major startup that...
major startup that way—should start a business that is having to make people
happy with them day one, through contracts, through small scale sales, whatever
it is. How low can you go? How can you build something really inexpensively?
How can you not spend money on furniture and matching carpet and
those sorts of things? The biggest thing that I probably didn’t do the second
time around was have any money.
Livingston: Tell me about how you got the idea for WAIS.
Kahle: The idea of WAIS was to make network services—stuff that you take
completely for granted now—but the idea was that you could use remote
machines to answer questions. The ARPANET was just really becoming in use
by universities in the 1980s, and so at Thinking Machines we were trying to
figure out, “How would you make use of a machine that had 15 gigabytes of
disk space and would have processors that you could run at, say, a gigahertz?”
This was completely amazing. How would you possibly use that much computing
power? We said, “Well, you’d put them on the Net, and they’d be smart
machines that would answer your questions for you.” So this was the idea. We’d
prototype it around Thinking Machines.
I prototyped it in my spare time. I guess there was very much an ethos that
hacking was encouraged—playing around and doing fun things, spending time
doing something that wasn’t your exact job responsibility, but doing it at work,
and getting support from work. So I tried out the idea of remote publishing—of
remotely asking machines questions. It was the first Internet publishing system.
It came before Gopher and before the Web, but it was the first system that was
trying to answer questions over the Net. Yes, search was a big part of it, but you
could also click around and it had a URL system and it had a search system for
finding servers. It had all the different pieces. It was built on an open protocol.
We did it as a project of Thinking Machines, working with Apple Computer,
KPMG Peat Marwick, and Dow Jones.
So my first experience with trying to start something at that scale was actually
done within Thinking Machines—again, following that original lesson of
“learn your lessons without spending your own money.” So we tried basically
building this system up within Thinking Machines. Thinking Machines wanted
to make money by selling servers, so we needed to get the rest of the system
going. We had Apple Computer to do the front end, the client piece; Dow
Jones to do the information sources; and KPMG Peat Marwick for their corporate
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