An AI SDR should have a defined job within your sales development process. Decide which research, drafting and follow-up tasks it owns, what it may change, and when it must stop for review. The important choice is the division of responsibility around the software, rather than how confidently a model presents its answer.
The original LinkedIn post behind this article described my reaction to a model release. That historical opinion is not a benchmark for current products. This guide focuses on assigning work and accountability. It does not assume that every product sold as an AI SDR has the same capabilities or permissions.
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“Fable is the first model to go like: Bro I know what I'm doing. Stay out of it please. That confidence makes sense when you see how Anthropic shipped it.”
Assign Tasks Before Assigning Autonomy
Describe one task in terms of inputs and an observable result. Account research might return a sourced brief. Drafting might produce a message for review. Follow-up preparation might summarize the last confirmed interaction and propose a next step. Each task needs a clear finish line that another person can inspect.
Keep account selection distinct from research. A system can find interesting facts about a company that should never enter your campaign. The sales owner should define the target criteria and exclusions, then review ambiguous matches. More information about an account does not establish that your offer is relevant to it.
Write the Responsibility Agreement
For each task, record the owner, allowed inputs, permitted actions, required evidence and escalation condition. Distinguish reading a record from editing it, and preparing a message from sending it. The workflow should not gain additional authority merely because it can technically perform an action.
An illustrative assignment might let the AI prepare an account brief and a draft while a seller decides whether the account belongs in the campaign. The same seller reviews the factual connection and owns the conversation. An operations owner handles integration failures. These are proposed roles to adapt to your team, rather than a staffing model with guaranteed results.
Make the Handoff Recognizable
A useful research handoff includes the sources, the specific finding, missing information and the proposed use of that finding. Separate observation from inference. If an announcement suggests a possible need, preserve that as a hypothesis instead of presenting it as a confirmed problem inside the prospect's business.
A useful drafting handoff identifies the intended recipient, the approved offer and the evidence supporting the message. Draft ready means a draft exists. It does not mean the person has been contacted. Require the next owner to accept or reject the handoff so work cannot disappear between two systems that both report success.
Give Replies a Human Owner
Define what happens when a person answers. A request for clarification, a complaint, an objection or a change in timing may invalidate the planned next step. Route the reply with the relevant history and stop incompatible pending actions. Do not let an old follow-up continue because another component has not received the update.
Set a clear owner for decisions involving price, scope, commitments or suitability. The software can organize context and suggest a response. Accountability for what the company promises should remain explicit. A buyer should not have to discover which automation is responsible for an inconsistent message.
Define Stop Conditions
Missing evidence should produce an incomplete result with the gap explicitly recorded. Conflicting account information should trigger review. An uncertain action outcome should remain uncertain until someone checks the destination. A decline or exclusion should prevent the same person from re-entering a campaign through a later import.
Failures also need ownership. Decide who investigates a broken integration, who can restart a task and what evidence makes a retry safe. A system that silently skips failed work creates a misleading picture of progress. A system that repeats an action blindly can create a second problem while trying to repair the first.
Evaluate the Role on Representative Work
Start with a small set of cases that includes missing data, poor-fit accounts, conflicting sources and replies that change the plan. Define the expected action before running the test. Include cases where the correct output is to stop or ask a question. Completing every task is not success when some tasks should have been rejected.
Measure accepted handoffs, factual corrections, unresolved failures and human review time. Keep these operational measures separate from delivered messages, qualified conversations and completed meetings. A faster brief is useful, but it does not prove an improvement in sales outcomes. Compare results only when the account mix and task definitions are understood.
Keep the Assignment Current
Review the responsibility agreement when your offer, tools or team changes. A permission that was appropriate for a narrow pilot may be unsuitable for another workflow. Preserve the previous version and the reason for the change so reviewers can explain which rules produced a particular action.
The first useful deployment is one bounded task with a visible result and a named owner. Expand only after the team can identify correct work, handle exceptions and stop the process when needed. The goal is a dependable division of labor that supports the sales conversation.
The email draft review guide explains how to inspect one proposed message.
The batch personalization workflow covers consistent checks and duplicate handling across a campaign.
The AI sales agent loop describes the general research, action and feedback structure.
