Salesforce is buying Braze for $5.66B. The pattern: the engagement layer is worth more than the record layer. Your CRM knows who to call — Braze decides when they actually listen.
Engagement is a cost line too: tools, data, and the team running the journeys. Before you add another layer, model the full rep economics, agent included: salesquants.com/agent-vs-rep…
ServiceNow: $1B+ in AI efficiency gains, headcount slightly down. The split matters: quota-carrying sellers UP double digits, sales ops headcount down significantly. AI didn't shrink the sellers — it shrank the overhead around them.
ServiceNow's split is the SDR math in miniature: sellers up, overhead down. Run the full loaded cost — comp, ramp, seats, ops — before you scale: salesquants.com/agent-vs-sdr…
Salesforce just shipped a kill switch for AI agents: hard budget caps, plus evals that shut an agent down when it fails. The question flips — not whether agents work, but what stops them when they don't. Who owns the stop button in your org?
Governance is a cost line too: evals, kill switches, human review — price the guardrails before you scale the agent. Model the full rep economics, agent included: salesquants.com/agent-vs-rep…
Otto launched a voice AI CRM today: reps call in the visit, the deal record updates itself. The admin tax is the hidden line in every SDR cost model — hours typed, not sold. Recover those hours and the math changes before headcount does.
Admin hours belong in the headcount math too: comp, ramp, quota, seats — plus the hours lost to typing notes. Model the full cost before you scale: salesquants.com/agent-vs-sdr…
Databricks kept SDR headcount flat while its closing org scaled. One SDR books 400 outbound meetings a month. Automation didn't kill the SDR — it made the SDR 10x more productive. Does your model count that as leverage or headcount?
That 400-meeting SDR is the amplification math in the wild: same headcount, more output. Run your own version before you re-cut the team: salesquants.com/agent-vs-rep…
AI sales agents just added WhatsApp: leads answered in seconds, day or night, with a human handoff when asked. The channel changed. The math didn't — first response still beats best message.
A seconds-fast reply still has to clear the headcount math: what does the agent actually replace — comp, ramp, quota, seats, tooling — and what stays human? Model it before you scale: salesquants.com/agent-vs-sdr…
Same 5 reps, 51% more meetings: we modeled AI amplification — 10.8 to 16.3 meetings per rep per month — and the net gain came out at $83,817 per rep. Nobody replaced. The team just produces like 7.6 reps.
Amplification still has to clear the headcount math: what does AI actually extend — volume, reply rate, meetings — and what stays human? Model it before you re-cut the team: salesquants.com/agent-vs-rep…
Salesforce turned Agentforce on by default for every eligible org in Winter '27. Default-on is not deployed. The winners decide what the agent actually replaces — comp, ramp, quota, seats — before it touches a pipeline.
Default-on still has to clear the headcount math: what does the agent actually replace — comp, ramp, quota, seats, tooling — and what stays human? Model it before you scale: salesquants.com/agent-vs-sdr…
Signal-based outreach reports 15-25% reply rates vs 3-5% for cold email. The AI is the same — the data layer isn't. Win rate doubles too: 37% vs 19%. The agent doesn't fix a bad list; the signal does.
A 15-25% reply rate still has to clear the headcount math: what does the agent actually replace — base, OTE, ramp, quota, tooling — and what stays human? Model it before you re-cut the team: salesquants.com/agent-vs-rep…
Everyone argues about whether AI agents replace SDRs. Almost nobody runs the numbers. So we built the calculator that does — and turned it into an app.
Two calculators, free, no signup to run the math: Agent vs. SDR. Agent vs. Sales Rep. Runs in your browser. Installs to your home screen like a native app.
We built it with AI and shipped it in the open — the code is public, the math is auditable:
App: jefflherrmann-prog.github.io…
Code: github.com/jefflherrmann-pro…
Run your own numbers. Then argue.
