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Discursive methodology: what it is (and why it changes everything)

A discursive methodology is a structured way to think through a problem with AI, not just talk about it.

It turns AI from text generation into a deliberation system that produces:

• Multiple lenses (not a single-track answer)
• Explicit assumptions (what is known vs inferred)
• Counterarguments and stress tests (where this could fail)
• Grounded claims (connected to retrievable evidence)
• Decision artifacts (briefs, options, trade-offs, next actions)

Key principle: Agents do not replace methodology, methodology governs agents.

What goes wrong without methodology

When the stakes matter, just prompting tends to fail in predictable ways:

• Blind spots: One perspective hides risks, values, and alternatives.
• False confidence: Fluent output can mask weak logic.
• Lack of methodological structure: Each conversation lacks a consistent framework for reasoning.
• No audit trail: Teams cannot review how the recommendation was formed.

Discursive methodology makes results more defensible, reviewable, and actionable.