AI agents can draft almost anything. The harder problem is choosing something current, relevant, and credible enough to distribute.
A public product URL is a useful starting point because it grounds the workflow before the agent looks for trends.
1. Understand the product
The first pass extracts a compact product context: who the product appears to serve, the problem it addresses, the claims visible on the site, credible topics, plausible formats, and assumptions that still need founder review.
Website text is untrusted input. It must be fetched through a bounded, server-side path and treated as evidence—not as instructions to the system.
2. Build source-specific queries
One broad query is rarely enough. Search demand, developer communities, code ecosystems, current web coverage, social conversations, and video formats each answer a different question.
The query plan should stay small and product-specific. The goal is not to collect everything. It is to find enough independent evidence to decide whether a useful window exists.
3. Normalize before synthesis
Every provider uses different fields and metrics. Normalization turns those responses into stored signals with source, canonical URL, observation time, freshness, provenance, and limitations.
Deterministic checks then handle relevance, lineage, independence, relative performance, novelty, saturation, founder credibility, channel fit, format fit, and evidence completeness.
The model receives a bounded candidate set after ranking. It can refine the angle, hook, and outline, but it cannot add evidence or change the deterministic action.
4. Return one Next Move
The output is exactly one of PUBLISH, REPLY, REMIX, or WAIT. It includes the recommended channel, format, topic, angle, hook, outline, why-now explanation, truth class, evidence receipts, confidence, limitations, and valid-until time.
That object works equally well in a private founder result and a JSON response. An agent can request work, poll the status URL, and pass the final decision into a drafting or planning workflow.
5. Keep the human decision
The first cohort is founder-reviewed. The reviewer checks inferred context, evidence fit, limitations, and whether the language stays inside what the receipts support.
TrendsFast does not connect social accounts or publish. The agent receives a structured move; the founder still decides whether and how to act.
That is the useful division of labor: the system replaces fragmented research with one inspectable decision, while the founder keeps authorship and judgment.