Explore Prompts

Generate a 15-second vertical ad concept and deliverables: shot list, camera moves, lighting, on-screen text, VO script, and a Sora 2-ready prompt per shot. Add 3 hook variants for A/B testing.

Take one longform input (webinar/podcast/blog) and output: 10 short scripts (15–45s), 5 carousels, 3 email snippets, and 20 hook lines. Include timecodes, b-roll notes, and caption text.

Build a 30-day content calendar for 3 channels (LinkedIn, X, email newsletter). Include weekly themes, daily hooks, CTAs, and repurposing instructions. Provide variants for B2B SaaS, consumer app, and consulting.

Create a complete Brand Voice Bible for a company: tone sliders, banned phrases, signature phrases, grammar rules, audience personas, and 15 example posts across LinkedIn/X/Email. Output: (1) one-page summary, (2) full bible, (3) prompt template to enforce voice in future content.

Produce a 100-day plan: quick wins, foundational work (governance/evals), first agent rollout, security controls, and stakeholder cadence. Include a weekly operating rhythm and deliverables.

Create a moat analysis: data network effects, workflow embedding, switching costs, and compliance advantage. Provide 10 defensibility tests and a 12-month moat-building plan.

Define north-star metrics for AI in 2026: time-to-decision, cost-per-outcome, error-rate under policy, trust score, and automation rate with human satisfaction. Provide instrumentation plan.

Create a sovereign AI readiness checklist: data residency, model hosting options, key ownership, audit access, and supply-chain risks. Provide a staged maturity model from 0→4.

Design a provenance layer for internal RAG: citation IDs, document signing, version pinning, and ‘evidence packs’ in responses. Include UX and evaluation methods.

Write incident response runbooks for AI failures: hallucination spike, data leakage, tool misuse, latency blow-ups, and agent runaway. Include severity levels, comms templates, and postmortem format.

Create a data contract strategy for AI pipelines: schema/versioning, quality SLAs, lineage, and rollback. Include a ‘self-healing’ playbook and governance checkpoints.

Define a framework to decide when AI is a feature, a workflow, or a product line. Provide examples, pricing implications, and a roadmap template for 2026.