We should start off
off my list of favorite theorems from the first decade of
complexity with the seminal paper in complexity, the one that gives
the field and this weblog its names.
This paper formalizes the idea that we now all take as obvious
that we should use Turing machines to determine complexity of
complexity by measuring time as a function of the
size of the input. Ever since the Hartmanis-Stearns paper we measure
nearly every resource (time, space, random bits, circuit depth, etc.)
as a function of the input size.
This paper also gives the first hierarchy of classes, showing that for
nice functions t and u with t2(n)=o(u(n)) then there are
problems solvable in time u(n) but not time t(n) on multitape Turing
machines. Soon later Hennie and Stearns showed the same
result if t(n) log t(n) = o(u(n)).