1
00:00:01,174 -->
00:00:03,218
All right, how's it going everyone?
2
00:00:03,218 -->
00:00:06,023
I'm stoked for another episode of Forward Thinking Founders.
3
00:00:06,023 -->
00:00:10,632
Today our guest is Connor Waslow, co-founder, CEO of Caddy.
4
00:00:10,632 -->
00:00:12,404
Welcome to the show, how's it going?
5
00:00:12,593 -->
00:00:13,682
Good dude, thanks for having me.
6
00:00:13,682 -->
00:00:15,118
Stoked to be here.
7
00:00:15,500 -->
00:00:17,052
Yeah, excited to have you on.
8
00:00:17,052 -->
00:00:19,114
I'm like, dude, I'm not surprised at all.
9
00:00:19,114 -->
00:00:25,861
We first met, I don't know, I don't even like eight years ago maybe in like this like Ozo
and Phoenix.
10
00:00:25,861 -->
00:00:27,553
And you just made like the best impression.
11
00:00:27,553 -->
00:00:29,310
like, know, so talented.
12
00:00:29,310 -->
00:00:32,929
Now you're doing this startup and I'm stoked to highlight you on this podcast.
13
00:00:32,929 -->
00:00:38,393
But I'm just like, I'm stoked to be doing this because you've come so far just from when
we first met at that brewery.
14
00:00:38,673 -->
00:00:41,093
It's actually insane how long we've known each other too.
15
00:00:41,093 -->
00:00:46,453
I think we caught up like a month or two ago and we were like, wait a second, has it been
eight years?
16
00:00:46,453 -->
00:00:48,133
Like that's absolutely nuts.
17
00:00:48,133 -->
00:00:48,833
Yeah.
18
00:00:48,833 -->
00:00:54,530
It's crazy to be on the podcast eight years later, 980, 990 episodes in.
19
00:00:54,530 -->
00:00:56,790
960, 970 somewhere in there.
20
00:00:56,790 -->
00:00:57,930
It's been fun.
21
00:00:57,930 -->
00:00:59,770
It's been fun way to meet people.
22
00:01:00,310 -->
00:01:02,510
Well, let's get into it.
23
00:01:02,510 -->
00:01:03,210
What's caddy?
24
00:01:03,210 -->
00:01:04,730
What are you cranking on?
25
00:01:05,061 -->
00:01:05,511
Yeah, dude.
26
00:01:05,511 -->
00:01:08,183
So, Caddy is the voice interface for your computer.
27
00:01:08,183 -->
00:01:11,644
We're trying to build a big Siri if it actually worked.
28
00:01:11,644 -->
00:01:17,867
We integrate with the apps that you work in every day and do tasks in the background for
you just by talking to your computer.
29
00:01:17,867 -->
00:01:22,209
So, uh think like Gmail, Calendar, Notion, Slack.
30
00:01:22,329 -->
00:01:30,113
Any time that you want to stay in flow and instead offload a task that you might to like a
teammate or someone else, Caddy takes care that for you.
31
00:01:30,808 -->
00:01:39,334
Okay, so let's use an example maybe, like what would be a common app that someone uses and
then how would I use Caddy to interface with that app?
32
00:01:39,334 -->
00:01:40,577
And is it like an extension?
33
00:01:40,577 -->
00:01:43,875
I guess like help me understand a little deeper and like the user experience of it.
34
00:01:43,875 -->
00:01:44,405
Yeah, totally.
35
00:01:44,405 -->
00:01:47,448
So we live as a desktop app that follows you wherever you go.
36
00:01:47,448 -->
00:01:50,771
And all you have to do is hold down the function key to record.
37
00:01:50,771 -->
00:01:54,294
And so for example, you know, I was a product manager at my old gig at loom.
38
00:01:54,294 -->
00:01:56,595
And so I might be going through the app and find a bug.
39
00:01:56,595 -->
00:02:00,918
All I have to do is hold down function and say, Hey, like make a linear ticket.
40
00:02:01,089 -->
00:02:04,161
this is the issue that I found the buttons, the wrong color or something like that.
41
00:02:04,161 -->
00:02:06,403
And then send it in our team Slack channel.
42
00:02:06,403 -->
00:02:13,918
And so caddy behind the scenes will go through, take a screenshot of what you're looking
at, create a linear ticket and then send it over in a link.
43
00:02:13,918 -->
00:02:14,825
in Slack.
44
00:02:15,746 -->
00:02:17,507
This is fascinating.
45
00:02:17,507 -->
00:02:20,418
it's kind of playing, correct me if I'm wrong, because I could be wrong.
46
00:02:20,418 -->
00:02:28,823
It's kind of playing in like the computer use world, like the computer agent, but like
it's a way to prompt computer use agents almost.
47
00:02:28,823 -->
00:02:31,494
Is that a correct way of thinking about it?
48
00:02:31,587 -->
00:02:31,937
Almost.
49
00:02:31,937 -->
00:02:33,238
So we've actually talked about this a lot.
50
00:02:33,238 -->
00:02:41,474
Like how much do we want to go down to computer use, which is like a pretty sexy space
right now versus how much do we want to avoid computer use where an app might take over
51
00:02:41,474 -->
00:02:46,187
your computer and be doing work for you on your laptop and prevent you from doing other
work.
52
00:02:46,187 -->
00:02:51,621
Our philosophy is more, how can we keep people in flow as much as possible and instead do
tasks in the background?
53
00:02:51,621 -->
00:02:53,302
So we don't take over your computer at all.
54
00:02:53,302 -->
00:02:55,624
All this happens just behind the scenes for you.
55
00:02:55,624 -->
00:02:58,656
And all you have to do is click approve in the app afterwards.
56
00:02:58,656 -->
00:03:01,027
So it's all API based.
57
00:03:01,550 -->
00:03:01,930
Cool.
58
00:03:01,930 -->
00:03:04,352
uh Sounds cool to me.
59
00:03:04,533 -->
00:03:06,634
So let's back up a little bit maybe.
60
00:03:07,115 -->
00:03:09,577
Where did this idea come from?
61
00:03:09,577 -->
00:03:15,270
And was it informed at all at your time at Loom, where I know you spent a few years at?
62
00:03:15,801 -->
00:03:18,542
Yeah, so this first came up, me and my co-founder were working together.
63
00:03:18,542 -->
00:03:23,584
My co-founder, Rajiv, is a phenomenal designer that I got to work with really closely over
the past couple years.
64
00:03:23,584 -->
00:03:29,327
And we were just jamming on ideas, talking about things that really pissed us off at our
job.
65
00:03:29,327 -->
00:03:37,650
And one of those things was just, it feels like there's gotta be a better way to take the
ideas that you have in your head and get them into the places that you're doing work.
66
00:03:37,650 -->
00:03:45,457
I was a product manager, so I had to write a bunch of docs and then sometimes rewrite them
as we got new updates or were presenting to a new audience.
67
00:03:45,457 -->
00:03:48,877
And it was a case of, I know exactly what I want to write.
68
00:03:48,877 -->
00:03:50,317
have the ideas in my head.
69
00:03:50,317 -->
00:03:58,377
How can we like just take all the different pieces of context across like the apps that we
use and then let me get my ideas out and then just have it taken care of.
70
00:03:58,377 -->
00:04:01,536
And so we started talking about that much earlier this year.
71
00:04:01,536 -->
00:04:06,517
We both decided that we were going to leave our jobs and start a startup, but we actually
ended up on a totally different track.
72
00:04:06,517 -->
00:04:11,637
Like we kind of just left this idea to the side and started working on like go to market
tooling instead.
73
00:04:11,757 -->
00:04:12,816
Uh, and then.
74
00:04:12,816 -->
00:04:15,196
After a couple months of that, we decided it was time to pivot.
75
00:04:15,196 -->
00:04:16,916
And so we kind of circled back to this idea.
76
00:04:16,916 -->
00:04:18,216
We were like, wait a second.
77
00:04:18,716 -->
00:04:20,216
One, we still have this pain point.
78
00:04:20,216 -->
00:04:22,516
Like, is this something that we absolutely want now?
79
00:04:22,516 -->
00:04:24,636
And definitely would have used it at our last jobs.
80
00:04:24,636 -->
00:04:26,936
Two, it's a space that we know much better.
81
00:04:26,936 -->
00:04:31,436
And it's like a motion as a startup that we think that we have a experience in.
82
00:04:31,436 -->
00:04:36,976
And so we started chipping away at it and just like put together the scrappiest prototype
you could possibly imagine.
83
00:04:36,976 -->
00:04:38,756
And we're like, all right, there's something here.
84
00:04:38,756 -->
00:04:40,356
Let's keep pulling on this thread.
85
00:04:41,178 -->
00:04:41,980
That's what it's about.
86
00:04:41,980 -->
00:04:45,806
I mean, it's kind of you throw some things out there.
87
00:04:45,806 -->
00:04:50,003
Maybe their original visions, maybe their inspiration, something you see or a problem that
you deal with.
88
00:04:50,003 -->
00:04:53,308
And then when you start to get some signal, you just like keep going down that path.
89
00:04:53,308 -->
00:04:55,280
That's kind of that's kind how these things go.
90
00:04:55,386 -->
00:04:55,936
For sure.
91
00:04:55,936 -->
00:05:01,389
we spent, I mean, like in the middle of all that, you know, I think it's safe to say that
we were in pivot hell for a little while, right?
92
00:05:01,389 -->
00:05:07,853
We're like, we'd had this idea a while back, but sometimes when you have like that
familiar idea, you kind of just like let it fester in your brain, but you don't like
93
00:05:07,853 -->
00:05:09,504
actually pay it too much credibility.
94
00:05:09,504 -->
00:05:11,395
And so we were trying everything else that could imagine.
95
00:05:11,395 -->
00:05:17,768
Like we spent like, you know, a couple of weeks cycling through ideas, like uh AIQA
engineer.
96
00:05:17,768 -->
00:05:25,392
um For about four hours, we were talking about like automotive industry, like agents.
97
00:05:25,392 -->
00:05:29,672
And then we were like, quickly like, we're not, we're not, this is not a space that we
know, we should not do that.
98
00:05:29,672 -->
00:05:34,872
And then we kind of just took a day of like, all right, let's like, let our brains like
reset a little bit.
99
00:05:34,872 -->
00:05:38,052
And then it kind of came back to, okay, wait, let's solve a problem for ourselves.
100
00:05:38,052 -->
00:05:39,212
Like, this is a cool idea.
101
00:05:39,212 -->
00:05:40,584
Like, let's see where it goes.
102
00:05:41,646 -->
00:05:54,186
So I'm kind of curious, you saw a evolution of a product in a company in Loom, I think you
were fairly early, at least I know you were there for several years, right?
103
00:05:54,186 -->
00:05:57,026
And you were there through exit and then you left to do this.
104
00:05:57,666 -->
00:06:07,046
What's compare and contrast, what's it like working, what was it like at Loom where you
kind of had a job and a function and you probably had a boss and there was organization?
105
00:06:07,116 -->
00:06:15,053
Comparing that to where you're at now where you just said you were at Pivot Hell, you
don't have a boss, it's just you and your co-founder figuring it out, you call the shots.
106
00:06:15,153 -->
00:06:19,898
What's the differences, are there any similarities between the two experiences?
107
00:06:20,088 -->
00:06:21,149
Yeah, for sure.
108
00:06:21,149 -->
00:06:26,832
I mean, it's definitely different, but a lot, there were so many learnings that I took
from Loom that have been so helpful now.
109
00:06:26,832 -->
00:06:35,056
Loom, I got very lucky in that Loom was like such a good environment to prepare you for a
startup and that however much ownership that you wanted, you were able to get.
110
00:06:35,056 -->
00:06:41,500
And so even when I was a software engineer intern, like I would just ask like, Hey, can I
like write the PRD for this project?
111
00:06:41,500 -->
00:06:46,842
And like, I was able to do that and like take on much more scope and you know, an intern
might normally be able to.
112
00:06:46,903 -->
00:06:49,198
And you know, as I, as I,
113
00:06:49,198 -->
00:06:53,331
spent more time at Lume and I switched from software engineering to being a product
manager.
114
00:06:53,812 -->
00:06:58,015
The scope kept increasing and the team just tried to move like as quickly as possible.
115
00:06:58,015 -->
00:07:07,542
And so a lot of the speed and a lot of the pressure of like, okay, how can we build like a
beautiful product that's as easy to use as possible and continue to grow the business?
116
00:07:07,542 -->
00:07:11,725
I think are like very similar feelings to now, except it was a little bit more on rails,
right?
117
00:07:11,725 -->
00:07:13,126
Like I had a much smaller scope.
118
00:07:13,126 -->
00:07:14,607
We already had product market fit.
119
00:07:14,607 -->
00:07:16,420
And so it was really just a matter of like.
120
00:07:16,420 -->
00:07:17,791
Like the distribution was already there.
121
00:07:17,791 -->
00:07:21,723
And if we built a new feature set, it kind of just got tax on top of that.
122
00:07:21,743 -->
00:07:25,145
Whereas now you're starting from zero.
123
00:07:25,145 -->
00:07:26,065
You got nothing.
124
00:07:26,065 -->
00:07:30,568
It's a lot of that familiarity of like, okay, we just build a great new feature.
125
00:07:30,568 -->
00:07:33,519
We'll get maybe like just a small subset of users who start using it.
126
00:07:33,519 -->
00:07:37,331
And then from there, we're able to like continue to grow it and like continue to add
value.
127
00:07:37,331 -->
00:07:38,512
You're starting with nothing.
128
00:07:38,512 -->
00:07:46,636
And in our case, voice is something that we like fundamentally believe is going to be a
huge part.
129
00:07:46,638 -->
00:07:50,871
or maybe even like the primary medium that people work through.
130
00:07:50,871 -->
00:07:53,213
But it's like still learned behavior for a lot of people.
131
00:07:53,213 -->
00:07:57,456
And like that's something that Lume faced really early on, it's something that we were
still dealing with when I was there.
132
00:07:57,456 -->
00:08:05,181
But now for us, it's not just that voice is a new medium, it's that doing work in this way
is a completely new behavior.
133
00:08:05,181 -->
00:08:07,743
And so there's a lot more to figure out.
134
00:08:07,743 -->
00:08:09,224
There's a lot less structure.
135
00:08:09,224 -->
00:08:13,507
The hours are certainly longer, uh but both have been great.
136
00:08:15,220 -->
00:08:17,893
And remind me, I actually don't know the answer to this.
137
00:08:17,893 -->
00:08:19,776
Right now you're in SF.
138
00:08:19,776 -->
00:08:22,459
Were you in SF when you were at Loom?
139
00:08:22,459 -->
00:08:25,422
Or have you only recently moved to SF?
140
00:08:25,751 -->
00:08:27,792
We just moved to SF for Y Combinator.
141
00:08:27,792 -->
00:08:29,832
So uh usually live in New York.
142
00:08:29,832 -->
00:08:32,873
We were lucky enough to get into Y Combinator in September.
143
00:08:32,873 -->
00:08:36,115
So been here since September and then we'll be here through the end of the year.
144
00:08:36,115 -->
00:08:40,096
So uh then this is the longest time I've spent in San Francisco, honestly.
145
00:08:40,096 -->
00:08:49,219
The first, I think the first, one of the first times that I was there, I actually slept on
your couch when I messed up my flight scheduling, if you remember that.
146
00:08:49,615 -->
00:08:52,759
Um, was this 2019?
147
00:08:52,759 -->
00:08:54,200
This was 2019, yeah.
148
00:08:54,200 -->
00:08:57,983
This was when you were doing a startup.
149
00:08:57,983 -->
00:09:07,170
I was going to TreeHacks for a hackathon and I had a layover in Dallas and I checked my
phone because I was like, I feel like I should have gotten some information about where
150
00:09:07,170 -->
00:09:08,470
I'm going to stay.
151
00:09:08,571 -->
00:09:09,852
Didn't get any of that.
152
00:09:09,852 -->
00:09:13,494
And then realized I booked my flight a day earlier than I was supposed to.
153
00:09:13,494 -->
00:09:17,357
And frantically tried to figure out who I knew who was in San Francisco.
154
00:09:17,357 -->
00:09:20,302
And you were kind enough to let me sleep on your couch that night.
155
00:09:20,302 -->
00:09:23,402
That was a flashback then that was was Pup Loft era.
156
00:09:23,402 -->
00:09:24,922
That's crazy.
157
00:09:24,922 -->
00:09:26,242
That's crazy.
158
00:09:26,622 -->
00:09:32,062
Okay, so so you just moved to SF you're gonna be there for a few more months.
159
00:09:32,602 -->
00:09:43,362
What's it tell me like I feel like if you've never been to SF like not you just in general
if you're listening to this you've never been to SF it's impossible to understand that
160
00:09:43,362 -->
00:09:47,962
culture of tech and like what the set the gravity is like being there.
161
00:09:47,962 -->
00:09:48,748
Oh you're there.
162
00:09:48,748 -->
00:09:49,753
And you're not always there, right?
163
00:09:49,753 -->
00:09:50,315
You just moved.
164
00:09:50,315 -->
00:09:53,438
yeah, tell us what's it been like since you moved?
165
00:09:53,528 -->
00:10:01,553
Yeah, a couple of weeks ago I was talking to my co-founder about this because he is from
SF and then I was in the middle of convincing him to move to New York when we got into Y
166
00:10:01,553 -->
00:10:03,656
Combinator and then we just like whipped it right back.
167
00:10:03,656 -->
00:10:11,142
um And I was telling him that there's like a tangible feeling of being at the epicenter of
innovation in San Francisco.
168
00:10:11,202 -->
00:10:21,150
It's hard to describe, but there's like everywhere that you go, you're seeing like
companies that are on the cutting edge with whether it's like billboards and just ads for
169
00:10:21,150 -->
00:10:22,563
like everything tech.
170
00:10:22,563 -->
00:10:31,030
You know, like that's like the dominant like advertising is like AI for video or like
startup banks, things like that.
171
00:10:31,190 -->
00:10:33,072
You see self-driving cars everywhere.
172
00:10:33,072 -->
00:10:37,756
Like that is going to become much more normal, but like this is the center of all of it.
173
00:10:37,756 -->
00:10:44,621
And so much of the social scene also revolves around like tech startups.
174
00:10:44,982 -->
00:10:46,083
It's unlike anywhere else.
175
00:10:46,083 -->
00:10:48,564
And I feel like, you know, I love New York city.
176
00:10:48,564 -->
00:10:51,105
It's my favorite place, but like the
177
00:10:51,105 -->
00:10:54,858
It all starts in San Francisco and then it eventually triples over into these other
cities.
178
00:10:55,982 -->
00:11:05,479
Well, so this is where I'm in Phoenix, obviously, as you know, and I think the perception
outside of SF is that SF and New York are the top two hubs.
179
00:11:05,479 -->
00:11:06,629
And it's true.
180
00:11:06,629 -->
00:11:15,415
But what I don't think people realize, and I'm curious to get your opinion on this, is how
far apart number one and number two is.
181
00:11:15,636 -->
00:11:20,999
Like, you you were at a hot company, you were in New York, obviously you're in the mix.
182
00:11:20,999 -->
00:11:23,861
Honestly, I'm just genuinely curious.
183
00:11:23,861 -->
00:11:24,942
Like, it is...
184
00:11:24,942 -->
00:11:26,262
Are they comparable?
185
00:11:26,262 -->
00:11:32,602
Is SF, there's like 10,000 miles ahead, and then it's New York and then it's Boston or LA
or whatever?
186
00:11:32,742 -->
00:11:40,642
Or is New York kind of closer than one may think to SF when it comes to just like tech
progress and tech scene?
187
00:11:41,178 -->
00:11:45,749
think New York has made a lot of progress in terms of tech density in the past couple
years.
188
00:11:46,090 -->
00:11:51,392
You have some absolutely killer companies over there like Ramp, Clay, plenty of others.
189
00:11:51,392 -->
00:11:52,912
And so it's definitely there.
190
00:11:52,912 -->
00:11:58,084
I think that San Francisco just has such a dominant density of tech that it feels
different.
191
00:11:58,084 -->
00:11:59,535
There's definitely a gap.
192
00:11:59,535 -->
00:12:00,545
You can find it in New York.
193
00:12:00,545 -->
00:12:04,477
You just have to search for it and be a little bit more purposeful about it.
194
00:12:04,477 -->
00:12:08,999
But in San Francisco, the default is that you're living in a tech-first world.
195
00:12:08,999 -->
00:12:10,579
It smacks you in the face, for sure.
196
00:12:10,579 -->
00:12:13,582
you get off of the plane, there's tech ads everywhere.
197
00:12:13,582 -->
00:12:15,402
Every ad is a tech ad, like you said.
198
00:12:15,402 -->
00:12:15,863
comical.
199
00:12:15,863 -->
00:12:20,483
If I see one more sign that says lock in, I'm going to lose it to be honest with you.
200
00:12:21,303 -->
00:12:24,023
everywhere you go, you talk to someone.
201
00:12:24,023 -->
00:12:29,982
They probably work in tech, whereas in New York, feel like if you just talk to a stranger,
your odds are just way lower.
202
00:12:29,982 -->
00:12:31,703
And so it definitely has a different feel.
203
00:12:32,174 -->
00:12:33,034
Totally.
204
00:12:33,054 -->
00:12:34,914
Well, you mentioned you're in YC.
205
00:12:35,374 -->
00:12:40,914
You know, what is like, I don't even know what to ask about it other than just like,
what's that like?
206
00:12:40,914 -->
00:12:45,814
Are you, has it maybe changed how you think about your startup before you got in?
207
00:12:45,814 -->
00:12:49,654
And just feel free to share anything that you want to about that experience.
208
00:12:49,773 -->
00:12:51,023
Yeah, for sure.
209
00:12:51,023 -->
00:12:58,936
YC has definitely changed our perception of our startup and in a very positive way.
210
00:12:58,936 -->
00:13:02,146
And I also just think it's changed us as founders in a positive way too.
211
00:13:02,146 -->
00:13:10,299
Like Y Combinator at the end of the day adds like a tremendous amount of time pressure,
which is very purposeful because you're all, you know, it starts in September for the fall
212
00:13:10,299 -->
00:13:10,719
batch.
213
00:13:10,719 -->
00:13:11,639
part of like F25.
214
00:13:11,639 -->
00:13:18,991
It starts in September and then you're all just racing towards demo day, which is in like
early December and
215
00:13:19,715 -->
00:13:26,999
That process just means that you have to build as quickly as you can a great business to
be able to present in December.
216
00:13:26,999 -->
00:13:37,565
And so, you know, before we got into YC, like I quit my job in July, uh basically with the
plan, like the concept of a plan, you know, like, okay, we'll figure it out.
217
00:13:37,565 -->
00:13:39,445
Like we'll find something to do.
218
00:13:39,506 -->
00:13:41,116
And the cycles were just much slower.
219
00:13:41,116 -->
00:13:49,719
Like there was less urgency despite, you know, bootstrapping and like, obviously like
working hard, but when you have that like legit time pressure,
220
00:13:49,719 -->
00:13:51,180
It just completely changes the game.
221
00:13:51,180 -->
00:14:00,503
And so it's done a great job of, for us, like as we were trying to figure out something
that even remotely resembles product market fit, ah or like an idea that we have like a
222
00:14:00,503 -->
00:14:03,675
lot of conviction in, it made the cycle so much faster.
223
00:14:03,675 -->
00:14:10,367
You really have to say like, okay, we're going to like validate or invalidate this thing
in as quick a time as possible.
224
00:14:10,367 -->
00:14:12,948
And so that alone has been tremendously helpful.
225
00:14:12,948 -->
00:14:15,749
And on top of that, it's just like a phenomenal community.
226
00:14:15,749 -->
00:14:17,486
You know, there's like a hundred in...
227
00:14:17,486 -->
00:14:21,427
50 I think companies that are all in the batch that you get to meet the founders of.
228
00:14:21,427 -->
00:14:30,350
You get to commiserate about all the ways that your businesses are challenging and all the
fires that you're putting out all the time.
229
00:14:30,350 -->
00:14:31,671
Get advice from people.
230
00:14:31,671 -->
00:14:37,212
And so ah it's been a crazy experience, but it's been absolutely amazing.
231
00:14:37,212 -->
00:14:38,433
We're still in the thick of it right now.
232
00:14:38,433 -->
00:14:42,484
And so we're deep in the trenches, but wouldn't trade it for anything.
233
00:14:43,502 -->
00:14:43,822
Yeah.
234
00:14:43,822 -->
00:14:47,222
For what I've heard, it's like, just want to move faster.
235
00:14:47,222 -->
00:14:49,002
It's this pressure, right?
236
00:14:49,002 -->
00:14:50,582
It's super smart.
237
00:14:51,222 -->
00:14:55,762
So I want to go a little back to product and like maybe how you're thinking about things.
238
00:14:55,762 -->
00:14:57,822
Don't spill any sauce, of course.
239
00:14:58,262 -->
00:15:01,222
But look, things are moving super quick with AI, right?
240
00:15:01,222 -->
00:15:10,162
I mean, like new models are coming out, you know, every, you know, in three months, people
say like three months ago today would be unrecognizable and the same will be said in three
241
00:15:10,162 -->
00:15:10,942
months.
242
00:15:10,942 -->
00:15:12,588
So how do you know?
243
00:15:12,588 -->
00:15:18,038
what to build and how do you know when to change things if new models come out?
244
00:15:18,038 -->
00:15:21,209
Or just like, how do you, how are you managing this fast paced environment?
245
00:15:21,209 -->
00:15:22,750
Pretty much is the question.
246
00:15:23,234 -->
00:15:25,955
think that there's two ways that we think about it.
247
00:15:25,955 -->
00:15:32,758
One is like the core product, and then two is like the tech that goes behind the scenes to
enable the core product.
248
00:15:32,938 -->
00:15:36,579
And the first one I think is what has to drive the vision of the direction.
249
00:15:37,100 -->
00:15:47,354
the second piece, the technology, is I think mostly dependent on the first, where our
mission right now is really just like talk to users, get their feedback, figure out how we
250
00:15:47,354 -->
00:15:51,779
can drive the most value possible, and build something that even if it's like a...
251
00:15:51,779 -->
00:15:56,222
the first build being super scrappy, uh people go, oh, there's something really cool here.
252
00:15:56,222 -->
00:15:57,983
I want XYZ.
253
00:15:58,043 -->
00:16:00,785
I'll use it even more if you give me these other features.
254
00:16:00,785 -->
00:16:05,208
That's what we were really hunting for and has been our North Star above all else.
255
00:16:05,208 -->
00:16:12,072
Behind the scenes, have, yeah, every three months they're dropping a new model that does
some crazy new capability.
256
00:16:12,132 -->
00:16:21,570
And so for us, it's about being pretty analytical for each of the different models ah that
are available, different like,
257
00:16:21,570 -->
00:16:25,554
frameworks and technologies, what does that unlock for us to drive more value?
258
00:16:25,554 -->
00:16:34,643
And so if there's like a new multimodal model that drops and we're able to like even
faster use context from like a user screen or something like that, then we like seriously
259
00:16:34,643 -->
00:16:35,234
consider it.
260
00:16:35,234 -->
00:16:41,490
But with the core question of, how can this make the product faster, better, ah and go
from there.
261
00:16:43,032 -->
00:16:53,087
Could you maybe give me one or two other use cases or ways that I'd be able to use the
product today or once it's built, you know, available to test?
262
00:16:53,087 -->
00:16:54,628
And I guess that's a second question.
263
00:16:54,628 -->
00:16:56,198
Is there something to test?
264
00:16:56,198 -->
00:16:57,279
Like, could I beta test it?
265
00:16:57,279 -->
00:16:58,099
Are you still building it?
266
00:16:58,099 -->
00:16:59,720
Where are you at with like development?
267
00:16:59,756 -->
00:17:05,488
Yeah, right now we're building out a wait list and then we're keeping a pretty tight group
of private beta testers at the moment.
268
00:17:05,488 -->
00:17:08,929
And so there is a product to test and we're just keeping it pretty tight.
269
00:17:08,929 -->
00:17:19,071
We have, this is the type of product that we like just really believe we have to meet a
very high level of like craft for us to like truly make something that people will be
270
00:17:19,071 -->
00:17:19,892
using every day.
271
00:17:19,892 -->
00:17:26,974
And so we've been very intentional about making sure that it's reliable, it's fast and
that it just works.
272
00:17:26,974 -->
00:17:28,834
uh So.
273
00:17:28,972 -->
00:17:29,912
That's where we're at right now.
274
00:17:29,912 -->
00:17:37,885
We do have a product we've been just, we're sprinting towards building out mostly towards
making it even faster uh first.
275
00:17:37,885 -->
00:17:44,407
And then in terms of like the different use cases that folks are using it for, one of them
honestly is even just dictation.
276
00:17:44,407 -->
00:17:52,129
So we offer like a, like that's like been a very quickly growing market recently is
letting people just instead of typing, just talk and then drop their texts in anywhere.
277
00:17:52,129 -->
00:17:55,540
So that's been a piece of the product that we've built out.
278
00:17:55,778 -->
00:18:03,012
Calendar has been a big hit as folks are doing sales quite a lot and don't want to have to
worry about setting up meetings, creating new calendar events, sending it over to people
279
00:18:03,012 -->
00:18:04,534
afterwards with details.
280
00:18:04,814 -->
00:18:08,837
oh So are you saying let's say after you know, we end this podcast.
281
00:18:08,837 -->
00:18:17,274
Let's say I'm coming to SF I'm not let's say I am and let's you know, let's meet up at
Phil's on South Park or you know, we bought all South Park, know on Wednesday at four
282
00:18:17,274 -->
00:18:25,040
o'clock I could press a little button say he's making an invite, know for me and Connor or
Phil's, know, whatever, know details and it makes that calendar invite.
283
00:18:25,040 -->
00:18:26,251
Is that correct?
284
00:18:27,212 -->
00:18:28,773
That's crazy.
285
00:18:28,833 -->
00:18:29,993
That's cool
286
00:18:30,156 -->
00:18:31,347
Yeah, it did.
287
00:18:31,347 -->
00:18:39,534
It's been so fun to build out and like the first time that we get some of these like
different integrations working and we like basically unlock a whole new capability for the
288
00:18:39,534 -->
00:18:40,434
users.
289
00:18:40,535 -->
00:18:47,881
It's pretty sweet seeing it work live and getting a sense of like how it's changed just
how like me and Rajiv work has been so cool.
290
00:18:47,881 -->
00:18:58,232
em And yeah, we have really been focused on, you know, for our old jobs, what are the
things that we really would have wanted to just like.
291
00:18:58,232 -->
00:19:00,335
do in the background not have to worry about.
292
00:19:00,335 -->
00:19:03,250
And so those have been the types of use cases that we're sprinting towards.
293
00:19:03,250 -->
00:19:08,808
then as we talk to more users, it's just been so helpful to figure out where we're going
to take it.
294
00:19:09,102 -->
00:19:13,422
So how do you think about, may not have an answer to this, I'm like, that's fine, I'm just
curious.
295
00:19:13,422 -->
00:19:14,702
Obviously there's a limit.
296
00:19:14,702 -->
00:19:21,062
There's the basics, is listen, transcribe what I'm saying and put it into text.
297
00:19:21,142 -->
00:19:30,422
And then there's, hey, Katty, edit this whole podcast, publish it on my podcast player and
share it on social media.
298
00:19:30,422 -->
00:19:32,282
I doubt it can do that yet, right?
299
00:19:32,282 -->
00:19:36,034
So where is your goal to eventually get it?
300
00:19:36,034 -->
00:19:41,196
Is that like a directional goal to be able to have it do that if you want?
301
00:19:41,197 -->
00:19:43,154
Is there a different direction you're going in?
302
00:19:43,154 -->
00:19:49,330
And I guess, how do you think about the line on when it's functional versus when it's
like, it's not functional?
303
00:19:49,330 -->
00:19:50,871
That was kind of three questions all jumbled up.
304
00:19:50,871 -->
00:19:52,680
Feel free to take that however you want.
305
00:19:52,680 -->
00:19:54,151
Yeah, yeah, yeah.
306
00:19:54,511 -->
00:20:03,037
I think for us, right now at least, the vision is in that direction.
307
00:20:03,037 -->
00:20:15,065
Like, how can we take care of the tasks that like all the context is there for and just
knock out like the busy work, the manual process, almost just like the interface with
308
00:20:15,065 -->
00:20:17,086
which you do that task for you.
309
00:20:17,086 -->
00:20:20,549
And so the example that you gave of like, okay, edit this podcast for me.
310
00:20:20,549 -->
00:20:21,599
I think that
311
00:20:21,729 -->
00:20:23,090
Directionally like that's right.
312
00:20:23,090 -->
00:20:33,015
I think that the part that we are most excited about is how can we take like your unique
point of view because this podcast like has such a following and uh Has been around for so
313
00:20:33,015 -->
00:20:42,010
long like because of like your perspective on founders and on venture capital and startups
and so how can we best capture like the intent that you have for what the podcast should
314
00:20:42,010 -->
00:20:47,824
look like and then Transform that into like the actions that an agent takes to kind of
reach your vision.
315
00:20:47,824 -->
00:20:50,711
And so in that example was for like podcasting
316
00:20:50,711 -->
00:21:01,374
And then for a work example, or like a tech company work example, it might be like
creating a strategy doc based on the inputs from your data platform plus the user research
317
00:21:01,374 -->
00:21:08,406
that you have, plus some product manager or designer or other leaders, like unique take on
where the business needs to go.
318
00:21:08,406 -->
00:21:18,081
And so our goal is to capture all the context that you have in the tools that you use,
plus your unique point of view so that your workday becomes much more about.
319
00:21:18,081 -->
00:21:23,665
your perspective on what needs to happen and less about how you're actually interfacing
with the tools that you use every day.
320
00:21:24,526 -->
00:21:25,566
Yeah, it makes sense.
321
00:21:25,566 -->
00:21:30,406
got shipped friend yesterday, you know, like friend dot com.
322
00:21:30,426 -->
00:21:34,066
I forgot that I ordered it or pre-ordered it or something.
323
00:21:34,066 -->
00:21:37,486
I, cause it was a bit, I was thinking I was kind of early, got shipped it.
324
00:21:37,486 -->
00:21:38,906
My wife was like, Hey, what's this?
325
00:21:38,906 -->
00:21:41,105
I'm like, Oh, it's Fred.
326
00:21:41,266 -->
00:21:41,926
Right.
327
00:21:41,926 -->
00:21:43,046
Uh, this is pretty cool.
328
00:21:43,046 -->
00:21:45,846
So, um, and I was wearing it and like, it's building context.
329
00:21:45,846 -->
00:21:47,906
And it's like, I'm curious what your opinion is.
330
00:21:47,906 -->
00:21:49,566
And no one has a final thought on this.
331
00:21:49,566 -->
00:21:52,486
Like it's, it's an evolving conversation.
332
00:21:52,686 -->
00:21:54,314
Oh, you know, I like.
333
00:21:54,314 -->
00:21:58,798
You know, my phone probably has context on me, like friend has context on me.
334
00:21:58,798 -->
00:22:01,200
Then there's a company that I'm involved with called Super Memory.
335
00:22:01,200 -->
00:22:03,142
That's like great shared, shared context.
336
00:22:03,142 -->
00:22:06,514
um But I feel like context is like a big deal.
337
00:22:06,514 -->
00:22:11,769
again, no, please don't share any like secret stuff.
338
00:22:11,769 -->
00:22:14,011
But it's like, how do you think about context?
339
00:22:14,011 -->
00:22:17,414
Like, I don't even I don't even know what the question is.
340
00:22:17,414 -->
00:22:19,175
But like context is the king.
341
00:22:19,175 -->
00:22:21,187
So how do you make sure you're able to get it?
342
00:22:21,187 -->
00:22:22,350
Are you going to have your own?
343
00:22:22,350 -->
00:22:24,602
Are you gonna work with a super memory type stuff?
344
00:22:24,602 -->
00:22:27,283
Is there a different paradigm that I'm not thinking about?
345
00:22:28,001 -->
00:22:30,533
I mean, I think that the paradigm that you're thinking about is the right one.
346
00:22:30,533 -->
00:22:40,069
Like for any, I think that the world that we're moving towards really is that any AI tool
that you're using is gonna try and get as much context as possible to make the outputs as
347
00:22:40,069 -->
00:22:40,830
good as possible.
348
00:22:40,830 -->
00:22:49,816
Because, you know, like all these LLMs are great, but they're really only as valuable for
you and your specific use case as they have context that like actually meets your needs.
349
00:22:49,816 -->
00:22:56,081
And so that they can tailor it to your tone, the products that you're using, like what
else is going on?
350
00:22:56,081 -->
00:22:57,081
And so,
351
00:22:57,707 -->
00:23:03,269
I think that every company is going to be trying to figure out how can we capture as much
context as we possibly can.
352
00:23:03,269 -->
00:23:05,200
And of course, like we have to think about that too.
353
00:23:05,200 -->
00:23:12,263
um And I think that for us in particular, one of the most important things that we think
about is like tone.
354
00:23:12,263 -->
00:23:22,157
How do we make sure that whatever the output is really like, you're, if you're trying to
write a new, you know, uh update for the podcast, like how can we make sure that that's
355
00:23:22,157 -->
00:23:27,359
like a match Sherman update and not just like chat, GPT, dash is all over the place.
356
00:23:27,554 -->
00:23:27,964
Totally.
357
00:23:27,964 -->
00:23:36,560
Well, I feel like I share an opinion that some people share, maybe, that it's like, in
some ways, AI is incredible.
358
00:23:36,560 -->
00:23:37,831
It's like, what an innovation.
359
00:23:37,831 -->
00:23:39,002
Holy smokes.
360
00:23:39,002 -->
00:23:40,903
But it's not.
361
00:23:40,943 -->
00:23:47,607
I do think there's a long way to go because I feel like there's folks that claim they can
do what you're talking about.
362
00:23:48,048 -->
00:23:52,001
you know, whether it be lovable or like Trash BT itself, it has all this context on me.
363
00:23:52,001 -->
00:23:54,412
And it's just missing the mark.
364
00:23:54,412 -->
00:23:57,070
And I just think maybe the models need to get better.
365
00:23:57,070 -->
00:23:58,170
There needs to be more innovation.
366
00:23:58,170 -->
00:24:07,053
I don't quite know, but it's going to be wild when these models are good enough for this
founders like you that have figured out how to like quite like get that balance to capture
367
00:24:07,053 -->
00:24:08,883
someone's taste, capture someone's tone.
368
00:24:08,883 -->
00:24:11,204
Because that's when things get real interesting.
369
00:24:11,204 -->
00:24:13,645
Like I don't want an AI clone that talks not like me.
370
00:24:13,645 -->
00:24:19,066
If I can get someone that talks just like me, same facial expressions, whatever, that's
where things get wild.
371
00:24:19,066 -->
00:24:21,937
And then I can put that on a robot on a freaking 1X.
372
00:24:21,937 -->
00:24:24,378
No, the crazy stuff.
373
00:24:24,965 -->
00:24:32,235
It's the I Can't wait till we have a robot mat we got to make that happen.
374
00:24:32,235 -->
00:24:35,939
We might It's crazy
375
00:24:35,939 -->
00:24:37,861
Yeah, yeah, sorry, I you off.
376
00:24:37,940 -->
00:24:39,060
No, you're good, dude, you're good.
377
00:24:39,060 -->
00:24:47,593
um I agree, because the models do a really good job of making you think that they're
unbelievable and that they have it all figured out.
378
00:24:47,593 -->
00:24:52,324
how many times have like, okay, I spend most of my day coding right now.
379
00:24:52,464 -->
00:24:58,146
So many times you put together a plan and whatever coding tool that you use is like, dude,
this is it.
380
00:24:58,146 -->
00:24:59,386
It's gonna work.
381
00:24:59,386 -->
00:25:00,576
Trust me, I got it.
382
00:25:00,576 -->
00:25:04,697
This is the best plan I've ever seen.
383
00:25:04,697 -->
00:25:05,508
Just let it rip.
384
00:25:05,508 -->
00:25:07,358
And then you do and you're like,
385
00:25:07,754 -->
00:25:08,955
that did not work at all.
386
00:25:08,955 -->
00:25:11,506
And then you ask it and it goes, of course that didn't work.
387
00:25:11,506 -->
00:25:12,406
What are you talking about?
388
00:25:12,406 -->
00:25:21,472
eh And so I agree with you that they're like, we're still a few iterations of like
innovation away from like some of this just like default working.
389
00:25:21,472 -->
00:25:31,917
And so in the meantime, em that's like, I think great news for founders because then you
get, I think even more room for you to find what your special sauce is and to be able to
390
00:25:31,917 -->
00:25:37,352
like continue to iterate and dig deep on like, okay, how can you make this as valuable as
possible for folks?
391
00:25:37,352 -->
00:25:45,276
Even if like you don't just have AGI that you can drop in and say like, all right, it's
just going to automatically draft something in my total voice.
392
00:25:46,062 -->
00:25:54,762
Yeah, that that's gonna future is gonna be gonna be gonna be wild It does lead me to my
next question like you're an SF all this stuff is getting started there What are you like,
393
00:25:54,762 -->
00:26:04,022
know, you know in their batch just on the streets at the events Like what are you seeing
that's blowing your mind that may not be may not have permeated to the rest of the world
394
00:26:04,022 -->
00:26:05,682
yet technology wise
395
00:26:07,806 -->
00:26:16,601
I think the thing that I think about a lot, and this is probably my bias from the Loom
Days showing, but video and AI is still so early and it's already so good.
396
00:26:16,601 -->
00:26:26,437
There's quite a few companies in the batch that are working on some form or factor of AI
for video, and it's sick.
397
00:26:26,437 -->
00:26:31,049
It's a little frightening too, just in terms of how good some of these SORA 2 videos are.
398
00:26:31,049 -->
00:26:36,224
um But we've had so many launch videos that...
399
00:26:36,224 -->
00:26:38,565
are all AI generated and they're great.
400
00:26:38,565 -->
00:26:50,432
um So on top of just the short form content that you see, people are gonna start putting
together really high production value and they already are, video content that's almost
401
00:26:50,432 -->
00:26:52,173
entirely AI generated.
402
00:26:52,173 -->
00:26:54,825
And that's one piece of it.
403
00:26:54,825 -->
00:27:02,418
think the video generation piece is super cool and also a little scary just in terms of
how good that it's getting.
404
00:27:02,719 -->
00:27:04,880
The other part of it is
405
00:27:04,982 -->
00:27:14,749
Processing video as like an input uh for AI models that is still a piece that I think
Gemini has done really well But I haven't actually seen a ton of other folks like fully
406
00:27:14,749 -->
00:27:26,487
utilizing uh that I'm like always interested in because You know talking about context
like that's the best way to get any sort of context is capture the video the audio Like
407
00:27:26,487 -->
00:27:29,859
how much can you how much can you pull from a video versus just like a text interaction?
408
00:27:29,859 -->
00:27:34,516
Yeah, I haven't seen too much of that like in our badge or
409
00:27:34,516 -->
00:27:36,954
in the Bay, but it's something that I think about a lot.
410
00:27:37,336 -->
00:27:38,007
Totally.
411
00:27:38,007 -->
00:27:41,519
Well, just like Marc Andreessen says, know, every idea is a good idea.
412
00:27:41,519 -->
00:27:43,590
It just needs to come out at the right time.
413
00:27:43,590 -->
00:27:44,591
Time in the cycle, right?
414
00:27:44,591 -->
00:27:45,931
And time in the market.
415
00:27:45,992 -->
00:27:48,193
So it sounds like that time may be upcoming for that.
416
00:27:48,193 -->
00:27:48,754
Who knows?
417
00:27:48,754 -->
00:27:53,236
um couple more questions, then we'll kind of round it out.
418
00:27:53,237 -->
00:27:57,289
what is your, like you're an SF, you're in the batch, you know, YC.
419
00:27:57,289 -->
00:27:59,991
Are you just grinding 14 hours a day?
420
00:27:59,991 -->
00:28:01,702
Like, do you socialize at all?
421
00:28:01,702 -->
00:28:04,064
Do you like, you know, yeah, what is your day to day?
422
00:28:04,064 -->
00:28:07,246
Like, you know, your average, if you have to pick your most average day,
423
00:28:07,246 -->
00:28:07,706
What do you do?
424
00:28:07,706 -->
00:28:08,806
What do you spend your time on?
425
00:28:08,806 -->
00:28:11,446
like, where do you go to the coffee shops?
426
00:28:11,446 -->
00:28:12,406
There's like an office.
427
00:28:12,406 -->
00:28:15,346
Like what's your day in the life in SF?
428
00:28:15,346 -->
00:28:20,120
day of the life in SA, I won't, this is the longest I've spent in San Francisco.
429
00:28:20,120 -->
00:28:26,936
Like before, like when I was in Alaska and I had to come here like maybe every two months
for like a week at a time, stay at a hotel, go to the office back and forth.
430
00:28:26,936 -->
00:28:28,347
And so I didn't get to see it then.
431
00:28:28,347 -->
00:28:33,811
And then I was hoping that, you know, my three months in San Francisco, four months, I
would really get to see the city.
432
00:28:33,811 -->
00:28:35,363
Frankly, still haven't really.
433
00:28:35,363 -->
00:28:37,995
A little bit more, but I know it's got more to offer.
434
00:28:37,995 -->
00:28:43,219
My day for the most part is I spend most of my time in the office.
435
00:28:43,219 -->
00:28:44,588
We have an office space.
436
00:28:44,588 -->
00:29:00,268
And so I wake up, go to the office, work until like mid-evening, like probably call it
like six-ish, go to the gym, get some food, back to the office, and then work until pretty
437
00:29:00,268 -->
00:29:01,608
late, pretty late.
438
00:29:01,608 -->
00:29:02,628
I won't lie.
439
00:29:02,708 -->
00:29:04,588
The days are exceptionally long.
440
00:29:05,028 -->
00:29:10,668
That's like the modal work day, but we still have a good time.
441
00:29:11,318 -->
00:29:20,434
there's a ton of YC events and coming back to the community aspect of it, that has made
life so much easier just because you do have folks who are in the same grind as you.
442
00:29:20,434 -->
00:29:29,160
So every Friday we all get together, or a bunch of us get together and just have some
drinks, get some food, and shoot the shit over the week.
443
00:29:29,160 -->
00:29:33,043
And then there's other events throughout the week that Y Combinator hosts too.
444
00:29:33,043 -->
00:29:38,987
And so that has kind of allowed us to chop out some time for more social time.
445
00:29:38,987 -->
00:29:40,938
But a lot of it is really just
446
00:29:40,938 -->
00:29:47,710
me, my co-founder, a couple people that we work with ah just grinding throughout the day
and trying to build as quick as we can.
447
00:29:48,236 -->
00:29:48,916
jealous dude.
448
00:29:48,916 -->
00:29:58,833
I mean, that was my life in 2019 when we were in Jason, Jason, like Calacanis accelerator,
me and my founder Jeremy like, just all we didn't have an office, we just worked in our
449
00:29:58,833 -->
00:29:59,894
Airbnb, right?
450
00:29:59,894 -->
00:30:05,448
So it's like, just like 24 not 24 seven, but like we're working all the time.
451
00:30:05,448 -->
00:30:08,900
Like, it's like, you don't really want to be doing anything.
452
00:30:08,900 -->
00:30:09,661
What else do you want?
453
00:30:09,661 -->
00:30:12,403
You're there to build a company care about what you're building.
454
00:30:12,403 -->
00:30:16,425
Some people like give folks like you and folks like me flack like, you work too much.
455
00:30:16,425 -->
00:30:17,926
It's not even work.
456
00:30:17,966 -->
00:30:19,546
We love this shit, right?
457
00:30:19,546 -->
00:30:21,086
It's so fun.
458
00:30:21,126 -->
00:30:23,046
I don't know if you will get that, right?
459
00:30:23,046 -->
00:30:23,947
know for sure.
460
00:30:23,947 -->
00:30:28,409
like the hours are long, but like I don't know what I would spend my time doing.
461
00:30:28,409 -->
00:30:34,293
I literally came here with like one purpose, which was like grow the company, build a
great product that people love.
462
00:30:34,293 -->
00:30:36,354
And then like that's it.
463
00:30:36,354 -->
00:30:45,649
And so any amount of time that I spend just like getting the product forward, like a
little bit more, making it more beautiful, making it better, getting user feedback, like
464
00:30:46,015 -->
00:30:47,225
dude, that's what I'm here for right now.
465
00:30:47,225 -->
00:30:49,966
And so any other time, like, you know, you have to recharge.
466
00:30:49,966 -->
00:30:55,838
You can't just like do the 16 hour day, like every single day for three months, you're
just going to burn yourself out.
467
00:30:55,838 -->
00:31:00,669
And so like, you have to bake in like the routines that like, keep you energized.
468
00:31:00,669 -->
00:31:03,950
And so like, you know, for me, that's like hanging out with other people.
469
00:31:03,950 -->
00:31:12,692
like trying to do something on a Friday, Saturday, going to the gym, you have to bake that
into your schedule because it's so easy when you do have like the pressure of starting a
470
00:31:12,692 -->
00:31:15,443
company to just have the anxiety of like, right,
471
00:31:15,443 -->
00:31:25,609
got more to do drive you towards like only ever working and so my co-founder and I have
tried to do as good of a job as we can of like having some balance to keep us recharged
472
00:31:25,609 -->
00:31:30,661
but that's still paired with like a ton of hours of work that honestly don't even feel
like work.
473
00:31:31,864 -->
00:31:32,224
Totally.
474
00:31:32,224 -->
00:31:34,115
Yeah, I mean, that makes sense.
475
00:31:34,115 -->
00:31:35,195
Can't can't work like you.
476
00:31:35,195 -->
00:31:39,427
You know, it's kind of a cycle or not a cycle, but they feed into each other.
477
00:31:39,427 -->
00:31:42,018
You got to work out, got to hang out with people like refresh.
478
00:31:42,018 -->
00:31:46,579
And then when you're refreshed, you do a 16 hour day or something or like a 14 hour day.
479
00:31:46,579 -->
00:31:51,461
um What is what is the like next few months look like?
480
00:31:51,461 -->
00:31:53,642
What my question actually is is.
481
00:31:54,004 -->
00:31:57,101
When is this going to be available for like the public soon?
482
00:31:57,101 -->
00:32:01,411
Maybe what is like your plan to like unveil is going to be wait list for a while.
483
00:32:01,411 -->
00:32:02,904
Someone's listening and they want to try it.
484
00:32:02,904 -->
00:32:05,278
Like what's what's your thoughts around that?
485
00:32:05,471 -->
00:32:09,174
Yeah, we don't have a timeline on full public release just yet.
486
00:32:09,174 -->
00:32:18,262
We're still just laser focused on working with our private beta group to make the product
as useful as possible.
487
00:32:18,442 -->
00:32:22,966
And we're going to launch here publicly very soon, the waitlist.
488
00:32:22,966 -->
00:32:27,410
then uh we'll be taking people off the waitlist all the time.
489
00:32:27,410 -->
00:32:29,712
the private beta group will grow pretty quickly.
490
00:32:29,832 -->
00:32:33,407
If someone's listening to the podcast and wants to get off the waitlist even sooner.
491
00:32:33,407 -->
00:32:42,248
then you can shoot me an email at connor at tricaddy.ai and then just mention the pod and
then we'll see what we can do.
492
00:32:42,248 -->
00:32:43,942
though even the pod listeners a hookup.
493
00:32:43,942 -->
00:32:44,861
I appreciate that.
494
00:32:44,861 -->
00:32:46,693
Yeah dude, come on.
495
00:32:46,693 -->
00:32:49,035
For these listeners, I'd do anything, alright?
496
00:32:49,035 -->
00:32:55,341
So, we'll keep the group like, relatively small at the start and then grow up pretty
quickly.
497
00:32:55,341 -->
00:32:58,163
But, that's the game plan for now.
498
00:32:58,968 -->
00:32:59,838
Cool.
499
00:32:59,858 -->
00:33:07,145
And I guess for my last question, it's like, is there anything anyone listening can do to
help, you know, probably get on the wait list?
500
00:33:07,325 -->
00:33:17,394
But is there, know, yeah, what else can someone do to engage with your brand view of like
website, you know, social media, newsletter, like how else can someone plug in?
501
00:33:17,673 -->
00:33:18,884
Yeah, get on the waitlist.
502
00:33:18,884 -->
00:33:25,087
We will uh be in contact regularly about what are the updates to the product that we're
shipping.
503
00:33:25,107 -->
00:33:27,468
We'll take you off the waitlist as soon as we possibly can.
504
00:33:27,468 -->
00:33:32,771
And ultimately right now, we just want to engage with users and get their feedback.
505
00:33:32,771 -->
00:33:36,533
so folks on the waitlist, we put everyone in a big Slack group.
506
00:33:36,533 -->
00:33:39,585
We just chat with them basically every day.
507
00:33:39,585 -->
00:33:43,587
And so uh it's been great so far.
508
00:33:43,587 -->
00:33:47,749
And I think that the more perspectives that we can get on that and the more we can hear
from folks about like,
509
00:33:47,807 -->
00:33:48,668
What are they loving?
510
00:33:48,668 -->
00:33:50,009
How do they want to use it?
511
00:33:50,009 -->
00:33:53,012
um You know, what are the bugs that they're finding?
512
00:33:53,012 -->
00:33:53,973
The better.
513
00:33:53,973 -->
00:34:00,039
But right now I think the best way to engage is just get on the wait list and then reach
out literally anytime.
514
00:34:00,526 -->
00:34:01,506
Cool.
515
00:34:01,886 -->
00:34:05,566
Anything else you want to share or kind of get, know, or maybe, maybe I'll finish it with
this.
516
00:34:05,566 -->
00:34:13,306
It can be anything you want to share or you see all these billboards and NSF and they all
have tech, tech, you know, tech brands on them.
517
00:34:13,306 -->
00:34:16,905
If you could own a billboard, I'm stealing someone's question.
518
00:34:16,905 -->
00:34:19,866
I don't know whose question is, but it's a podcast or ask this question.
519
00:34:20,006 -->
00:34:27,926
What would you put, what would you put on a billboard on the 101 or the 202, whatever it's
called, NSF and we'll end it on that.
520
00:34:28,085 -->
00:34:33,238
Dude, this is a great Tim Ferriss question and I've listened to his podcast.
521
00:34:33,238 -->
00:34:33,676
Yeah.
522
00:34:33,676 -->
00:34:36,523
knew it was someone's and you're right, it is Tim Ferriss.
523
00:34:36,523 -->
00:34:44,583
I've listened to his podcast so many times and I've listened to this question and I have
not thought of an answer to have prepared just yet.
524
00:34:44,583 -->
00:34:46,467
So now I'm like, what would I
525
00:34:46,550 -->
00:34:48,315
It doesn't even have to be, it could be anything.
526
00:34:48,315 -->
00:34:54,410
could be, you know, about life, philosophy, business, could be anything you want, you
know.
527
00:35:00,223 -->
00:35:07,085
I think this is, you know, maybe this is gonna be cheesy, but the people who you choose to
work with are genuinely the most important part about what you're doing.
528
00:35:07,085 -->
00:35:10,526
And so that's a lot of words to put on a billboard.
529
00:35:10,887 -->
00:35:18,209
But metaphorically, we'll make it that it's gonna be one that like, you're only gonna be
able to read in traffic when you're stuck still.
530
00:35:18,209 -->
00:35:24,221
But em I think that like I got very lucky my time at Lume by working with people who were
just like,
531
00:35:24,401 -->
00:35:27,233
amazing at their jobs, but also like amazing people.
532
00:35:27,233 -->
00:35:31,836
And then now I'm working with like a much, much smaller group of me and my co-founder and
like two other people.
533
00:35:31,836 -->
00:35:38,641
But even when things are like exceptionally hard because I enjoy spending time with them,
it makes life so much easier.
534
00:35:38,641 -->
00:35:47,938
And so to the extent that you can select to like work with the people that you really like
to spend time with, especially if you're doing a startup, like it's like a non-negotiable.
535
00:35:47,938 -->
00:35:52,771
You have to be finding people that you like want to be spending 16 hours at like uh
536
00:35:53,067 -->
00:35:54,907
San Francisco office with.
537
00:35:55,107 -->
00:36:03,067
And so I think that when I think about like even like the hard times now, like the things
that I'm most grateful for is, you know, who I've chosen to do this with, my co-founder
538
00:36:03,067 -->
00:36:03,507
Rajiv.
539
00:36:03,507 -->
00:36:08,515
And so that's my heartfelt, very long billboard.
540
00:36:08,876 -->
00:36:10,549
Hey, give me a big billboard.
541
00:36:10,551 -->
00:36:11,092
Cool.
542
00:36:11,092 -->
00:36:12,966
Well, Connor, great to catch up.
543
00:36:12,966 -->
00:36:16,724
Thanks for coming on and looking forward to seeing you roll this thing out.
544
00:36:16,863 -->
00:36:17,988
Yeah, dude, thanks for having me.
545
00:36:17,988 -->
00:36:20,268
Can't believe we finally got to the podcast after so long.
546
00:36:20,268 -->
00:36:21,651
So thanks so much.
547
00:36:21,651 -->
00:36:22,365
we got it in.
548
00:36:22,365 -->
00:36:23,326
Bye.
