Large tech company employees leaving to start AI application businesses has become a trend. Entering 2024, the landscape at the model layer is set, while AI applications have low barriers to entry and low costs, allowing even individuals to develop quickly.
A former Baidu employee calculated that hiring 4 employees plus a few AI assistants could cover everything from development to design for only $80 per month. Although risks remain, many are willing to give it a try.
This year's AI startup environment seems more friendly, but investors are actually more cautious, focusing on product-market fit. With increased difficulty in fundraising, entrepreneurs must either pursue a small but beautiful approach or seek PMF in user scale.
Hit applications are the best choice. From Miao Ya to "Coaxing Simulator" to Writing Style Test, several hit apps show highly similar user groups, distribution channels, and growth curves, providing reference for developers. However, achieving business conversion is key.
Miao Ya Camera first proved the importance of social circles. Starting with internal testing, it spread quickly through friend circles, reaching peak popularity within a week.
"Coaxing Simulator" and Writing Style Test opened up the "QQ Zone-Xiaohongshu" traffic chain. QQ groups gather many young users, becoming an incubator for hit apps. Xiaohongshu became an important platform for secondary distribution.
These cases reveal the "wind tunnel testing" environment needed for AI applications: low trial-and-error costs, high fault tolerance, and users willing to try new things.
Studying hit applications helps open up ideas for super apps. The distribution path has basically formed: incubation in QQ Zones and groups, expansion to various platforms after explosion, with Xiaohongshu becoming a secondary explosion site.
Xiaohongshu has become a marketing battlefield for AI companies, used to clarify user profiles and obtain vertical data. Companies like Kimi collect prompts and use cases through topics for user segmentation.
Successful experiences include: abandoning obsession with large models, allowing users to quickly get started; better understanding scenarios and users; guiding users to break frameworks for viral spread.
Creating hit AI applications is replicable. By replicating elements such as tone and user groups, hit applications can be continuously produced.
Lightweight AI applications can be used for A/B testing, collecting user feedback, and as traffic-driving tools for main businesses. This provides a new low-cost traffic acquisition path.
[This content is for reference only and does not represent personal views]