Recorded on 4/15/2026 at 02:32 PM PDT
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[00:00:00.260 --> 00:00:01.280] we thought it was [00:00:01.280 --> 00:00:02.140] going to be two [00:00:02.140 --> 00:00:03.160] weeks and we were [00:00:03.160 --> 00:00:03.500] like, yeah, [00:00:03.500 --> 00:00:04.520] we're going to make [00:00:04.520 --> 00:00:05.780] the best kineserve [00:00:05.780 --> 00:00:08.650] app out there and [00:00:08.650 --> 00:00:09.940] best wind data. [00:00:09.940 --> 00:00:11.790] So two weeks turned [00:00:11.790 --> 00:00:13.070] three months [00:00:13.070 --> 00:00:14.780] testing, talking [00:00:14.780 --> 00:00:15.310] with users. [00:00:15.310 --> 00:00:16.740] And we ultimately [00:00:16.740 --> 00:00:18.060] what we discovered [00:00:18.060 --> 00:00:19.470] in that process was [00:00:19.470 --> 00:00:21.340] that a lot of [00:00:21.340 --> 00:00:21.620] people [00:00:21.620 --> 00:00:22.390] just wanted to know [00:00:22.390 --> 00:00:23.070] when it was a good [00:00:23.070 --> 00:00:23.820] time to go out. [00:00:23.820 --> 00:00:25.230] And we started [00:00:25.230 --> 00:00:26.690] asking what, how is [00:00:26.690 --> 00:00:29.470] that? And basically,