Lucky's Tanabata co-branding controversy may seem to be a marketing rollover, but in fact it exposes the current trust gap between brands and consumers. This IP has 6 million fans in the Short Video circle, but public awareness is almost zero. Lucky chose to force cooperation, as if testing the bottom line of consumers 'tolerance. This kind of "circle self-hi" marketing strategy is not new. There are many cases in history where brands have been disconnected from mainstream consumers due to excessive pursuit of "niche culture." For example, Starbucks 'infamous "Cat Claw Cup" incident, which eventually evolved into a buying farce and crazy hype in the second-hand market. Luckin's problem this time is that it didn't realize that as a chain coffee brand, its user base is far more diverse than any vertical circle. When consumers find themselves spending money to pay for the love affair of a strange couple, behind the anger lies questions about the transparency of brand decision-making. What is even more alarming is that this marketing method is becoming a trend-brands are increasingly relying on algorithmic recommendations and data-driven, while ignoring the most basic human resonance. Lucky's approach reminds people of Pepsi's "Live for Now" marketing, which tried to kidnap young people with radical slogans, but was accused of being the supremacy of consumerism. The difference is that Pepsi at least has a clear target audience, and Lucky's co-branding is more like a blind gamble on consumers 'blind loyalty to the brand. In the long run, this strategy will accelerate the collapse of brand trust, especially in an era when consumers are increasingly wary of being "harvested."
Another theme worthy of attention is that the deep water area where AI is being implemented is emerging, and the emerging position of FDE (Frontline Deployment Engineer) is the best footnote. From Alibaba Tongyi Qianwen's download exceeding 2 billion, to Tencent's QQ Bot access to Harness, to NVIDIA's promotion of computing power financing and energy cooperation, the story of AI has moved from "showdown" to "pragmatic" stage. But the emergence of FDE exposes an ignored truth: after general AI capabilities become public supplies, the competitiveness of enterprises no longer depends on the model itself, but how to embed it into specific business scenarios. This is exactly the same as when cloud computing emerged in the 2000s-AWS and Azure were successful not because of how advanced their technologies were, but because they solved the "last-mile" problem when enterprises landed. The core value of FDE is to bridge the gap between model and business, but this also means that the implementation cost of AI is shifting from explicit computing power investment to implicit labor costs. The bigger risk is that FDE may become a new "IT outsourcing" trap-companies have to rely on external engineers in order to quickly implement AI, and these engineers 'deep understanding of the business determines the success or failure of AI applications. Historically, there have been many cases of failure to implement ERP systems, often not due to problems with the software itself, but the disconnect between the implementation team and the business department. The rise of FDE may repeat the same mistakes, especially when AI is regarded as a "universal antidote", and it is easy for companies to ignore the sorting out of business processes and the adjustment of organizational structures. In addition, the emergence of FDE also indicates that the AI industry is changing from "models are king" to "scenarios are king," which means that competition in the future will be more cruel, because the complexity of scenarios is far from being solved by models alone.
Finally, the rise of HTML as a new carrier of AI office reminds people of the rise and fall of Flash back then. WorkBuddy claims that users can generate HTML pages in natural language in more than ten seconds. This may seem like a model of AI-enabled productivity, but in fact it may repeat the mistake of Flash-on the surface, lowering the technical threshold, but in fact creating More technical debt. The problem with Flash is that it creates a closed ecosystem that HTML's openness should avoid, but AI intervention may turn HTML back into a black box. The bigger worry is, when AI can generate HTML, who will ensure that the generated code is maintainable? Historically, tools such as FrontPage and Dreamweaver have promised to make web pages accessible to non-technical people, only to create large amounts of "spaghetti code" that are difficult to maintain. AI-generated HTML may be more subtle because it may seem "smart" but may actually pose more compatibility and security risks. In addition, HTML, as a new carrier of AI office, may also accelerate the fragmentation of office tools, because each AI tool may generate its own unique HTML structure, making cross-platform collaboration more difficult. This is exactly the same as the compatibility war between Microsoft Office and WPS, except this time the enemy is more secretive. What is even more alarming is that behind AI's generation of HTML may be a redefinition of the developer's role-when AI can generate code, will the value of developers be weakened? History tells us that every technological revolution eliminates a group of old roles, but it also creates new opportunities. However, behind AI's generation of HTML, is there really enough market demand to support its long-term development, or is it just another bubble that is ripened by capital? The answer to this question may require waiting time to verify.