How one sentence of chat becomes a five-stage AI content campaign
product
A walkthrough of SNAP's pipeline: how a single chat request moves from collect, to reason, to draft, to review, to publish-ready output.
Most AI writing tools stop at a draft. SNAP's pipeline treats a single line of chat as the trigger for a five-stage workflow — the same shape a human content team would follow, run by connected agents on top of your grounded sources.
The five stages, in order
1. Collect. SNAP walks your project's source layer and pulls every passage relevant to the topic, audience, and length you named. No manual attachment step.
2. Reason. A reasoning pass synthesizes the collected passages into an outline, flags gaps, and asks the source layer for follow-up material if needed. This is where reasoning search does the heavy lifting.
3. Draft. A writing skill turns the outline into a full draft in your brand voice, keeping citations attached to every claim.
4. Review. Responsible-AI gates run automatically — completeness, requirement-fit, and sign-off — so nothing ships past its own approval criteria.
5. Act. The finished asset lands where the work lives, whether that's a doc, a deck in validation, a training video, or a Jira ticket via the action layer.
Why the pipeline shape matters
A single-shot prompt collapses these steps into one, which is why generic tools produce plausible but ungrounded work. Splitting collect, reason, draft, review, and act lets each stage be inspected, scoped, and improved on its own. Teams get an output they can trust and a trail they can audit.
Where teams put it to work
- Positioning and messaging refreshes
- HR answers grounded in current policy
- Onboarding, product updates, and sales enablement
- Training video generation, live today
One request, five stages, one grounded output.