Curation for Decision Intelligence News is simple. In most cases, it is just a clear title, a short excerpt or description, and a few sentences of insight.

The goal is not to write a full review. The goal is to help readers quickly understand why a link matters, what it is really about, and where it fits in the broader field of decision intelligence.

Curated items may include articles, papers, blog posts, podcasts, videos, webinars, reports, tools, case studies, courses, conference talks, or anything else with a useful link. Whatever the format, the curator’s role is the same: add enough context to help readers decide whether to spend time with it and how to interpret it.

A strong curation usually does three things:

1. Chooses a useful link
   • Curate items that help readers understand, apply, or navigate DI.
2. Engages with the source
   • Read, watch, or listen enough to understand the main point.
3. Adds context
   • Explain why the item matters to DI readers and where it fits in the field.

As you write, ask:

• What is this item really about?
• Why is it useful to DI readers?
• Is it about P-decisions, C-decisions, governance, AI, analytics, human judgment, or something adjacent?
• Does the excerpt or description reveal the item’s main contribution?
• Would a clearer title help readers understand the link?

Also be selective. Avoid hype, vague uses of “decision intelligence,” pure vendor promotion, or items that would make the field more confusing rather than clearer.

That is the core of it. For examples, edge cases, and deeper guidance on what to include or avoid, read the full guide below.

Note: “Decision making” doesn’t have a hyphen unless it’s an adjectival phrase:

• “Decision making is important” is correct
• “Decision-making is important” is not correct
• “She had a great decision-making system” is correct
• “She had a great decision making system is not correct.

If there’s a post at lorienpratt.com that hasn’t yet been curated to the DI news, then we’d very much appreciate if you’d do that.

Please also preferentially curate material from our friends and customers like at CModel (we’ll add to this list in the future).

Not every item that mentions “decision intelligence” needs to be curated.  And sometimes an article that doesn’t mention DI is still relevant and of value to DI practitioners.

Before posting, ask whether the item will genuinely help DI News readers.

Good candidates may:

• explain an important DI concept
• provide a useful case study
• show how organizations are applying DI-related methods
• connect DI to AI, analytics, decision quality, causal reasoning, governance, or human judgment
• introduce a relevant tool, framework, event, research finding, or practitioner story
• raise an important question for the field
• help readers understand how the term “decision intelligence” is being used in practice
• reflect a newsworthy / recent event

An item does not need to be perfect. It may still be worth curating if it is useful, timely, provocative, or illustrative. But the curator should help readers understand its contribution.

Avoid curating items that do not help readers understand, apply, or navigate decision intelligence.

Do not curate items where “decision intelligence” appears mainly as a marketing label, with no meaningful discussion of decisions, decision quality, causal reasoning, analytics, governance, or human judgment.

Example:

“Our platform delivers next-generation decision intelligence for digital transformation.”

If the item never explains what kind of decisions are being improved or how, it is probably not worth curating.

Avoid items that simply say AI will transform business, improve productivity, or automate decisions without offering a specific decision-related insight.

Example:

“AI is changing everything. Companies that use AI will make smarter decisions faster.”

This is too broad unless the item includes a concrete DI-relevant example, framework, or lesson.

Some items treat prediction, classification, scoring, or recommendation as if they are the whole of decision intelligence. These may be worth curating only if the curator can use them to clarify the distinction.

Do not curate if the item merely says:

“The model predicts outcomes, therefore it makes better decisions.”

Prediction can support decisions, but it is not the same as decision intelligence.

Vendor pieces can be useful, but avoid purely promotional content that mainly sells a product, service, event, or platform.

Do not curate if the item is mostly:

• product claims
• lead generation
• vague benefits
• unsupported ROI promises
• “book a demo” language
• inflated claims about AI-powered decisions

Vendor content is more curatable when it includes a concrete case study, useful framework, architecture, governance lesson, or practical decision example.

Avoid pieces that mention DI but do not connect it to any recognizable part of the field, such as:

• decision quality
• causal reasoning
• prediction or classification
• decision automation
• human-AI collaboration
• governance
• uncertainty
• actions and outcomes
• analytics or modeling
• organizational decision processes

If the item cannot be situated in the field, it may not help DI News readers.

Avoid items that are little more than a headline, short announcement, infographic, quote, or social post unless they point to something genuinely useful.

Example:

“Decision intelligence is the future. Are you ready?”

That may be fine as social media, but it is usually not enough for DI News.

Avoid curating items that claim DI, AI, or analytics improves decisions but provide no examples, citations, data, mechanism, or reasoning.

Be cautious with claims like:

• “guarantees better decisions”
• “eliminates uncertainty”
• “removes the need for human judgment”
• “solves decision making”
• “fully automates strategic decisions”

These claims tend to mislead rather than educate.

Business intelligence, data visualization, and analytics can be relevant to DI. But not every dashboard or data story is a DI story.

Do not curate if the item stops at:

“We gave leaders more data.”

A DI-relevant item should go further:

“We changed how leaders choose among alternatives, evaluate tradeoffs, monitor outcomes, or learn from feedback.”

Be cautious with content that presents automation as inherently superior to human decision making, especially in high-stakes contexts.

Avoid items that imply:

• humans should simply accept AI outputs
• accountability can be delegated to models
• explainability is unnecessary
• governance is an obstacle rather than part of decision quality
• organizational adoption is automatic

DI News should help readers understand responsible decision systems, not just automated ones.

Some items introduce a new definition of decision intelligence without acknowledging existing meanings or traditions. These may be worth curating if the curator can frame them carefully.

But avoid curating them uncritically if they would leave readers more confused about what DI means.

Signs of fragmentation risk:

• DI is redefined casually
• existing DI work is ignored
• adjacent topics are renamed “decision intelligence”
• the item treats DI as synonymous with AI, analytics, or automation
• no distinction is made among prediction, decision quality, and causal decision making

Older items can be valuable, especially if foundational. But avoid stale material that no longer reflects the field, technology, or current practice.

Curate older content only when it is:

• historically important
• still conceptually useful
• foundational
• newly relevant
• helpful for understanding how the field evolved

Avoid items that are only loosely related to DI, such as general leadership advice, generic AI news, productivity tips, or broad digital transformation commentary.

They may be curatable if the insight clearly connects them to DI, but otherwise they dilute the publication.

Avoid items with:

• no identifiable author or source
• obvious factual errors
• suspicious claims
• plagiarized or AI-generated filler
• no references for technical or empirical claims
• low-quality reposts of better original sources

Prefer primary sources when possible.

Sometimes an item has a DI-related title but the content is so confused that the curation would need to spend most of its space correcting it.

In that case, it is usually better not to curate it.

A good rule:

If the curator’s insight would need to be mostly warning label, skip the item.

DI News readers are busy. Avoid items that are long, vague, repetitive, or low-value unless there is a clear payoff.

Ask:

Would a thoughtful DI practitioner be glad we pointed them to this?

If the answer is no, do not curate it.

Skip the item if most of these are true:

• It uses “decision intelligence” vaguely.
• It is mostly hype or promotion.
• It does not identify actual decisions.
• It confuses prediction with decision making.
• It lacks examples, evidence, or mechanisms.
• It does not connect to any recognizable DI concept.
• It would make the field less clear for readers.
• A good insight would need to apologize for the source.
• There is a better original source available.

One-sentence rule

Do not curate items that merely use the language of decision intelligence; curate items that help readers understand, apply, evaluate, or navigate decision intelligence.

A curation is not just a repost. Read, listen to, watch, or skim enough of the item to understand its main point.

As you engage with the item, ask:

• What definition of decision intelligence is being used?
• Is this mainly about prediction, decision quality, causal reasoning, automation, governance, AI adoption, or organizational change?
• Is it about making better decisions, building decision systems, managing AI, or something adjacent?
• Does it connect to established DI ideas?
• What would a DI reader need to know in order to interpret this correctly?

This does not mean being critical for the sake of being critical. It means being helpful. A curator adds value by noticing what kind of contribution the item makes.

Decision intelligence includes several related but distinct traditions. A good curation helps readers see which part of the field an item relates to.

For example, an item might be mainly about:

• P-decisions: pattern-based decisions, such as classification, scoring, prediction, detection, recommendation, or routing
• C-decisions: causal decisions, where the focus is on choosing actions based on their expected downstream consequences
• AI governance & model management in production: accountability, model risk management, explainability, auditability, and responsible use
• Human-AI collaboration: how people use, trust, challenge, or override AI-supported recommendations
• Organizational decision capability: how institutions build repeatable systems for making better decisions at scale
• DI education or awareness: material that introduces, popularizes, or explains DI to new audiences

Many good items touch more than one category. The curator’s job is not to force a rigid label, but to help readers orient themselves.

A simple phrase can be enough:

This podcast is especially relevant to the governance side of DI.

or:

This video is a useful example of a P-decision system being embedded into a larger organizational workflow.

or:

This report is most relevant to C-decisions because it focuses on how actions create downstream consequences over time.

Decision intelligence is developing quickly, and the term is now used in many different ways. Some people use it to mean AI-assisted decision making. Others use it to mean decision automation, decision quality, causal modeling, business analytics, decision support, or organizational transformation.

That variety can be productive, but it can also make the field harder to understand.

One purpose of DI News is to help readers navigate this landscape. Curators can do that by gently clarifying how an item uses the term.

For example:

This webinar uses “decision intelligence” in the context of enterprise AI governance.

or:

This article approaches DI from an analytics and prediction perspective.

or:

This podcast is adjacent to DI rather than a full DI framework, but it is useful for understanding how leaders are thinking about AI-supported decisions.

This kind of context helps readers without criticizing the creator.

The “Insight” is the curator’s main contribution. It should not simply repeat the title, abstract, intro, or description. It should help the reader understand why the item matters.

A weak insight says:

This video discusses how AI can improve decision making in healthcare.

A stronger insight says:

This video is useful for readers interested in how prediction systems are being integrated into clinical workflows. From a DI perspective, it is especially relevant to the boundary between P-decisions, such as risk scoring, and C-decisions.

The stronger version helps readers place the item in the field.

A good insight often includes:

• one sentence on what the item is about
• one sentence on why it matters to DI readers
• one sentence placing it in the broader DI landscape
• optionally, one gentle note about what readers should watch for

The tone should be clear, useful, and field-building.

For articles, papers, reports, and blog posts, the excerpt should give readers a useful window into the item. Choose a passage that captures the central claim, shows how DI is being used, or highlights the most relevant contribution.

For podcasts, videos, webinars, or talks, you may not have a text excerpt. In that case, choose or write a concise description that fairly represents the most relevant point.

Good excerpts or descriptions usually do one of the following:

• state the central claim
• show how decision intelligence is being defined
• capture the practical contribution
• highlight a useful example
• identify a key question or tension
• help readers decide whether to click, watch, or listen

Avoid excerpts or descriptions that are too vague, promotional, or generic.

A weak excerpt or description might be:

“The future of business depends on smarter decisions.”

A stronger one might be:

“The company uses predictive models to identify customers at risk of churn, then routes high-value cases to human retention specialists.”

This gives the curator something concrete to discuss: prediction, workflow design, human intervention, and business outcomes.

Curators may adjust the displayed title when doing so adds value for readers.

Sometimes the original title is too long, vague, promotional, or unclear. A curated title can make the item’s relevance more obvious.

For example, suppose the original title is:

Unlocking the Future of Intelligent Enterprise Transformation

A better curated title might be:

How DI Orchestration is Changing Customer Retention Decisions

The curated title should not distort the item. It should clarify it.

Good title changes:

• make the topic more specific
• identify the DI relevance
• reduce hype
• help readers know what they are clicking
• preserve the creator’s meaning

Also you should double check that there your title, graphic, and insight are aligned. If the title is, say, about agentic AI, but your graphic and insight are about how DI makes AI explainable, then you should edit the elements so that they’re in sync.

DI News should help strengthen the field. Curations can be positive, clarifying, or gently cautionary, but they should not sound dismissive.

It is fine to say:

This item is useful for understanding AI governance, though it uses decision intelligence in a broad organizational sense.

It is better to avoid wording like:

The creator does not understand decision intelligence.

Even when an item uses terminology loosely, the curation can frame that constructively:

Readers may find it helpful to distinguish this item’s use of DI from other DI traditions, including decision quality and causal decision modeling.

That kind of sentence helps readers without personalizing the critique.

A strong DI News curation can be written in this structure:

Title
Make it clear, accurate, and useful.  Ideally also catchy and compelling.

Excerpt or description
Choose a short passage or description that captures the item’s main point or reveals how it uses DI.

Insight
Write two to four sentences that explain:

• what the item is about
• why it matters
• where it fits in DI
• what readers should notice

Suppose you find an article titled: AI Is Revolutionizing Decision Intelligence in Retail

The article describes a retailer using machine learning to predict which customers are likely to stop buying, then sending those customers targeted offers.

A weak curation would say:

“This article shows how decision intelligence is revolutionizing retail with AI-powered customer insights.”

A stronger curation might be:

Curated title:
Prediction and Causal Reasoning Supercharge Churn Models for Retail Decision Intelligence

Excerpt:
The system scores each customer’s likelihood of churn and recommends personalized offers for those at highest risk.

Insight:
“This is a useful example of a combined P-decision / C-decision system: the model predicts which customers are likely to churn and recommends an intervention based on how the retailer evaluates the downstream consequences of those interventions, such as margin impact, customer trust, and long-term loyalty. The article is most useful as an example of predictive analytics becoming part of a larger decision workflow.”

Suppose you find a podcast episode titled: The Future of AI-Powered Decisions

The guest discusses how a logistics company uses AI to recommend delivery routes, adjust staffing, and respond to weather disruptions.

Possible curated title:
AI Route Optimization and the Causal Side of Logistics Decisions

Description:
A logistics leader explains how AI recommendations are used to adjust routes, staffing, and delivery commitments in response to changing conditions.

Insight:
“This episode is relevant to DI because it goes beyond prediction and into operational action. The most interesting DI question is not just whether the system predicts delays, but how the organization chooses among interventions such as rerouting, adding staff, changing delivery promises, or absorbing higher costs. DI readers may find this useful as a practical example of C-decisions in a high-uncertainty operating environment, and how DI relates to operations research.”

Before publishing a curation, ask:

• Is this item worth DI readers’ attention?
• Have I engaged with enough of it to understand the main point?
• Have I chosen an excerpt or description that reveals something meaningful?
• Does my insight add context rather than just summary?
• Have I helped readers see where this fits in DI?
• Have I avoided unnecessary criticism of the creator?
• Would a busy reader understand why this item matters?
• Would the curation help clarify the field?

A DI News curator is not merely collecting links. The curator is helping readers make sense of a field.

The best curations are concise, thoughtful, and generous. They point readers toward useful material, clarify how that material relates to decision intelligence, and help the field become more coherent over time.