How do you view Huma airdropping to Kaito Yaper?

Author: Haotian

Regarding the airdrop from @humafinance to Kaito Yaper, the underlying intricacies are much deeper than they appear on the surface. Here are three points:

1) The transition from "interaction farming" to the "algorithm farming" era. In the past, interaction farming relied on "diligence"—opening multiple wallets, boosting interactions, and stacking TVL. Now, we have directly entered an era where "algorithmic weight" and Mindshare are the focus.

Platforms like @KaitoAI and @cookiedotfun essentially create a "digital profile" for each KOL, quantifying content value, audience quality, interaction efficiency, and other influence dimensions through machine learning.

To some extent, this upgrades the KOL selection mechanism, which originally depended on "insider relationships" and "subjective judgment," to a precision targeting driven by AI data.

However, initial algorithm assessments can be less than satisfactory. For example, small-scale collusion can be achieved through mutual liking groups, follower boosting, and comment exchanges, leading to a short-term influx of farming studios eager to seize the opportunity.

But don't forget that algorithms can be continuously optimized. By paying attention to IP and asset relevance, one can avoid being targeted by "witches" in interaction farming, but in algorithm farming, especially under "black box" conditions, the probability of being targeted by "witches" will only increase. Treating this as a "farming business strategy" requires caution.

2) The "hierarchical differentiation" of the platform KOL ecosystem will accelerate. To be honest, top KOLs already have the ability for Alpha research and opportunities for early deep involvement in quality projects, which allows them to monetize their influence through consulting, investment, and on-chain finance.

As a result, these big names tend to be more "aloof," posting infrequently and interacting cautiously, which may lead them to be classified as "inactive users" in the eyes of algorithms. In contrast, mid-tier and lower-tier KOLs who frequently retweet, comment, and interact daily can score high in the algorithm's activity ratings.

This actually exposes a core bug in the current algorithm assessment—mistaking "quantity" for "quality" and "frequency" for "value." In the short term, this will indeed bring a wave of benefits to those KOLs willing to frequently promote projects.

However, the algorithm ultimately needs to rely on objective influence assessments to succeed. As algorithms continue to optimize, "interaction frequency" will inevitably yield to "content value" weight; otherwise, top KOLs and quality projects will leave, which is something the platform holders controlling the algorithm's black box definitely do not want to see. The key is how to balance content value and interaction frequency to avoid severe differentiation of platform KOL resources.

3) The "hidden inflation" of marketing costs for project parties has already begun. On the surface, moving from finding agencies to package KOL resources to directly using platforms like Kaito for precise targeting seems to eliminate the middleman. But what is the reality? Project parties must pay a booth fee to participate in this "algorithm arms race," and as competition for bidding positions intensifies, hidden costs will only rise.

What’s more concerning is that algorithms overly rely on quantitative metrics—like the interaction numbers of Smart Followers—while neglecting truly valuable aspects such as content depth, audience quality, and brand fit. The issues arising from algorithmic bias are evident:

First, marketing ROI declines—airdropping to accounts with mismatched influence value will certainly lead to conversion results falling short of expectations; second, brand reputation risks—overemphasizing interaction quantity at the expense of content quality could damage the market recognition that project parties have painstakingly built.

Of course, this is also a dynamic game. Algorithm models will continuously optimize, and project parties can intervene for adjustments. Ultimately, it must return to the mutual matching of brand value and user value for the business of algorithm platforms like Kaito and Cookie to truly grow and strengthen.

Note: My personal Yap points are acquired in a very laid-back manner. In the past week, I've noticeably felt that valuable content has been weighted more heavily, resulting in a higher ranking. Platforms like this AI algorithm are quite important in the allocation of "ecological niches" in the attention economy's Mindshare.

However, it’s best to avoid a monopoly, so supporting more platforms similar to Cookie to join the competition is very necessary.