Tool
Source-linked workflows that name AI Agents. Part of the AI agent use cases on UsecaseBoard, or browse all use cases.
An Ask HN on controlling agents that take real actions converges on: LLM proposes → deterministic validator (rules, spend ceilings, replay checks) → human approve—especially for refunds, payments, and database writes where prompt 'never do X' fails.
In r/AI_Agents, builders say the lasting 2026 pattern is collect→draft→show evidence→wait for approval: inbox triage, GitHub/release monitoring, support handoff drafts, and invoice extraction that formats billing payloads without silent sends.
An Indie Hackers builder runs event-driven agents: when backend changes land, webhooks update TypeScript/Python SDKs, run tests, draft changelogs/PRs, and only deploy if checks pass—plus a morning schedule that drafts Agent Store listings for review.
After 20+ SMB AI audits, an Indie Hackers operator says the <90-day winners are boring—missed-call capture, calendar booking follow-ups, lead routing, and quote nudges—not strategy decks.
Show HN: a hotel exposes live price/availability so AI agents can read rates and hand the user a booking link entirely over the open web, without MCPs or custom connectors.
The published agent workflow alternates idea generation and critical review, then uses specialist prompts to develop an accepted campaign's audience, tactics, budget, and measures.