Several key insights I learned:
Show Me the Prototype
A prototype proves the technical feasibility of the new idea. It also creates an opportunity to test customer preference. As the result, we either know to drop the idea or earn investors trust to make the prototype into a real product.
Form the Team Like Ditto
Rules in a big organization could slow down the way we promote a new idea or even block it. Agile team structure enables the formation of a squad team by dragging the most talented or suitable roles from different umbrellas. The formed team is empowered to work with more freedom and flexibility to put the idea into a real product.
Quality Matters
When moving further to introduce the product to an extensive number of customers, we want to ensure that every customer experiences the beautiful moment using the product. Quality marks how many more units are going to be sold and how the public values the product brand. It impacts the team’s brand and the sales in the coming quarters. News like a sold product recall can harm the brand a lot. ( for example: major recall of the Humane AI Pin’s charging case )
I Know You Say No But Please Give Me a Constructive Suggestion After Syaing No
“This AI model size is too large to run on our existing system.” If “No” comes from believing the existing logic or rules, we lose the capability to propose the ideas of originality. Existing logic or rules exist with reasons. We do not abandon them, but we have a responsibility to figure out how they came from in the last generation of revolution, so that we know how to adjust them in the wave of the next revolution of the industry.
Do Not Overestimate the Data We Have
Some of the data in a certain field is not colletable but remains important. It is likely for us to overestimate the data we have on hand and as the result, leads to the path of wrong decision. Cost data, for example, is something we have in most cases, and we can overemphasize its importance in the decision making process.
