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CronkiteNews You Can Trust

A set of AI agents turns scattered posts, sources, and claims into one clear view of an event: what happened, who is saying what, what each side believes, and what evidence supports it.

TimelineWhat led here?
ViewpointWhat is being argued?
Trust profileWho is saying it?
EvidenceWhat supports it?
One news event
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The trust problem

We do not know who to trust anymore.

A single story now arrives as posts, clips, screenshots, creator takes, official statements, and instant rebuttals. Everything looks equally urgent. Very little arrives with enough context.

The problem is not access to information. The problem is knowing what to trust.

The feed Reporting, propaganda, reactions, and AI media collapsed into one stream.

Every fragment competes before the story is understood.

Trust 28%

U.S. trust in mass media.

Gallup
Missing layer Context that explains where the claims came from.

The product opportunity is trust built around the story, not another headline stream.

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How news is consumed now

The front page is now a crowd of people.

News reaches us through accounts, creators, journalists, experts, institutions, eyewitnesses, and anonymous aggregators. Some are useful. Some are early. Some are wrong. Some are pushing a viewpoint.

If people are the new front page, the product has to understand their history.

53% of U.S. adults at least sometimes get news from social media. Pew
77% independent voices of sampled news influencers had no current or past news-organization affiliation. Pew
61% third-party platforms
29% publisher apps/sites
U.S. news video distribution Reuters shows the market has moved to Facebook, YouTube, X, Instagram, and TikTok. Reuters Institute
21% Influencers of U.S. adults regularly get news from news influencers. Pew
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Core insight

A post is not the story.

Every event has a past. Every source has a history. Every viewpoint comes from somewhere.

Cronkite starts from the belief that history is the clue to trust.

Now The viral claim everyone is reacting to
BeforeWhat happened before this?
SourceWhat did they say before?
EvidenceWhich claims have support?
UnknownWhat is still missing?
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What Cronkite builds

The full idea in one look.

Agents research the topic, search the web for historical context, inspect source histories, validate claims, group viewpoints, and present the full shape of the story.

The output is not a verdict. It is an inspectable map of the story.

One evolving topic
Timeline What happened, and what led here.

Built through web research and source links.

Viewpoints What each side believes happened.

Grouped by claims, emphasis, and disputed facts.

Trust profiles Who is behind each perspective.

Previous statements, evidence habits, and topic history.

Evidence What supports, contradicts, or remains unresolved.

Linked back to sources where possible.

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Consumer experience

Before you react, inspect the story.

Cronkite turns a chaotic topic into one readable topic page: what happened, how we got here, what each side believes, who is pushing each perspective, and what evidence exists.

The user sees an evolving timeline with viewpoints and trust profiles attached to the voices inside each perspective.

Living timeline The topic history grows over time.

Agents add new events, source links, documents, and prior coverage as the topic develops.

Viewpoint lanes Separate the major perspectives.

What each side believes happened, what they emphasize, and where the dispute sits.

Trust profiles Attach background to the voices in each lane.

Previous statements, evidence habits, corrections, proximity to the event, and topic-specific history.

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Why now

Agents do the work people cannot.

Cronkite is built around agents. Not one summary bot. A research system that watches X for live signals, builds source material from the web, validates claims, and appends new context to a living topic timeline.

The timeline is not rebuilt from scratch every time. It becomes the memory layer that agents keep updating as the topic evolves.

01Event agents

Collect live signals from X, where claims, clips, and reactions first land.

02Web research agents

Find source material, documents, prior coverage, and historical events.

03X/profile agents

Search relevant X profiles for previous statements on the topic.

04Validation agents

Check claims against source material and mark what is supported, contradicted, or unresolved.

05Viewpoint agents

Group competing perspectives and the voices pushing each one.

06Timeline agents

Append new events to the living topic timeline and keep the UI current.

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First build

MVP: one evolving topic, one living timeline.

The MVP follows one topic as it develops and keeps adding context over time instead of treating news as disconnected updates.

If Cronkite can make one evolving topic understandable over time, it has the foundation for a consumer news trust product.

Before Raw topic noise

Posts, clips, reactions, official statements, and arguments arriving as disconnected updates.

After Living Cronkite timeline

New events appended over time, with major viewpoints, source background, trust profiles, and validated claims.

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Business model

Make trust a weekly subscription.

Cronkite starts as a consumer subscription. A new subscriber chooses topics, sources, and delivery cadence; Cronkite maintains the living context map and delivers briefings when the story changes.

Free public topic pages acquire users. Paid personalization and alerts retain them. Reusable topic memory is the path to margin.

Acquire Shareable topic pages

Major stories become public context maps people can search, cite, and share.

Convert Personal news agent

Subscribers choose topics, voices, regions, and delivery rhythm.

Deliver Briefings when facts move

Daily digest, instant update, or watchlist alert when claims change.

Paid value More signal, less research work

Premium unlocks more watched topics, deeper source profiles, archive search, and professional-grade alerts.

Profit path One topic memory, many subscribers

Agents build and refresh the living topic graph once, then reuse that context across every subscriber who follows it.

Measure API cost / living topic AI cost / subscriber retention by watched topic
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Shipyard ask

Credits for X research and Hermes sensemaking.

Cronkite needs two credit pools: xAI credits for the X Search and Grok calls used by X research agents, plus ChatGPT, Claude, and other AI credits for the Hermes agents themselves.

The ask is API credits to search X, build and run the Hermes agents, and measure cost per living topic.

Credit bucket What it funds Current estimate
xAI credits X research agentsUse X Search and Grok to inspect profile history, pull live signals, and find previous statements from relevant voices. $5 / 1,000 X Search callsUp to 20 handles per call. Local blended estimate with Grok synthesis is about $0.0225 per call.
X source graph Profile monitoringFollow useful X accounts as topics evolve: reporters, experts, institutions, outlets, and primary sources. 100 profiles: $18-$72 / month500 profiles: $90-$360. 1,000 profiles: $180-$720. Token costs extra.
ChatGPT / Claude / other AI credits Hermes sensemaking agentsBuild the timeline, group viewpoints, validate claims, create trust profiles, summarize evidence, and prepare UI-ready context. TBD per agent runPrototype must measure cost by Hermes agent type: timeline, validation, viewpoint, profile, and presentation.
Raw X API fallback Deterministic capture if neededHydrated post objects and exact capture when X Search is not enough. $3k-$7.5k / monthFor 1,000 accounts at 20-50 posts per account per day. This is why xAI X Search is the first path.