"To me, the 'idea' is how you would describe the product to a customer in one sentence."

Yes, that seems to be a better definition of the 'new', Web 2.0 definition of an 'idea' than I was able to formulate. I just don't think it is a very appropriate, significant, or meaningful use of 'idea'.

I regard the important ideas as the crucial, difficult, powerful 'secret sauce' and the 'execution' as the routine stuff that comes later, especially after customers arrive. With a sufficiently good idea, say, the first Xerox machine, TWA in its first months as it had the only Lockheed Connies in the world, and more, as relatively 'routine' and this because the work before was so darned good. The US is absolutely awash in ability to do routine execution, from a corner store up to a giant corporation, well.

For my project, I've worked out more than the math: The math is now in code ready for production -- tested, timed, documented. It's shockingly fast. I've worked out a server farm 'architecture' that is dirt simple and looks like it will 'scale' beyond what the world could use. Much of the simplicity is because there is a lot of parallelism and redundancy and a lot of data that is read-only for at least a day and maybe a week. Actually, all the big data is read-only in this sense. And, it does appear that in production this big read-only data can be just in virtual memory off either rotating magnetic disks or the newer, faster solid state disks (that love read-only data). Windows Server 2008 (I'm staying with Microsoft) can have 16 TB of virtual memory, and my software does the accesses with very nice, and, thus, fast, locality of reference.

The role of the math is to take the available data, 'crunch' it, and give the desired results. The quality of the results is key and where the work of the other guys sucks.

There is a 'larger business plan' beyond just the crucial, core math: As a byproduct of the work itself, the Web site gets some data from the users. The users give that data as part of getting the results they want and won't mind giving the data because there is no privacy threat.

But from some subtle results in advanced math (the Radon-Nikodym theorem), that data will be the main source of 'base data' for the whole system for everything. So, in particular, compared with the other guys, I have some new data, of unusually high quality, and especially valuable. People won't see why the data is valuable, but it is! In particular, the data will let me do some good ad targeting, and that's where the 'monitization' and 'revenue model' come from. I don't really want to use third party cookies to connect with the ad targeting of the ad networks, and I should be able to do better ad targeting just with my own data and some more of my math.

The software promises to be astoundingly efficient: From the timings, data rates, and data sizes, it appears that for the on-line production servers, four racks should be enough for about $4.5 billion a year in revenue, and 2000 square feet of on-line rack space should be sufficient to serve the world. Right: If 4 racks can give $4.5 billion a year in revenue, then 2000 square feet of rack space should give one of the most valuable companies in the world. Of course would want more space for redundancy, backup and recovery, testing, and development. For more reliability and lower latency, might want more than one data center. Could make a little use of some caching on the network.

I'm not eager to say what the problem is much before I'm ready to go live.

Actually, telling people what the problem is seems to have no upside at all: Plenty of people in venture capital have had descriptions of the work polished to more luster than any gold and really don't give a hoot. The situation is very much as in, "before good ComScore numbers, the project is just an idea, and ideas are easy and plentiful. Execution is everything and doesn't start until after the ComScrore numbers." The flip side of this thinking is an opportunity for me.

Net, what they care about are ComScore numbers. But, as threatens to be increasingly the case, for a successful Web site, there will be a window narrow in time between when the ComScore numbers are (1) good enough for the VCs to invest and (2) so good that I won't need or take their check. The advantages of being 100% owner of a 100% private, very profitable Subchapter S corporation, or even a C corporation, are just huge.

Actually, I'm terrified of having a Board: (1) They could kill my company just from taking up 25% of my time developing information to report to them. (2) There is no way they could possibly understand anything significant about the future of the business and no way I could explain it to them or keep them happy about it.

For the 'algorithms', I would say that they are trivial because the real content is in the math; the only claim of power or quality from the code is the math it implements; actually, given the math, the implementation was not difficult. So what matters is the math, not the algorithms.

This is a general situation in newer computing: An algorithm standing alone has little to recommend it, and just 'experience' will be a long, slow path to 'validity'. Instead, for 'validity', quality, whatever, an algorithm needs a prior 'specification' of what it does. Often that specification will have to be some relatively advanced math. Currently this math is a huge bottleneck for promise in computing.