FWIW, building your own tools/workflows on top of a standard software typically dramatically increase the lock-in in my experience.
It is typically non-trivial to port this functionality to a new system.
So it would be in favor of existing SaaS vendors.
Comparing re-sale price of Tesla to Ford is absurd.
Elon Musk alienated most of Tesla‘s potential customers.
I would assume more of the price drop comes from that than from anything inherent about EVs.
You still do from operating the software.
You see what problems users have using it, which types of problems they tackle with it.
By the end of running the software for a month you will have typically learned a boat load.
Imho opinion, what you are describing are republicans of the past. As parent says, there used to be shared values. Two of the shared valued were peaceful transition of power and respect for the rule of law / division of power between executive, legislative and judiciary.
Imho the values of MAGA republicans are clearly distinct from GWB republicans (even if it may be precisely the same voters). Specifically the two values described above are no longer shared values.
I believe there are more, but for the two values above we have irrevocable proof.
Afaik that was already the rule 25-30 years ago when Armstrong was cycling.
I can remember track and field athletes being banned when they didn‘t show up for surprise tests.
So either cycling was more lenient or he got a bonus treatment because he was famous.
On a side note: much harder today to not be available/found than it was 30 odd years ago.
I sometimes sum this up as:
Don‘t listen to your customer. Watch your customer.
Obviously needs to be taken with a grain of salt, but seeing how users behave is often more insightful than asking them what they want. You just need to setup the environment for watching in a way that you learn what you want to learn.
It is survivorship bias.
Because the companies get to a point where unimportant things are important and you spend years in that second phase, the learnings are upside down.
„If only we would have solved technical problem X from day 1 we would have so much less hassle in the years to come.“
Except that solving problem X on day 1 instead of shipping what the company did might have killed the company.
I see this in a lot of second time founders, where startup 1 was successful - „this time I‘ll really avoid my mistake X.“
Why?
Climate science works with quantative models and makes concrete predictions.
So if the predictions don‘t come true the model is false.
E.g. this random blog I found googling compares IPCC predictions with actual outcomes: https://johncarlosbaez.wordpress.com/2012/03/27/the-1990-ipc...
[the link is just supposed to show how climate science is falsifiable. I have no idea whether the numbers in this specific source are trustworthy]
My experience: Skip most of the talks (maybe only 1-2 per day). Spend time drinking coffee and bumping into random strangers. Then spend more time with people you found nice/interesting.
Thanks. Great post!
How would you divide a seed and/or A round between angels and VCs? Is there a perfect mix in your opinion or something you would be opportunistic about, depending on who is interested?
A close relative is an architect. The way construction projects are managed is waterfall.
It is made worse by the fact that you typically have
1) a large number of different expert firms involved, creating huge dependencies (imagine instead of FE & BE, having 8 different types of engineers, that can only work in a certain pre-defined order and have very limited availability (so if you are late and miss a slot, they may only be available again a few weeks or months later)
2) communication is either physical meeting of principles (bosses/managers) - rarely actual workers, email or paper print outs. It is not uncommon for on premise workers to work with month old plans that have since been changed.
Buildings are one of the few purchasable objects that have gotten more expensive over the last decades (compared to pretty much every consumer goods item).
In the case of food retailers you also need to consider the time on shelf.
To take the coffee example. If any average shop buys 4 cases of coffee (24 bags) and on average sells 2 bags per week, then the last bags will sell after 12 weeks.
On avg. it will be 6 weeks (42 days).
Product will also spend 1-2 days in transit and might not be unpacked on the floor until 1-2 working days later (so maybe 2-3 days).
We can assume payments take 1 day to process.
So 46-48 days in total.
So 50 day payment terms means they are more or less cash flow neutral.
Numbers are made up, but roughly align with my experience of selling other durable food to grocery retailers.