ran out of cash, and 23% had team issues… Entrepreneurs can use the following evidence-backed checklist based on patterns from startup failures: Fit, Acquisition Economics, Internal Alignment, and Liquidity Planning.

Divergent Thinking: When, Why, What and How – Audrey Crane

• “A study on divergent thinking showed that, “[T]he relation between divergent thinking and innovation outcomes is always positive, with increasing marginal returns ranging from 16-38%. There is also evidence for non-linear effects of divergent thinking on exploratory innovations, job creation, and expansion outcomes.” Add the fact that it’s good for us personally—studies show it decreases anxiety, boosts dopamine, and even makes us feel more confident. Given all that good stuff, why don’t we do more of it?”

Test Before You Invest – David Bland 

• “Corporate Venture Capital (CVC) is becoming increasingly popular to accelerate innovation. Yet, most of these partnerships between corporations and startup fail to create strategic or financial returns… CVCs often operate like traditional investors when they need to act more like experimenters.”

AI-Generated “Workslop” Is Destroying Productivity – HBR 

• “Employees are using AI tools to create low-effort, passable looking work that ends up creating more work for their coworkers. On social media, which is increasingly clogged with low-quality AI-generated posts, this content is often referred to as “AI slop.” In the context of work, we refer to this phenomenon as “
  workslop 108(9.2%).” We define workslop as AI generated work content that masquerades as good work, but lacks the substance to meaningfully advance a given task.”

Next Four Innovation Articles

Here’s What the Data Says People Ask ChatGPT – Washington Post 

• “OpenAI released the first detailed public study on who uses its chatbot and what they most often ask it to do… The company reports that most ChatGPT users are women and that the majority of requests sent its way are not work-related. The user base is dominated by young people — nearly half of the conversations studied were from people aged 18 to 25. In June 2024, prompts to the chatbot were split roughly evenly between work and personal uses. By June 2025, nonwork uses made up 73 percent of all conversations, the company said.

7-Eleven Begins Trial of Shelf-Stocking, Floor-Cleaning Robots in Tokyo – Japan Today 

• “Seven-Eleven Japan Co introduced worker robots to one of its convenience stores in Tokyo, with the trial part of an automation push necessitated by Japan’s worker shortage. One robot will take over tasks such as stocking bottled drinks and canned alcohol, while others will clean the store’s floors and windows. The development is aimed at aiding store operators who are struggling with labor shortages and higher wage costs. The store has also introduced a screen on which customers can be served remotely to lessen the workload of cashiers in stores during late-night shifts.”

Is AI a Bubble? – Azeem Azhar 

• The best way to understand a question like this is to create a framework, one that you can update as new evidence emerges. Putting this together has taken dozens of hours of data analysis, modeling and numerous conversations with investors and executives. This essay is that framework: five gauges to weigh genAI against history’s bubbles.

The Human Skills That Will Help Us Adapt To AI (And Not Die) – Shane Snow 

• “Organizations can’t rely on being the first to adopt new AI technology as a strategy. Individuals can perhaps adopt fast enough to gain short-term advantages. But by the time that new AI workflow tool goes through your company’s compliance department… your competitors have it too. Our advantage is going to be our ability to think differently than folks who are all using the same AI tools.

Final Two Innovation Articles

Golden Design Lessons from Tokyo Metro – Lihn Nguyen

• “Tokyo’s metro isn’t just about trains — it’s a whole experience designed to carry you from point A to point B without getting lost (or panic-scrolling through your map like a tourist in distress). I’ve broken the ride down into four steps to show how they make every part of the journey feel smooth and user-friendly.”

No One Wants Ads on Their Fridge – Jeff Gothelf 

• “Samsung’s latest “innovation” is an $1,800 fridge that shows ads. Samsung recently confirmed that their Family Hub “smart” refrigerator (retail price $1,800) will show ads when the screen on the front door is idle. They claim this is innovation. I claim it’s bulls**t and I suspect you do too. Can you imagine installing your brand new, state-of-the-art refrigerator only to have it show you ads on the screen that’s supposed to show, well, whatever a “smart” refrigerator screen is supposed to show? Once again, we find ourselves with a feature that no one asked for, no one wants and will undoubtedly hurt sales of the product. Why does this continue to happen? The answer is simple: a lack of customer-centricity and greed.”

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