> Manus is running $5000 credit for 2000 people.

How would this work though? They give out free "credits" and then claim usage of those as ARR? That would be outright fraudulent, no?

Who is paying for those "Manus Credits"?

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And now Perplexity has mailed all of those "free" users to add a "card" (wont charge now) to continue with its free pro offer. Apart from airtel perplexity ran a lot of college based programs where students were basically referring each other for money.

>paying about $500-600 for a 14 day course. I only co-mentor for 2 days - the days we teach fundamentals of software development and then show how to code with Replit, Bolt, Lovable, Emergent, etc.

Wow.

Do these tools require training to use? Are they not really designed such that a 5 year old can use it? "build me a thing that does Y" style.

After 10 years of hard work, it was an "instant" success.

IMHO at least some spending on AI are FOMO driven. Companies think how they can adopt AI faster than competitors in a fear being left behind and loose the race. They don’t yet know if ROI of AI adoption is above zero. Even if adopting AI is the only right decision some of AI users may go out of business having overspend on AI and either way AI customer base will decrease.

Yes if they are losing on unit economics can they make it up on scale (facetious saying but there may be truth to it for some AI startups)

There's a loop between adoption of a technology and adaptation of a technology. For some domains that loop is fast, the adaptations prove to be easy and the feedback from adopters is easy to get. For other domains it's slow, especially towards the end of the process of going from something interesting to something useful. A good example of a slow loop is self driving, it's hard to get feedback about self driving in safety critical real world situations... another example is medicine.

The other issue is that the value is more or less all in the LLMs (at the minute). For example, I built a data engineering toolkit using LLMs, it created synthetic data from examples, it created ingestion pipelines given different source filed and a target, it created data test rules. I liked my little toolkit and some people were impressed, but the value was all in the models that underpinned it. The crust of clever bits that added value was thin, very thin. Ok, we used the llms to generate some python that then created the synthetic data and testing rules to reduce costs, we had three or four "agents" that worked together to create the pipelines. We decorated target code with open provenance code to create provanance... But just by saying these things or letting you use the toolkit and you seeing what it made - that's enough for any half competent person to relicate it (with AI assistance) in an afternoon, or maybe a couple of afternoons. Maybe.

So, to create a viable company is going to take significant effort (if you can think of a value add) because the value add still has to be real.

The market doesn’t know to ask for the car, yet.

Just a faster horse.

[dead]

If these customers have set an automated system to pay you $200 every single minute, that’s correct. If they haven’t and it was just a one off sale, you are missing the “recurring” part in ARR.

Probably just another AI website generator, like v0 and lovable. Probably no difference.

It's no different than any other VC funded company before GenAI.

They all sold $100 bills with discount before either capturing market or disappear.

I would wager much more.

Is this the capacity most people are using Manus in? I'd imagine it's the higher level stuff.

I guess it's because they all produce sh*t.

I can not unsee it now!

Btw, this reminds me the red hot logo, which is a ass hole too.

That was a really good read.

Yikes.

With a bit of education one would know that manus is Latin for hand. That's where "manual" comes from.

And their logo is, lo and behold ... a hand!