That is what "using AI to learn AI" means to me.
You do not need to understand the whole system before you begin. You use the work to build the understanding.
Another learning: sit in the room with your team and figure it out together.
AI is an empty text box. Watching someone else use it closes the gap faster than anything else. Big shoutout to March Rogers for building that culture.
We brought the prototype to product partners, and because they could use it, they could feel the problem.
It influenced product direction. The work now coming into the product traces back to what the research made visible.
We iterated using Figma Make, GitHub Copilot, Claude, Codex CLI, and eventually GitHub Copilot in CLI.
We built against the Intune design system and partnered with the security org's design team who owned it.
In about 3.5 weeks, with AI alongside us, I set up a GitHub repo for the first time in years, learned Azure hosting, made plenty of mistakes, and helped lock the prototype down to Microsoft employees only.
Something we could send as a link. Something people could feel, not just look at.
The goal was not to ship code. It was to learn fast enough to influence the people who would.
Then came the human decision: this problem is real, and we need to solve it.
Once we committed, we made another call: instead of weeks of static Figma sketches, we would prototype the actual experience.
We had two years of conversations, studies, and feedback in different places. We used AI to synthesize all of it.
It did not replace researcher judgment. It helped us look across everything at once.
It started with research. Abena Edugyan and our research team had benchmarks across our core Intune experiences.
Task success was poor, so we went deeper. What we found confirmed we had a real problem.
One of my biggest learnings after almost a year of using AI every day: you should be using AI to learn AI.
Last fall our team did exactly that, and it changed the direction of our Windows 365 management experiences in Intune.
Two weeks since launch, which is WILD to think about it only being that long.
@themiseapp has seen 4.27k new users in the past two weeks, with 402 active trials and a >$0 #MRR of $180.
Shout out to all the other creators sharing their tips and #buildinginpublic
1/ When we sat down to create Mise, we wrote a few goals on the whiteboard.
Among them were to learn and to generate more than $1 in MRR (spoiler: we've done both), but we also wanted to design something that actually solved a problem for ourselves.
Love taking a vacation and having an app work for you. Coming back to more sign ups and some steady growth! Need to double down on learning how to post engaging content. I’ve always been a lurker and I’m realizing I’ve never really learned each platform.
One week into launching @themiseapp and learning a lot. We’re close to crossing $100 MRR which is really cool. Lots of product work ahead and I still have so much to learn about leveraging social media to grow this business. Just trying different hooks and content types on X, IG, and TikTok - if folks have good learnings to share I’d appreciate it!
#BuildInPublic #BuildingInPublic #IndieHackers #StartupLife #SaaS #FoundersJourney #VibeCoding
16/16 My advice: go build the thing.
AI can get you to something you can hold, test, and feel fast enough that the old excuses stop working.
You don’t need the finished version to know if an idea is worth pursuing. You just need to get close enough to see it.
1/16 Last week I wrote about why I hate meal planning.
I love cooking for my family. But every Sunday, the planning wears me down: staring into the fridge, scrolling through apps that never quite fit, and wishing someone would build a better solution.
15/16 In one month, we moved from research and rough ideas to a fully interactive prototype that felt like the real product.
Our product partners loved it, and the work changed the trajectory of this year’s roadmap.
More to share at Ignite.