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It would be interesting to see a statistically significant number of data points on this test. I wonder about variability of the max load on the used anchors vs. new ones. I think I'd prefer a known max load to one that might be greater, but is unknown.

Is anyone making anchors designed with a notch?

Where exactly did he say he was unhappy with the change? All he said was that he didn't know about it and would ask when he gets to the office.

I like his point about focus in new companies. Do one thing, make it work. When it does, use your expanding group of resources to add on.

I don't understand his distinction between companies and features. If you have a product that can stand on its own, clearly a business can be built around it. But I don't think selling features that will contribute to a larger product is any less legitimate of a business. A hardware store can be a very healthy business even though a bolt isn't very useful until it's attached to something larger.

It will be interesting, a few years down the line, to compare what Tesla does with its $465m compared to what GM does with its billions. Obviously not an apples-to-apples comparison, but it might illustrate the cost of the inherent friction in massively bureaucratic companies.

Regarding Tesla's profitability, it's EBITDA profitability, and in the words of Warren Buffet:

"References to ebitda make us shudder-does management think the tooth fairy pays for capital expenditures?"

Certainly this is an important milestone for Tesla. It means that they're getting a handle on their supply chain, but this doesn't make them anything close to a stable company. They still have to get to a point where their cars aren't just profitable, but profitable enough to pay for the factories they're built in. Hopefully this latest influx of cash will be enough to get them there.

I would have made the same assumption, except, as I mentioned, the two examples he gives are major construction projects. Since it was clear that the 37signals post was addressing all types of projects, I thought I'd give one example where the argument against planning doesn't hold.

The point that seems to completely elude 37signals is that not every industry operates the same way as web design and development. They've taken their very narrow range of experience and told us that it applies to all projects in every industry (he cites Denver International Airport and the Big Dig in his post). This is such an outlandish notion that it becomes difficult to take them seriously at all.

As an example, I work as a design engineer in the R&D wing of an automotive supplier. If we were to just start building products on a hunch, without any market research or project planning, we could easily spend hundreds of thousands of dollars or more before we knew if we were headed in the right direction.

Ultimately planning is imperfect and comes at a cost (time and resources), but that needs to be compared to the cost of no planning at all. In the web app business the cost of trying a new idea may be next to nothing, so trial and error becomes the most expedient method. In my industry, we're aware that our plans are imperfect, but if they allow us to cut a few very expensive iterations out of the development process then they're worth it.

The title seems a bit misleading. Humans don't prefer cockiness to expertise, they just have a hard time differentiating between the two.

Autodesk has an iphone app called "Fluid". Pretty much the same idea.

This is purely my intuition, but it seems like anyone who would develop for the platform is pretty used to digging around a website for information. The people who are just syncing photos, videos, etc. are more likely to be scared off by the first line on the front page.

If it were me I'd put up a simple explanation on the front page then give developers an obvious place to go for more information on the platform.

Which facts did you find to be editorialized, specifically?

I'm not sure you're right about that. I think of a genetic algorithm as an optimization algorithm that imitates a genetic reproductive process. This algorithm seems to be a rough approximation of binary fission instead of sexual reproduction. Still a genetic process, just a different one than is typically used.