The title of this paper is meant to highlight an emerging duality between two fundamental topics in algorithms and complexity theory. Algorithms for circuits} refers to the design of interesting algorithms which can perform non-trivial circuit analysis of some kind, on either a circuit or a Boolean function given as a truth table. For instance, an algorithm determining whether a given circuit has an input that forces a true output would solve the NP-complete Circuit-SAT problem. Such an algorithm is of course unlikely to run in polynomial time, but could possibly be more efficient than exhaustively trying all possible inputs to the circuit. Circuits for algorithms refers to the modeling of uniform algorithms with non-uniform circuit families (or proving such modeling is impossible). For instance, the NEXP versus P/poly question asks whether nondeterministic exponential-time algorithms can be simulated using non-uniform circuit families of polynomial size. It is widely believed that the answer is emph{no}, however the present mathematical tools available are still too crude to prove this kind of separation. This paper surveys these two generic subjects, the ways in which they arise, and connections that have been developed between them, focusing on the connections between non-trivial circuit-analysis algorithms and proofs of circuit size lower bounds. To give one example, if there is a nontrivial algorithm (running slightly faster than exhaustive search) that can determine if a given circuit computes a constant function, then it can be concluded that NEXP is not contained in P/poly. Informally, this connection can be interpreted as saying "some good algorithms for circuits imply there are no good circuits for some algorithms."