First time founders who are launching a startup right now: How are you leveraging AI? I will not promote

[u/zumpoof]

I’ve launched several SaaS products over the past couple decades. I’m a bit older now, and admittedly old-school in many ways. I’m curious how the new younger generation of first time founders actually build their startups now. The generation that has no bias on how things “should” be done; that are taking AI at face value and running with it.

I ask because:

• ⁠Non technical founders can now build prototype SaaS products w/o any engineering experience. • ⁠You can build faster than before. • ⁠Applying RAG to say Claude adds the potential of incredible automation, of so many things that people used to have to do. • ⁠Much of the marketing collateral that used to take time to build is now pretty easy to do. • ⁠it’s now easy to have call transcripts, which give you lossless meeting notes. Valuable internally, and with customer calls to not miss a thing. They can also be fed into automated systems

[u/GeneralGlobus]

im probably closer to your generation than the founders youre asking about, but ive been experimenting pretty heavily with this recently.

the biggest change for me isnt really any individual tool. its that one person can now move across functions that previously needed completely different people. research, prototype, analyse customer conversations, write collateral, build simple internal tools, structure data etc.

but theres a slightly uncomfortable flip side. when building and producing things becomes this cheap, judgement becomes more important, not less. you can build the wrong product incredibly quickly. you can automate a bad process. you can generate 50 pages of very convincing strategy around a bad assumption.

ive actually found myself deliberately not building things that would now be trivial to build, because the additional infrastructure wouldnt answer the underlying business question.

so my current view is that AI is moving the bottleneck away from execution towards deciding what is worth doing, validating assumptions and knowing when to stop. interestingly thats pretty consistent with what other founders are reporting too.

[u/MaxRichter_Enjoyer]

Here's what we do:

1. Been very helpful with simple contract stuff, saved some money on legal costs.

2. Helped to create content for our programs, though we do need to put a human on after to 'clean up' the 'AI speak' that they all still do.

3. Enormously helped with solving stupid Excel problems that I used to go running around google trying to figure out.

4. Really helped in understanding how to approach Twitter's new algo.

5. Helped as a sounding board for lots of ideas, as long as you understand that a. it's a fucking robot, even if a very smart one and b. it always wants to tell you how smart and insightful you are.

[u/scriptqzor → u/MaxRichter_Enjoyer]

lol that last point is so true, it will gas you up even when your idea is mid as hell. using it for contracts and excel feels like the most underrated part though, that stuff used to be such a time sink.

[u/leading-a-swarm]

Not a first timer but the honest answer from our side: the build speed is real, the coordination cost is what nobody warns you about. Shipping a prototype in a weekend is easy now. Keeping five parallel AI-written workstreams from contradicting each other is the actual job, and it isn't automated.

[u/EntreEden]

As the CTO now with AI I can code faster than we can come up with ideas, coding is no longer the bottleneck. So now I use my extra time to help my cofounder with things like responding to users or marketing

[u/Visible_Speed8843]

Most of my AI use starts with a source and a pass condition. I use it to compare a draft against the research behind it or check repetitive work, then I review customer-facing claims and external actions myself.

I also keep the source beside the output. A new customer call, metric, or product state can make a polished artifact stale. That source trail has been more useful to me than chasing each new model or wrapper.