Decision intelligence
Decision intelligence is not a chatbot with a strategy accent. It is the practice of making a choice inspectable: what was compared, what evidence was used, wha...
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A library for people who have to decide
These articles explain methods Argumont uses in the product. They are education, not a pile of keyword stubs, and not fake news with invented dates.
How this relates to Insights
Insights is reserved for dated editorial pieces when we publish them. Learn is the standing library.
In this cluster
Decision analysis
Decision analysis is the older sibling of decision intelligence: options, criteria, tradeoffs, and a way to talk about uncertainty without pretending you have a...
Multi-agent AI
Multi-agent systems assign different roles or models to a task. In a decision product, that only helps if the roles produce claims you can score and challenge.
Adversarial reasoning
Adversarial reasoning is not being difficult in a meeting. It is assigning someone, or a model, the job of breaking the story so you do not ship a hole.
Evidence-based decisions
The phrase is used in medicine and public policy. In business it means you can point to a source when you say a number or a causal story, and you label what you...
Decision matrix
A matrix is a table: options as rows, criteria as columns, weights on criteria, scores in cells. The math is simple. The honesty is not.
Decision confidence
Confidence should fall when evidence is thin, dates are old, or roles disagree. It should not rise because the slide is pretty or the room is aligned.
Decision calibration
A well-calibrated decision maker who says 70% is right about seven times in ten, in that bucket. Most people are not well calibrated on novel bets.
Decision bias
Confirmation bias, sunk cost, authority bias, and recency show up in almost every material choice. Process is how you make them more expensive to indulge.
Counterfactuals
A counterfactual is an alternate world: if churn did not fall, if the vendor missed the SLA, if the hire left in a year. You score that world too.
Pre-mortem
A pre-mortem asks the team to imagine it is a year later and the project is a disaster, then to write that history before you commit.
Risk-adjusted decisions
Finance uses risk-adjusted return. Operators can use the same idea without a lecture: what is the downside, how likely, and who eats it.
Argument evaluation
A good argument has a claim, a warrant, and evidence. Evaluation asks whether those pieces connect, not whether the paragraph sounds smart.
Assumption testing
Every plan sits on unstated ifs. Testing means you write them, rank them by how much they would change the decision, and gather evidence on the top few.
Decision criteria
Criteria should be named before options are scored. Weights should reflect the actual trade, not the slide that needs to look balanced.
Decision scoring
A score says this option is stronger on this criterion, given this evidence. If you cannot show the evidence, the score is decoration.
Audit trail
Regulators and boards sometimes require a trail. Operators need one even when nobody is asking, because memories of meetings are fiction.
Outcomes
Linking what you decided to what happened is how confidence becomes calibration instead of folklore.
AI debate
People ask models to debate because a single answer feels too smooth. Debate without scoring is still a show.
AI decision support
Support is research, structure, challenge, and a draft score. Authority stays with the person who will live with the outcome.
Insights
This section will hold original articles on decision making, AI reasoning, strategy, product, risk, and research. We will not invent backdated posts to look est...
Questions
These pages answer a search the way an operator would: what the question hides, what evidence is needed, and how to run it in Argumont.
Start with decision intelligence
Argumont challenges assumptions, researches evidence, compares competing approaches, and identifies the strongest decision.
Start with decision intelligence