This exactly. It is more important to move fast. Screw the edge cases. As long as it’s correct _most_ of the time, you can always fix anything that’s broken tomorrow.
A programmer’s wife is pregnant and goes into labor. Programmer brings her to the hospital, she gives birth and the doctor hands the baby to the doting father.
Studying, getting hired, career promotions, raising funds... It’s all about beating the system. You’re evaluated based on certain criteria and you optimize for those.
Does pitch get lower with age? That would correlate with larger companies tending to choose more experienced CEOs.
That aside, there are other forms of biases, like people preferring better _looking_ leaders (based on socially perceived ideals on height, color, religion, hereditary status) and so too will they prefer better sounding CEOs.
This is an easy one - go for it! With your age, experience and accessibility to support from friends and family I think the upside far outweighs the downside.
You haven’t mentioned any financial commitments (loans, dependants, filial support, etc) so presumably you have none.
You will probably regret not going for it more than sticking with something you hate.
Get a barcode scanner, scan the ISBN and use that to do a API query on Amazon to retrieve title, author, category, price, etc. Store this info in a DB.
Some scenarios:
1. Generally lookup should return something. Store these book by categories, e.g. business, children, fiction, etc. in their shelves/containers for physical browsing by your customers. The more subcategories you can do the better.
2. If price is bigger than some threshold then store these books privately and list for sale directly in an online marketplace. There’s an industry around book scalping (forgot the actual term) where traders buy books from fairs and sell online based solely on margin.
3. The lookup returns nothing - these books are probably very valuable or worthless. Some manual action required.
I was actually considering doing something like this for remainders before, but never got it going. I’d love to know more about your eventual solution.
Amazing! This pretty much enables clothing brands to generate extremely targeted ads on the fly. Models can have similar body shape, hair style, skin colour to the user. Based on past photos the advertiser can figure out preferred colours, patterns and possibly even styles.
I'd love to read more about how you positioned your brand, especially on the design decisions that you made to entice customers come more regularly and how you manage to sell more cups than your competitors.
They implemented this fee whenever they were growing too fast and needed to slow they growth to keep their servers in check. At other times it was free.
How do you qualify candidates as being the target audience, and what happens if it’s a really small, hard-to-reach niche - how do you guarantee the number of respondents?