Threadcast link:
https://inleo.io/threads/view/khaleelkazi/re-leothreads-nd34dhbu
Link to recording:
Speakers
@khaleelkazi @anomadsoul @scaredycatguide
DISCLAIMER: The following has been generated by AI (Claude-3) based on the publicly available recording of the livestream. Because the content is AI generated it may contain errors, so please keep that in mind when reading. Feel free to suggest corrections and/or add additional information/improvements in the comments. Read more: Introduction post for the AI Summaries project
This episode of the InLeo AMA provided an in-depth look at the current state of the InLeo platform and the team's plans for future development. The discussion covered a range of topics, including user growth metrics, upcoming feature releases, and strategies for improving content curation and engagement.
Current User Metrics
The latest monthly active user (MAU) numbers for the platform was shared. It reported that InLeo closed June with over 1,350 MAUs, which is a positive sign considering the overall downtrend in the crypto market over the past few months. The team is aiming for at least 20% month-over-month growth, and they expect July's numbers to be even better.
The team also shared data on threaders (866 users) and content creators (988) - two key user segments for the platform. Notably, the total number of threads, posts, and comments made on InLeo has been on a significant upward trend, with June seeing over 90,000 threads created, a new record.
Improving Content Curation
A major focus of the discussion was the team's plans to enhance content curation on the platform, particularly for threads. Khal acknowledged that there is currently a lack of diverse curation, with a small number of accounts responsible for the majority of votes on many threads.
To address this, the team is exploring ways to incentivize more manual curation, rather than relying on automated voting. This could include changes to the leaderboard system, such as incorporating metrics that reward users for voting on a wider range of content, rather than just the total number of votes cast.
Khal also suggested the possibility of adding a "like" button in addition to the upvote, which could then trigger curation from designated accounts once a certain number of likes is reached. The goal is to shift the culture away from voting primarily for rewards and towards more organic, community-driven curation.
Upcoming Feature Releases
The team provided updates on several upcoming feature releases, including the introduction of video capabilities on the platform. They are currently testing long-form video uploads, with plans to roll out a "shorts" feature as well. The shorts will be designed to work similarly to platforms like TikTok, with a full-screen, swipeable feed.
Additionally, the team discussed the integration of LeoAI, the platform's artificial intelligence component. The first implementations of LeoAI will focus on improving the recommendation engine, both on the "For You" feed and on individual thread pages. LeoAI will analyze user behavior and interests to serve more personalized and relevant content.
In the future, LeoAI will also power features like a ChatGPT-style prompt engine and a "co-pilot" tool to assist users with writing and ideation. These AI-powered features will be exclusive to Premium subscribers, as the team aims to provide significant value to justify the subscription cost.
Conclusion
Overall, this AMA session provided valuable insights into the current state of InLeo and the team's plans for continued growth and development. The focus on improving content curation, enhancing the user experience, and leveraging AI technology suggests that the platform is well-positioned to attract and retain a dedicated user base in the evolving social media landscape.
@leoglossary links added using LeoLinker.
Posted Using InLeo Alpha
Pretty cool summary. I haven't listened to the AMA yet. Anyone know how accurate this is?
It does tend to omit some of the finer details though, so if you want to make sure you heard it all, you'd probably prefer listening to the whole episode as well.
I just finished listening to
Alright! What's your verdict? Regarding your question about the summary that is
It was accurate but some points were missing
It's pretty accurate. The summary is strictly based off of the episode's transcript and I'm using an almost top of the line language model.