{"slug": "rate-limit-your-own-agent-before-someone-else-does", "title": "Rate-Limit Your Own Agent Before Someone Else Does", "summary": "Nylas warns developers to rate-limit their own AI agents before platform-enforced limits kick in. The company's Agent Accounts platform enforces a 0.1% complaint rate and 5% bounce rate before pausing sending, but Nylas recommends setting stricter self-imposed quotas via policies to catch runaway loops early. Policies allow per-agent daily send limits, storage caps, and outbound rules that block sends to specific domains or restrict reply-only behavior.", "body_md": "0.1%. That's the complaint rate that puts an email-sending account under review on Nylas Agent Accounts — one spam report per thousand sends. At 0.5%, sending is paused outright. For bounces, the review threshold is 5% and the pause kicks in at 10%. These aren't suggestions; they're enforced by the platform, and a pause [doesn't clear itself on a timer](https://developer.nylas.com/docs/v3/agent-accounts/send-limits/) — you have to contact support with evidence of a fix.\n\nHere's my position: those numbers shouldn't be your rate limit. They should be your last line of defense, behind a stricter limit you set yourself. Rate-limit your own agent before someone else does it for you.\n\nTraditional email code sends when a human or a cron job tells it to. An autonomous agent sends when a model *decides* to, and models inside feedback loops make weird decisions. A reply triggers a webhook, the webhook triggers a reply, and a benign bug becomes a thousand sends before lunch. Nothing in the model's reasoning says \"this is my 400th message this hour, that seems off.\" That awareness has to live in infrastructure.\n\nAgent Accounts (in beta) bake the infrastructure in through [policies](https://developer.nylas.com/docs/v3/agent-accounts/policies-rules-lists/). A policy bundles daily send quotas, storage caps, retention windows, and spam settings, and applies to every account in a workspace. Without one, an account runs at your billing plan's maximums — 200 messages per account per day on the free plan — which is exactly what you don't want for an experiment that might loop. Every limit on a policy is optional; omit one and it defaults to the plan maximum, ask for more than the plan allows and the API rejects it.\n\nThe useful mental shift: a self-imposed quota isn't throttling, it's an assertion. \"This support agent should never need more than 150 sends a day. If it asks for number 151, something upstream is wrong.\" That's the same logic as a circuit breaker in a service mesh — you're not limiting capacity, you're encoding an expectation so violations become visible instead of expensive.\n\nPolicies let you encode different expectations per agent archetype. A prototype gets a tight quota; a production sales agent gets a higher one. The docs explicitly suggest separate workspaces per archetype, because a triage agent and an outreach agent have completely different send profiles.\n\nOutbound rules go a step further than volume — they constrain *direction*. A rule with `trigger: \"outbound\"`\n\nevaluates before the message reaches the provider, and a `block`\n\naction rejects the send with a `403`\n\n:\n\n```\ncurl --request POST \\\n  --url \"https://api.us.nylas.com/v3/rules\" \\\n  --header \"Authorization: Bearer <NYLAS_API_KEY>\" \\\n  --header \"Content-Type: application/json\" \\\n  --data '{\n    \"name\": \"Block outbound to example.net\",\n    \"trigger\": \"outbound\",\n    \"match\": {\n      \"conditions\": [\n        { \"field\": \"recipient.domain\", \"operator\": \"is\", \"value\": \"example.net\" }\n      ]\n    },\n    \"actions\": [{ \"type\": \"block\" }]\n  }'\n```\n\nThe `recipient.*`\n\nfields match any recipient, including BCC and SMTP envelope recipients — so an agent can't smuggle a send past the rule by hiding the address. You can also match `outbound.type`\n\n(`compose`\n\nvs `reply`\n\n) to, say, let an agent reply freely but block it from starting brand-new threads.\n\nThe bounce and complaint rates that trigger pauses are computed from events you can subscribe to: `message.transactional.delivered`\n\n, `message.transactional.bounced`\n\n, `message.transactional.complaint`\n\n, and `message.transactional.rejected`\n\n— four webhook triggers that are your only real-time window into those rates. The docs' advice is blunt: wire them up and pause your own outbound logic when bounces or complaints climb. You'll see the problem in your own telemetry before the platform tells you about it, and \"we paused ourselves\" is a much better incident report than \"we got paused.\"\n\nIt also helps to know what's actually being counted. Bounce rate only counts hard bounces — addresses that don't exist — divided by a recent representative send volume; soft bounces from full mailboxes or greylisting don't touch it, and healthy is under 2%. Complaint rate counts recipients clicking **Mark this email as spam** or dragging your mail to junk, measured only across domains that send complaint feedback. That's why 0.1% is so easy to hit at low volume: a handful of annoyed recipients in a 2,000-send week puts the account under review.\n\nThe error responses are worth knowing too. A reputation pause surfaces as a `400`\n\non send; a per-account or per-domain rate limit returns `429`\n\n(back off and retry); an abuse restriction returns `403`\n\nwith `send blocked by abuse restriction`\n\n. That last one can be scoped to a single sender address, a domain and its subdomains, a grant, or the entire application — and an application-level restriction stops every Agent Account under the app, not just the one that misbehaved. If your agent treats all send failures as retryable, it will hammer a paused account and learn nothing.\n\nTwo details make the rule layer trustworthy enough to bet on. First, evaluation **fails closed**: if a `block`\n\nrule can't be evaluated because of a transient infrastructure error — say, a list lookup failure during `in_list`\n\nmatching — Nylas blocks the message rather than letting it through. The failure is surfaced as retryable: an API send returns `503`\n\ninstead of `403`\n\n, and inbound SMTP answers with a `451`\n\ntempfail so the sending server retries instead of bouncing. A safety mechanism that silently disables itself under load isn't a safety mechanism.\n\nSecond, every evaluation writes an audit record. `GET /v3/grants/{grant_id}/rule-evaluations`\n\nlists, most recent first, which rules matched, what actions were applied, and the normalized sender and recipient data that was considered. When a block happened because evaluation errored rather than matched, the record carries `blocked_by_evaluation_error: true`\n\n. So when your agent's send comes back `403`\n\nat 2 a.m., \"why was this blocked?\" is one API call, not an archaeology project. A circuit breaker without observability is just a mystery outage.\n\nThe honest objection is that real workloads spike. A support agent during an outage might legitimately need 5x its normal volume, and a hard quota turns your safety net into an availability incident. That's true — if the quota is a dead end.\n\nSo don't make it a dead end. Make hitting the quota an escalation path: alert a human, queue the overflow, require an approval to raise the cap. The failure mode of a too-tight quota is a Slack ping and an hour of delayed email. The failure mode of no quota is a 10% bounce rate, a platform-level pause that requires a support ticket to lift, and a sender reputation you rebuild over weeks. Those aren't symmetric risks.\n\nThere's also a softer dial worth knowing: policies expose `spam_sensitivity`\n\nfrom 0.1 to 5.0 for inbound filtering. Inbound hygiene matters for outbound health, because agents that reply to junk generate complaints.\n\nConcrete next step: before your agent's next deploy, create one policy with a daily quota at roughly 2x the agent's observed peak, attach it to the workspace, and subscribe to the four `message.transactional.*`\n\ntriggers. Then deliberately make your agent hit the quota in staging and check that your alerting fires. If it doesn't, you've found the gap while it's still cheap.", "url": "https://wpnews.pro/news/rate-limit-your-own-agent-before-someone-else-does", "canonical_source": "https://dev.to/qasim157/rate-limit-your-own-agent-before-someone-else-does-33cb", "published_at": "2026-06-16 21:38:17+00:00", "updated_at": "2026-06-16 21:59:52.175003+00:00", "lang": "en", "topics": ["ai-agents", "developer-tools", "ai-infrastructure"], "entities": ["Nylas", "Nylas Agent Accounts"], "alternates": {"html": "https://wpnews.pro/news/rate-limit-your-own-agent-before-someone-else-does", "markdown": "https://wpnews.pro/news/rate-limit-your-own-agent-before-someone-else-does.md", "text": "https://wpnews.pro/news/rate-limit-your-own-agent-before-someone-else-does.txt", "jsonld": "https://wpnews.pro/news/rate-limit-your-own-agent-before-someone-else-does.jsonld"}}