Bounded Rationality and Satisficing

Overview

Herbert Simon's Bounded Rationality recognizes that any agent operating under finite resources cannot exhaustively optimize: the search space is too large, information is incomplete, and acting has a cost. Rather than pursuing the optimal solution, Simon proposed "satisficing"—a portmanteau of satisfy + suffice—choosing the first solution good enough to meet an explicit threshold, then stopping.

For an autonomous coding agent the binding constraint is a budget: tool calls, search/read operations, context window, and wall-clock time per turn. A grep that could keep matching, a file tree you could keep traversing, a doc set you could keep reading — each has steeply diminishing returns. Satisficing converts "search until certain" (which never terminates) into "search until the threshold is met, then act."

Core Principle: Define "good enough" before you search, and stop at the first option that clears the bar. Optimizing is correct only when the gap between good and best is worth more than the budget it costs to close it.

When to Use

• An investigation or search has no natural endpoint (greps, file reads, doc crawls, candidate solutions) and could consume the whole budget.
• Multiple options would all clear the requirement and you're tempted to keep comparing.
• You're gathering more context than the decision actually needs.
• A reversible, low-stakes choice is consuming optimization-level effort.
• You need to commit and ship before the turn/budget runs out.

Decision flow: