Don't expect an AI agent to invent a successful sales process. First, have your human team identify and document what works—effective emails, scripts, and objection handling. Then, train the AI on this proven playbook to execute it flawlessly and at scale. The AI is a scaling tool, not a strategist from day one.

AI won't magically fix a broken strategy. The key is to identify what already works—your best emails, responses, and processes—and use that proven data to train the agent. This approach scales your known successes rather than hoping AI will invent a winning formula from scratch.

Don't deploy an AI SDR to find product-market fit or create a sales motion from scratch. It's a tool for amplification. You must first prove that a human can successfully sell your product with a specific playbook, then feed that playbook to the AI.

The quality bar for AI sales outreach isn't perfection; it's simply being better and more consistent than your average human SDR. A 'pretty good' email sent consistently without errors is sufficient to generate high response rates and outperform the variable quality of human efforts. Don't let the quest for the perfect email stall implementation.

Don't benchmark your AI SDR against your top 1% sales rep. The realistic and valuable goal is to create an agent that is more knowledgeable, consistent, and available than an average human. This creates a superior experience for most prospects and is an achievable bar to clear.

Don't let an AI agent generate sales copy from scratch. The key to creating high-quality, effective outreach is to train the model using the proven email templates and scripts from your highest-performing salesperson. This provides a strong baseline for the AI to iterate and test from.

AI's power is not in creating successful strategies from scratch, but in scaling your existing best practices. An AI agent cannot make a broken process work. First, identify what messaging and campaigns are effective, then use AI to execute them at a near-infinite scale, 24/7.

AI agents can continuously experiment with variables like subject lines, send times, and offers for each individual user. This level of granular, ongoing A/B testing is impossible to manage manually, unlocking significant performance lifts that compound over time.

Unlike training a human, feeding an AI SDR historical 'good' emails can limit its effectiveness. The better approach is to train it on core personas and ways to add value, allowing the AI to use its ability to scrape vast, real-time data for hyper-personalization.