On Truth Social this morning, President Trump joined the chorus of Americans calling for Cracker Barrel to “go back to the old logo, admit a mistake based on customer response (the ultimate Poll), and manage the company better than ever before.”

After Trump’s post, Cracker Barrel’s stock price, which had plummeted by eight dollars following the announcement of the company’s new logo and store layout last week, rebounded by three dollars. Whether the rebound was mainly a reaction to the free publicity Trump generated for the company, or a sign of optimism that Cracker Barrel might follow his advice, remains to be seen.

What is clear is that Trump’s intervention notwithstanding, Cracker Barrel should reverse course.

When the company chose to replace its iconic old-man-and-barrel logo with an antiseptic blank slate featuring only the words “Cracker Barrel”, and to transform its wood-paneled tchotchke-cluttered interiors to look sleek and shiny, it ignored the closest thing to a hard-and-fast rule in marketing: that it’s more expensive to convert new customers than it is to keep old ones.

A large part of Cracker Barrel’s value as a company (perhaps a larger part than that of any other national restaurant chain) lies in goodwill — in customers’ lifelong relationship with the Cracker Barrel brand, their memories in Cracker Barrel restaurants, and the nostalgia those memories evoke. Now that Cracker Barrel restaurants have been sanitized to look like Applebee’s, many of those customers will likely stop patronizing Cracker Barrel, or will do so less frequently.

And who are the legions of new customers who will replace those lifelong fans and patronize the “Cracker Barrel of the future” (to quote Cracker Barrel CEO Julie Masino)? The company will have to find them through hard-fought, expensive, and very likely fruitless marketing campaigns.

Cracker Barrel’s strategy here is emblematic of an all-too-common tendency in general management: to be too quick to blame bad business results on a bad brand. Restaurant chains end up underperforming for a host of reasons such as location choices, supply chain, customer service, product offerings and quality. But one of the hardest things for any retailer is to develop and maintain a memorable brand that has intrinsic value. That was one thing that Cracker Barrel had, and it should have been the very last thing that company executives were willing to reevaluate when fiscal times got hard.

By reducing its logo and interiors to the blandest, most inoffensive version of themselves, Cracker Barrel is chasing shallow mass appeal. But stronger branding often comes from cultivating a deeper connection with a smaller audience — and from rejecting the idea that every brand must “look like the future” to be better.

A week into Cracker Barrel’s calamitous new brand launch, CEO Masino continues to hold firm, insisting that customers “like” the changes. The stock market, our most accurate public opinion poll on business behavior, tells a different story. The best course of action for Cracker Barrel is to take the free advice and go back to the drawing board.

China is trying to catch up with America on artificial intelligence. The Wall Street Journal has reported that Zhipu AI — one of China’s six “AI tiger” LLMs — has released a new model that can rival leading US systems, including Anthropic’s Mythos, in cybersecurity tasks such as pinpointing security bugs. While this marks a milestone in China’s drive to catch up with Western AI capabilities, strong performance on a single benchmark does not mean it has taken the lead. Chinese models still lag behind their Western counterparts in broader capabilities, such as autonomous operation. Skepticism is therefore warranted before resorting to hysterical conclusions, but complacency about the geopolitical implications of China’s AI advances would be an even greater mistake.

On the infrastructure side, Chinese AI is still constrained by access to advanced chips, with American labs way ahead in computing capacity as well as investment. Analysis from earlier this year suggests that Chinese models are likely to be at least a few months behind those in the US. But they are still continuing to make progress, or that the geopolitical importance of AI will be decided only by whose LLM has ventured deeper into the technological frontier. The practical applications of AI, countries’ to capture foreign markets, and the application of AI into the real economy will matter just as much.

Here, China may hold an advantage. As with its dominance across many critical supply chains, Beijing may not need to produce the most advanced AI systems — only those that are affordable and widely deployable. In doing so, it could consolidate global influence by supplying functional, low-cost AI at scale.

Beijing seems to be pursuing exactly that path, developing an AI “open-source” strategy that offers affordable, widely available AI models for companies and individuals to use and modify as they wish. The production of the DeepSeek AI model, which matched the performance of Silicon Valley tools such as ChatGPT at a fraction of the cost for users, created goodwill among Chinese models with developers.

The four most popular models on OpenRouter, an AI hardware platform for developers, are now all Chinese. The goal for China is not only to win the frontier-model race, but to make its systems the default layer of AI adoption across industries and global markets. For most economies, the choice is increasingly between an affordable tool they can deploy now and a more robust one that may be out of reach.

And while the countries adopting Chinese models may be exposed to political pressure and cyber threats from Beijing, safer and more capable alternatives matter little if they are unaffordable. American AI companies are already under pressure to monetize products whose operating costs are rising. If Chinese open-source models become the cheap default for startups, universities, governments and businesses across the developing world, then America’s AI lead will be eroded from below.

Perhaps more concerning for America in the long run is how AI can give Chinese manufacturing even more strength, through the ongoing integration of AI as a general-purpose technology. China’s new Five-Year Plan mentioned AI more than 50 times and includes an “AI+” action plan aimed at spreading AI across the economy.

Beijing has been pioneering automation of its critical infrastructure for years, with promising recent results in increasing warplane production capacity. In that regard, China’s open-model strategy and manufacturing dominance will reinforce each other. Cheap, adaptable models accelerate deployment across the real economy while those deployments generate real-world data and use cases that can feed back into further model improvement.

The United States should not dismiss the importance of its lead in the AI race. That lead worries Beijing, not least because a more automated Chinese economy would also become more vulnerable to AI-generated cyber threats. But nor should Washington assume that China cannot catch up with American capabilities over time.

This AI competition represents part of a broader struggle over tech supply chains and geopolitical influence. Decisions over whether to adopt US or Chinese models could produce a more fragmented global reality, with different regions relying on different cloud providers, chips and security structures. The result will likely be a global economy which is divided into competing spheres, rather than one which produces a single winner.

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Miquel Vila is a political and geopolitical risk consultant focusing on industrial strategy, critical infrastructure and global supply chains.

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