The Next Next: Update #12

One foot in front of the other.

For those of you tuning in for the first time, The Next Next is a ‘build in public’ type of journey from founder Jason Jacobs (me!) to explore 1) how I can build my next company differently (prioritizing health and family, not just work, while still building an ambitious and important company) and 2) how AI can help, and more broadly, how it will change how startups are built and funded.

There is this newsletter (subscribe here), which publishes weekly and chronicles the ground I covered that week, insights I’ve gleaned, topics I’m wrestling with, and where I plan to dig in the week following. And there’s also this podcast, which publishes twice a week, and explores these topics in-depth in a series of interview-style discussions with others who are well placed for me (and you!) to learn from.

The goal of this public learning journey is to have it evolve over time from a journey into a livelihood, to prove to myself and others that it is possible to ‘have your cake and eat it too’, and to help define a new playbook for how to build companies that inspires many other founders to follow suit and gives them a roadmap for how to get started.

If you want to catch up, the historical weekly updates are here:

Week 1, Week 2, Week 3, Week 4, Week 5, Week 6, Week 7, Week 8, Week 9, Week 10, Week 11

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Another packed week.

On content:

The content machine is ROLLING! I think I scheduled a dozen more recordings in the last few days alone. Loving how much I learn from each one, and how each one builds on the one before. I swear, if I could have learned this way in grade school, I would have been a straight A student! (I was far from it)

As the content library grows, it seems clear that 1) our production value should be improving over time, 2) we should expand to more formats over time, 3) we can do more with the clips and 4) there is gold in the underlying aggregate data.

For now, I am just focused on being a recording machine. But these are all things to keep an eye on, as the slider will slowly upgrade in each of these areas over time as we get more established and the machine gets more efficient.

Couple new episodes shipped this week:

Brian Balfour - Brian is a multiple-time VC-backed entrepreneur, a dad, and happens to be building a company that provides expert training & AI-powered tools for product teams, so his perspective is super relevant to my journey on a number of levels. Brian got super honest and vulnerable in this episode, and I am grateful to him for doing so, as I got a ton out of the discussion. You can find it on apple, spotify, and youtube.

Paul Heayn - Paul was a PM with me at Runkeeper back in the day, and came inbound from this newsletter, as he’s been incorporating AI into his day job, building stuff with it nights/weekends, and excited about where things are going. I invited him on to talk about his approach, what he’s been learning so far, how he sees it changing the PM function over time, and of course, to give me advice on how to incorporate it into what we are building here with TNN. Paul did not disappoint, he had a lot of great insight that should be super valuable to anyone trying to figure out how to get going with these tools. You can find it on apple, spotify, and youtube.

New product idea:

My friend Makaela texted me this:

What was interesting about it was that today, a videographer (or a parent!) shoots game footage, or perhaps you can use the footage from a service that records all the games like LiveBarn (w/ lesser quality). Then you send all of that footage to a videographer, let them know your player’s jersey number, they pull clips of that player across games, make a highlight reel, and add some music.

It seems like a good use case for AI to handle. It’s highly manual and time consuming, and the AI could be trained to pull clips at key moments, for example when the crowd cheers or when the goal buzzer sounds.

It could be a self-service model for people who need these videos made (to send to coaches or scouts, or to post on social media), and they would presumably be cheaper to buy than hiring a professional and “good enough” quality.

This makes me think that it would be interesting to determine where AI is best suited to help with these kinds of use cases, determine key criteria, and go make a big list. Then, you could cross reference that list with the criteria to determine where the math works (for example, does it need to be a certain price point or margin?), come up with a short list of where both align, and go build AI products for each one!

I am sure there would be economies of scale in terms of both expertise and infrastructure under the hood that you could leverage across products. Of course distribution would need to be figured out, but it is an exciting direction to think about. I am not sure if it would be “purposeful” enough, but if you built 10 products, each w/ $1m ARR run-rates and a 2-3 person team total to power all of them, it would not be a bad business! (understatement)

Innovator’s dilemma on my mind:

I’ve been thinking a lot about Clayton Christensen’s Innovator’s Dilemma. There is this huge paradigm shift coming caused by the acceleration of AI. You have all these established companies who know they should be thinking about it and getting smart on it, but are also under a lot of pressure on the hamster wheel of their core business. This, I believe, is causing them to lurch and pay big consulting dollars, pay for a bunch of subscriptions to different AI tools, etc without having a clear grasp on what they need or on which types of tools or services will be the best fit for them. So, in this sense, I can see why there could be artificially inflated revenue growth in these areas in the short term.

But directionally, it is also clear (to me at least!) that the changes coming will be profound. And just bolting on AI to your existing stuff will be a lot less impactful than re-architecting how you do things from the bottom up in an AI-first way. To me, this is where the Innovator’s Dilemma plays a role. I think a big obstacle to fully embracing what’s coming is less of a technical one and more about inertia and people/process/established core businesses. In that regard, it is a fantastic time to be an upstart! Or, given how fast things are moving, it is exciting to be a free agent too like me, who hasn’t chosen a lane yet, but is investing a lot in getting smart on what’s happening at the tip of the spear.

The journey becoming the destination:

Another thing on my mind is all this learning is great, but at some point I need to build something! This whole journey is about finding my lane. One interesting thought though is that I wouldn’t be surprised if the journey becomes the destination. While I have no business model yet, this journey sure feels like one I am going to be on for a long time, meaning if I can find a way to make money (to feed my family, and also to put more resources towards what we’re building here), then maybe the path I am on now is the path I set out to search for!

Are the tools ready for non-coders?

If you’ve read my prior updates, you know that I have been chasing my own tail around with this one. What I am finding though is that it’s not just me! It seems that half the people I talk to that are deep w/ using AI for coding say it’s for anyone and that chatGPT can be your mentor and that’s enough. And the other half of people that are deep w/ using AI for coding say it’s really only ready to help experienced engineers be more efficient, and that maybe for prototypes its fine but for any type of real software, it isn’t for non-coders like me.

I am going to continue to get my hands dirtier with these tools over time regardless, but I still don’t know whether it will be me doing the coding for our needs at the TNN or whether I’ll need/want help. My current thought is still that I could go super far w/ two helpers: a hacker for coding and a producer for content, both of whom lean hard into AI to make their efforts go further. But I still can’t rule out that it will be only me!

Asks for this week:

• intros to strong founders using AI for meaningful parts of their development process

• intros to consultants helping bigcos figure out (and implement) their AI strategies

• intros to investors who have been active backing AI companies for a while now

• intros to people inside established companies who have bene spearheading their transition to incorporating AI into their products and internal processes

• any tips on how to step up our content game

That’s it for now, have a good weekend/week!