The most expensive mistake when you stand up an AI SDR isn't the copy. It's burning your domain in two weeks and finding out your emails have been landing in spam for a month while the dashboard said everything was fine. Once a domain loses reputation, getting it back takes months. That's why an AI SDR doesn't start with the message: it starts with the sending infrastructure.
Warm up before you fire
We never prospect from the main domain. We use dedicated secondary domains, each with its own gradual warm-up over weeks before the first real send. Volume ramps slowly: the rush to start at full throttle is exactly what kills reputation.
- SPF, DKIM and DMARC configured and verified before anything else.
- Sending domains kept separate from the corporate one (the brand doesn't gamble its reputation).
- Progressive warm-up: volume climbs in steps, not all at once.
- Clean, verified lists — a high bounce rate is a red flag to the providers.
The AI qualifies, it doesn't spew
The agent doesn't exist to send more email. It exists to send the right email to the right person with a real signal behind it. Segment by ICP, personalize with data that matters (not "saw you work at {company}") and drop whoever doesn't fit. Less volume, more relevance: that's the only thing deliverability rewards over the long run.
What we measure
An AI SDR that "sends a lot of email" isn't a result. The result is qualified meetings with deliverability intact. That's why we watch sending health with the same attention we give the pipeline.
- Qualified meetings generated (not just replies).
- Response rate and its trend.
- Sending health: bounce rate and spam rate per domain.
- CPL — cost per lead, to know whether the system pays for itself.
This is what a Senior AI Growth Implementer does inside an Implementa pod: not "launch a sequence", but build a system that generates pipeline without mortgaging the client's most fragile asset — their sending reputation.