Hooksbase

Getting started / April 25, 2026

AI agent examples (with the event triggers behind them)

Hooksbase dashboard showing demo event deliveries and webhooks

When people ask "what does an AI agent actually do," the honest answer is: respond to a real-world event by reasoning, acting, and either finishing or escalating. The interesting part isn't the model — it's the event that triggers it and the chain of actions that follow.

This guide collects production-shaped agent examples by domain. Each one names the trigger, the action, the success condition, and the event-layer features the agent depends on to stay reliable.

Customer support agents

Email triage agent

  • Trigger: Inbound email to support@your-app.com (parsed via email-to-webhook).
  • Action: Classify intent, look up the customer, draft a reply, and either send it or hand off to a human in a Slack channel.
  • Stops when: A reply is sent or a human picks it up.
  • Event layer needs: Email ingest with attachment relay; downstream dedupe on the message ID; retained replay when a prompt change deserves re-runs of last week's misclassifications.

Ticket-deflection agent

  • Trigger: Form submission from your help center contact page.
  • Action: Search docs, propose a candidate solution, and either auto-resolve or escalate with the proposed solution attached.
  • Stops when: The user confirms resolution or escalation lands in the queue.
  • Event layer needs: Form ingest with file uploads; routing rules that send "billing" topics to one agent and "technical" to another.

Revenue agents

Failed payment recovery agent

  • Trigger: Stripe invoice.payment_failed webhook.
  • Action: Look up the customer's payment history, attempt a card-update flow, notify the account owner if the customer churns.
  • Stops when: Payment retries succeed or the subscription is cancelled.
  • Event layer needs: Starter+ verified Stripe inbound; deterministic replay while payloads are retained (because retries hit Stripe APIs that have side effects); Pro+ alerts on terminal-failure spikes.

Lead enrichment agent

  • Trigger: Form submission from a "request a demo" page.
  • Action: Hit enrichment APIs, score the lead, route to the right SDR, write the decision back to the CRM.
  • Stops when: Lead is in the CRM with an owner.
  • Event layer needs: Form ingest; Pro+ throttling so the agent doesn't burn through enrichment-API rate limits during traffic spikes.

Subscription change handler agent

  • Trigger: Stripe customer.subscription.updated.
  • Action: Reconcile the change against your billing database, update entitlements, notify CS if downgrade volume spikes.
  • Stops when: Database is consistent and notifications sent.
  • Event layer needs: Pro+ strict FIFO ordering so subscription event sequences process in order; queryable provider.eventType from a Starter+ provider pack for routing.

Engineering and ops agents

Release notes agent

  • Trigger: GitHub release event.
  • Action: Pull every PR merged into the release tag, generate a changelog draft, post to Slack for review.
  • Stops when: Draft is posted.
  • Event layer needs: Starter+ verified GitHub inbound and payload transforms to extract just the release tag and PR numbers.

Incident triage agent

  • Trigger: Webhook from your monitoring stack (Datadog, Grafana, custom metrics) when an alert fires.
  • Action: Pull the runbook for the alert, check recent deploys, propose a root cause, page on-call only if the agent's confidence is low.
  • Stops when: The alert resolves automatically or on-call acknowledges.
  • Event layer needs: HTTP ingest from the alerting webhook; routing rules by alert severity; DLQ for terminal failures so unhandled alerts don't get lost.

PR review agent

  • Trigger: GitHub pull_request.opened or pull_request.synchronize.
  • Action: Run a first-pass review (style, common bugs, test coverage), post comments via the GitHub API, request changes if anything is critical.
  • Stops when: A comment is posted or the PR is approved.
  • Event layer needs: Starter+ verified GitHub inbound; Pro+ throttling so a 200-PR migration doesn't burn the model budget; retained replay so prompt changes can re-run yesterday's reviews.

Vulnerability response agent

  • Trigger: GitHub repository_vulnerability_alert (or a third-party scanner webhook).
  • Action: Check affected versions in your dependency graph, classify severity, page on-call for criticals, file a tracking issue otherwise.
  • Stops when: The vulnerability is acknowledged or remediated.
  • Event layer needs: Starter+ verified GitHub inbound when the source is GitHub, destination-side verification for other scanners, and Pro+ alerts on the agent's own DLQ so unhandled vulnerabilities don't sit silently.

Background and scheduled agents

Reconciliation agent

  • Trigger: Cron (every 15 minutes).
  • Action: Compare expected and actual state across systems (e.g. Stripe vs your DB), find drift, attempt auto-correction or alert.
  • Stops when: State is consistent or a delta is reported.
  • Event layer needs: Starter+ scheduled triggers with static payload templates so every tick has a consistent shape; an agent-level guard in case the previous run is still working.

Cost monitoring agent

  • Trigger: Cron (daily).
  • Action: Pull yesterday's cloud spend, compare against budget, flag anomalies, post to a Slack channel.
  • Stops when: Report is posted.
  • Event layer needs: Starter+ scheduled triggers; Pro+ event drains so daily reports flow into your observability stack alongside other metrics.

Inventory monitoring agent

  • Trigger: Cron (hourly) or a Shopify products/update webhook.
  • Action: Check inventory levels, compare to reorder thresholds, ping the buyer if action is needed.
  • Stops when: A reorder is placed or the level is acknowledged.
  • Event layer needs: Either ingest channel works; routing rules that suppress noisy non-actionable updates.

Product and onboarding agents

Onboarding agent

  • Trigger: Clerk user.created event.
  • Action: Enrich the user's profile, personalize the first email, schedule a guided setup task.
  • Stops when: The first email is sent and a task is scheduled.
  • Event layer needs: Verified Clerk inbound; payload transforms to flatten the Clerk user object to what your downstream expects.

Activation agent

  • Trigger: Cron (daily) or a product-event webhook (e.g. feature_used from your analytics stack).
  • Action: Identify users at risk of churning before activation, schedule a personalized nudge.
  • Stops when: The nudge is sent or the user activates on their own.
  • Event layer needs: HTTP ingest; throttling on the nudge channel to respect quiet hours.

Multi-agent systems

Coordinator + specialists

  • Trigger: Any of the above.
  • Action: A coordinator agent receives the event, decides which specialist agent to delegate to, and waits for results.
  • Stops when: All specialists have responded.
  • Event layer needs: A coordinator destination selected by routing rules; if the same event must reach multiple specialists, hand it to a downstream queue or coordinator service that owns the fan-out. Queryable delivery history lets you trace which path was selected.

What every example has in common

Look across the list and the same patterns show up:

  1. A single, well-named trigger. Not "the agent runs when something happens" — this event from this source.
  2. A small, bounded action. Five tools beat fifty.
  3. A clear stop condition. The agent knows when it's done; it doesn't run forever.
  4. An event-layer dependency. Verification, retries, replay, idempotency, observability — every example needs at least three of these.

The model and framework are commodities now. The differentiator is the event layer underneath: how reliably the trigger reaches the agent, how cleanly the result ships out, and how recoverable the system is when something fails.

Hooksbase is the event layer for these agents — HTTP, email, and form ingest on every tier; scheduled ingest, verified provider packs, and transforms on Starter+; programmable routing; retries with backoff; Pro+ strict FIFO where needed; deterministic replay while payloads are retained; DLQ; and delivery history. Pick a workflow blueprint, point it at your agent, and skip the channel-specific work.

Where to go next

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