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Case study 06 / Fractional executives

20,000 articles scored daily.
The right stories by 8am.

A news-intelligence system monitors 3,000 publications, ranks stories by importance and relevance, drafts a timely point of view, and delivers it to each executive in Slack.

3,000 sources monitoredExecutive-specific scoringSlack-ready first drafts
01

3,000

news sources monitored continuously

02

20K+

published articles processed each day

03

~667h

manual scanning equivalent every day

04

By 08:00

ranked stories and draft takes in Slack

The attention problem

Track every development.
Miss no commentary window.

Fractional C-level executives wanted to build thought-leadership brands around timely commentary in their specialist fields. Their authority came from reacting to developments while those developments were still relevant.

The limiting factor was attention. No executive had the bandwidth to monitor thousands of publications, separate repeated coverage from new information, judge what their audience would care about, and draft a useful point of view before starting client work.

This did not have a credible manual equivalent. Even a shallow two-minute scan per article would consume roughly 667 human hours every day, before research, prioritization, or writing began.

The system

Scan 20,000 stories.
Deliver the few worth saying.

Collection creates the universe. Deduplication reduces noise. AI scores what remains against the executive, their audience, the engagement opportunity, and the remaining commentary window.

News intelligence / daily run

From the entire news cycle to the right executive take

Delivered by 08:00
3,000 NEWS SOURCES20,000+ ARTICLES / DAYAI SCORINGEXECUTIVE DELIVERYCOLLECT + DEDUPLICATE20,418PUBLISHED6,280UNIQUE STORIES842IN-SCOPESCORE EACH STORY01RELEVANCEDoes it match this executive?02IMPORTANCEWill their audience care?03ENGAGEMENTCan it support a strong take?04TIMELINESSIs the window still open?SLACK / 07:58Why this mattersStory summaryEngagement scoreFirst-draft takeWRITESKIPA HUMAN COULD NOT MONITOR THIS UNIVERSE. THE SYSTEM MAKES IT FINITE.

3,000

sources monitored

20K+

articles processed daily

~667h

manual scan equivalent

08:00

daily Slack delivery

Scoring before generation

Rank the opportunity.
Then draft the take.

The system did not generate commentary for everything it found. It first decided whether a story deserved the executive’s attention. Only the strongest candidates earned a draft.

01

Relevant

Matches the executive’s field and point of view.

02

Important

Material enough for their audience to care.

03

Engaging

Contains tension, novelty, or a useful disagreement.

04

Timely

Still inside the window for relevant commentary.

The human decision

Open Slack.
Choose write or skip.

Every morning, each executive received a compact brief containing the original story, why it mattered to their audience, an engagement score, and a first-draft take. The system removed discovery and blank-page work. The executive kept the final judgment and voice.

No feed browsing

The relevant story arrives instead of waiting to be found.

No blank page

A drafted angle creates a useful starting point, not a finished opinion.

Voice stays human

The executive decides whether to write, change the angle, or skip it entirely.

Scale, made tangible

Manual scan assumption

2 min

A deliberately shallow read per published article.

Daily article volume

20,000+

Before deduplication, relevance, and quality scoring.

Equivalent daily effort

~667h

More than 83 eight-hour workdays, every single day.

Back-of-the-envelope comparison: 20,000 articles × 2 minutes ÷ 60.

The outcome

Monitor 3,000 sources.
Start every day with a point of view.

Map an intelligence system