Building profitable AI SaaS in public AIPeekaboo.com • AI search visibility SubredditSignals.com • Reddit & X customer leads
Based in United States
- Tweets 17,022
- Following 1,649
- Followers 3,394
- Likes 15,775
Pinned Tweet
We almost hit $50,000 MRR 🤯
A year ago, AI search barely mattered.
Today, companies pay us to understand how ChatGPT, Gemini, Claude, Perplexity, and Google AI talk about their brand.
It's been a lot of late nights, mistakes, and customer conversations, but seeing this category emerge in real time has been incredible.
Grateful to everyone who's trusted us along the way.
Next stop: $55k MRR. 🚀
123
12
449
895,627
Hot take:
Vibe coding didn’t kill coding.
It killed the excuse that building is too hard.
16
1
22
676
Good morning! ☀️
Today it's 11 days left until we get the keys to our new house 🤩 will be packing a lot during the day and also exploring some playgrounds so the kids get to run around a bit too 😄
What are you doing today?
34
56
880
If you finally have the courage to say who you are and what you need and the person leaves... good. They just did you a favor.
26
82
1,011
23,014
Robotaxi operating hours moved from 10pm to 11pm.
The main thing we’re trying to solve is making sure that we don’t run over pets when they’re hard to see at night. Literally trying to avoid grey kittens on grey tarmac in the dark.
2,185
1,951
29,134
2,786,555
You don't need a perfect sales script.
You need enough conversations to stop sounding scripted.
18
1
24
549
One of the hardest founder decisions is leaving a good idea alone.
Not every good idea needs to become a product.
Timing and focus matter too.
6
1
9
276
Gonna make an alt account where I just straight up lie about AI stuff and see how quickly I can go viral with it
176
13
1,597
46,601
One thing I really liked about this explanation:
we don't naturally communicate through text boxes and perfect prompts.
We talk. We pause. We react. We look at each other. We pick up on things that aren't explicitly said.
Making AI understand more of that feels like the right direction.
Yesterday we previewed Griffin, a Human Interaction Model capable of seeing, hearing, sounding, and looking like a human does. There have been a lot of questions, so I wanted to take a moment to share our thoughts.
By way of introduction: Tavus is a research lab focused on enabling machines to meet us where we are, and to understand the nuances of how we communicate beyond words.
Griffin, our latest model, isn’t publicly available yet. Yesterday’s announcement was a limited research preview to demonstrate what the model is capable of. With AI progressing so quickly, we prefer to share breakthroughs openly and in real-time as we work on a safe public release.
Face-to-face is how we evolutionarily communicate, it carries the most meaning and intent, and we want computers to be able to help with work that benefits from that emotional understanding, expression, and immersion. Some examples of the kinds of use cases we care deeply about:
- A tutor that can build understanding of how a student learns, see exactly when there is confusion or disengagement, and adapt the lesson to fit them.
- A health expert that can answer any questions about your upcoming appointment or prescription, at the pace you want, at any time you need, even on a weekend.
- A language coach that you can practice speaking with, that can correct your movement and pronunciation, and help build confidence to have real conversations
- Or the perfect assistant for everyone, that understands intent, knows how you work and remembers what matters.
We’re working with partners on safeguards and systems for disclosure, as well as inviting discussions with officials around wider regulation and safe use. People will always know they’re interacting with AI, while providing an interface that removes the need to ‘speak computer’.
We believe in a future where computers understand us well enough to make technology more accessible, more useful, and make us more capable as humans. That is the world we want to build, and we understand the responsibility to do so safely.
3
2
8
222
A product doesn't need to solve a huge problem to be
valuable.
A small problem that happens every day can be more
valuable than a huge problem that happens once a year.
3
3
14
265
