Diversity of Thought in Agent Design

Rule

Each agent’s system prompt defines three cognitive components: a perspective (how it frames the problem), heuristics (strategies for finding solutions), and an interpretive model (what “good” means). These are not decorative — they determine which solutions the agent considers and which it misses.

Why

A team of diverse “good enough” agents outperforms a single “best” agent on complex problems. Different perspectives reveal different solution peaks; on a rugged problem landscape, no single optimization target finds them all. The IT4IT value streams already encode this — distinct roles (engineer, ops, product, QA) optimize for different things on purpose. Tool diversity alone is insufficient: two agents with different tools but identical prompts converge on the same generic answer.

Applies To

In-platform coworkers and any external agent topology with multiple roles. When a complex problem requires multiple perspectives, the orchestrator consults several specialists and combines their output. The principle does not apply to single-agent workflows (no diversity to architect) or to UI affordances (which are not agents).

How To Apply

For every new agent role, declare its perspective, heuristics, and success criteria in the system prompt. Example: the Software Engineer agent’s perspective is “code structure,” its heuristic is “test-driven development,” its interpretive model is “correctness over speed.” The Operations Engineer reads the same problem through “deployment safety,” uses “rollback-first deployment,” and optimizes for “availability.” If two agent roles end up with the same three components, one of them is redundant.

Decision Dimensions

Examples

Sources

(Rendered from the sources: frontmatter by WikiSourceCitations — do not duplicate citation prose here.)