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  • 1.  The Top 100 Gen AI Consumer Apps - 6th Edition (a16z)

    Posted 25 days ago

    Release update from a16z posted this week:

    The Top 100 Gen AI Consumer Apps

    Key details*:

    • ChatGPT crossed 900M weekly users and still dwarfs every rival, but the gap is tightening - with Claude and Gemini growing paid subs over 200% last year.

    • The new list included "AI-enhanced" consumer apps for the first time, with CapCut, Canva, Notion, Grammarly, and others now slotting into the rankings.

    • The report found three distinct AI ecosystems forming: Western, Chinese, and Russian, with sanctions accelerating the split as local alternatives fill the gaps.

    • Agents are gaining ground, with Manus (#44) and (#47) Genspark making the cut, while OpenClaw is absent due to the report's time frame.

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    * as per The Rundown AI
    - Todor


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    Todor Kostov
    Director
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  • 2.  RE: The Top 100 Gen AI Consumer Apps - 6th Edition (a16z)

    Posted 25 days ago

    Thanks for highlighting this Todor, 

    I particularly liked playing around with Manus which I have found to be very impressive (even the lite version). If anyone has not already set up a demo to build an App or platform that would otherwise have been done in Excel, then I recommend playing around with it. 

    Given some recent discussions - is this an idea for an event? Develop a dashboard for different use cases (investment research, portfolio optimization, idea generation...etc) across different AI Agent platforms? Claude / Manus...etc. 

    Here is a very quick example of a demo on a dashboard which shows long-term capital market expectations for investors: https://capmarkdash-epfbzbb6.manus.space/?code=DQdCoGDWeN975jUMwwpFZc

    This took 5 minutes to create - just imagine how many add-ons could be built here!? 



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    Shane Jocelyn
    Director
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  • 3.  RE: The Top 100 Gen AI Consumer Apps - 6th Edition (a16z)

    Posted 24 days ago

    Great info Shane.  Your idea for an event to discuss tools like Manus is interesting but I'd probably focus more on the inherent issues of these tools with regards output integrity and how to tackle them.  

    From my experience, Manus and similar providers (Base44, etc) are good for quick prototyping but awful to build scalable solutions with plenty of spaguetti code, hidden bugs (black box effect) and security risks. Moreover, they sometimes also drop the ball with regards implementing advance financial  models (e.g. hierarchical risk parity optimization) and, worse yet, they can be very expensive draining credits if the user starts the idea from scratch since their usage pricing is steeper than vanilla chatgpt subscriptions.  

    My opinion it can sometimes be more effective and cheaper to prompt an open-source LLM specialized in software engineering to generate Python source code for the app or dashboard idea, using a framework such as dash or streamlit. The resulting application can then be deployed on a simple and affordable hosting platform like Heroku if it needs to be shared with a team or external users.

    In any case, this is a good event idea that could be discuss in upcoming calls.



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    Carlos Salas
    Portfolio Manager & Freelance Investment Research Consultant
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  • 4.  RE: The Top 100 Gen AI Consumer Apps - 6th Edition (a16z)

    Posted 18 days ago

    Great efforts Shane. Thanks for sharing.



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    Todor Kostov
    Director
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