@elonmusk@aelluswamy v14 to the legacy model s plz
Will come work on the distillation process for free….
Have we tried telling grok to make it happen faster ????
The $15k MRR clients are nice to have, but there really are not that many for us In this industry.
The $3k - $6k have the best margins, perform the best and are closing 20%-30% of the leads we send.
$15k clients are happy with sales reps closing 10% of all leads we send them.
Do I wish they closed higher? Yes
Do I like billing $15k in one rip? Yes
It’s all about balance.
My steak is too juicy my lobster is too buttery blah blah blah
Btw for those of you thinking of copying us, I specifically price myself lower than what you can do this for.
How?
✨Vertical integration✨
We own the database, the sending infrastructure, direct integrations with their legacy crms, and a fuck load more.
We actually on track to our own insurance carrier lol
Why?
I don’t want to sell leads for the rest of my life. I have enough self respect not to sell a course lol.
So yeah starting a national carrier is the next logical step.
One step at a time.
Anyway, if you control the leads you control the business.
What do I know tho. 🤷 This is your world, I’m just living in it.
Interesting take, but I'd be interested to explore the other side. What will this do for consumers? How many people who couldn't afford a lawyer before this + AI can afford one now?
How many people per year hire a lawyer vs. how many would've liked to, across all practice areas?
What about lawyer costs? These stats suggest rates go way down.
What about how many cases one lawyer can take on with AI in their back pocket?
Why is everyone expected to have a personal doctor but not a lawyer?
What happens if lawyers move from discretionary to essential for people? I'd say if this becomes reality, then one could argue we don't have enough people registering for the LSAT.
One critical point made by Karpathy on the Dwarkesh podcast was about the difference between AI coding agents and the rest of knowledge work.
It’s clear that AI agents in coding have taken off extremely quickly. There are many reasons for this, including the fact that a substantial amount of training data is already online compared to other domains, developers are quick to try new tools, and the labs have a lot of incentive to get this right.
But there’s a subtle and fundamental reason as well that Karpathy covers: the domain is comprised almost entirely of text (great for LLMs!) and we have clear standardized tools that already are essentially text editors (IDE) where almost all of the work is self-contained in. There are few other domains where AI agents will find as ripe of territory as this.
This is partly why the diffusion of AI agents will take longer in other spaces, but it’s equally the opportunity in front of anyone working on knowledge worker agents. We are entering a new era of software for knowledge workers that allow for intuitive, yet powerful ways to interact with agents.
Some of the existing incumbents will have a natural position to build these solutions, but a lot of spaces will be up for grabs because some won’t move fast enough. And equally there will be many categories where there’s no natural incumbent because it’s the first time software is being applied to the market.
The companies that are able to bring these solutions to market, especially into enterprises that will require change management and process reengineering, will be those that win.