One possible explanation: business owners have more skin in the game and care the most, so they are the most demanding and can’t tolerate waste. So they are the hardest to satisfy.
Additionally, they are not used to mincing their words because they don’t have bosses and are the most direct (and also egoistic).
According to NYT it seems like there were 2 controllers and “2 more in the building”. They also wrote that 2 seems normal for the late slower time of the night.
Not saying this is the right number of controllers to have, just sharing what I read in NYT.
I know about 2 big discontinuities in group dynamics, which are based on the limits of human cognition at specific sizes:
1) ~7 people. This is when each member cannot participate in the whole context and all important decisions. "2 pizza teams", limits of the working memory. Decisions cannot be done all together anymore. This results in hierarchies forming and people worrying about their positions in them.
2) ~150 people (Dunbar's number). This is when group members cannot all know each other anymore and have meaningful relationships. Max sizes of family-based tribes, an important unit size in the army. This results in inability to observe each other's actions well, so understanding who contributes a lot vs not shifts to indirect stories. Group members start building narratives instead of demonstrating contributions directly.
Beyond the common narrative on this topic, a factor to consider is that people might be more interested in hearing about death causes, which are not considered their own “fault”. These situations are less “fair”. Thus terrorism, homicide and accidents get a big focus.
Why do you think Glean and other top company GPT startups who are doing this for longer and have more resources cannot get this level of performance (helpful and accurate)? What makes your approach different and not easy to replicate?
Motif Analytics | Founding Designer, Founding Engineer, Founding Data Scientist | San Francisco or REMOTE | Full-time | https://motifanalytics.com
Motif is an analytics product tailored to answer complex business questions through analyzing event sequences. It goes beyond traditional reporting (what is happening to the key business metrics?) and instead focuses on root-causing (why are metrics moving?) and guiding (how can the metrics be moved in the right direction?) [1].
Today, questions about product gaps and opportunities require multi-week deep dives, and often just raise further questions. As a result, many business questions go unanswered and teams rely on hunches to come up with and prioritize features [2].
Motif solves this by providing an interactive data wrangling, visualization and exploration experience to find insights in event sequences - “motifs”. Designers create magnificent art in Photoshop, game developers build powerful games in Unity and engineers architect reliable constructions in AutoCAD. Motif is a kindred power tool for data practitioners.
This approach has been proven at Google and Uber, and is ripe for bringing to the wider data ecosystem.
We are iterating on an MVP with a few early customers, are well-funded, offer competitive compensation and are hiring the founding team.
If you are interested, or you know someone who might be, please reach out to [email protected] .
Additionally, they are not used to mincing their words because they don’t have bosses and are the most direct (and also egoistic).