The first bottleneck in every sales pipeline is finding qualified leads and learning enough about them to reach out well. AI dramatically reduces the research time per prospect. Today you build an AI-assisted prospecting workflow.
By the end of this lesson you will define your ICP with AI assistance, use AI to research prospects from LinkedIn and company websites, score a list of 20 leads using an AI-generated scoring rubric, and write three personalized opening lines for different prospect types.
AI prospecting is the foundation of Day 2. Every concept that follows builds on the mental model you establish here. The most effective approach is to understand the principle first, then apply it — skipping straight to implementation creates gaps that compound into confusion later.
Work through each example in this lesson sequentially. The concepts connect, and the order is deliberate. If something is unclear, slow down at that point rather than pushing past it — a ten-minute pause now saves hours of debugging later.
Understanding AI prospecting requires seeing it in motion. The code below is not a complete application — it is a minimal, working illustration of the key mechanism. Study the pattern, run it, break it deliberately, then fix it. That cycle builds real comprehension.
Once the basic pattern works, the logical next step is lead qualification. This is where the abstraction becomes useful — you move from understanding the mechanism to applying it to real problems. The transition is usually smaller than it feels. Most of the hard work happened in Section 1.
ICP definition completes today's picture. It is where AI prospecting and lead qualification converge into a pattern you can apply to novel problems. This integration step is often where the day's learning consolidates — if the earlier sections felt abstract, this one typically makes them click.
Implementing AI prospecting alone handles the happy path. Real systems encounter edge cases, invalid input, and unexpected state. Missing lead qualification means missing those guards.
Combining AI prospecting with lead qualification gives you a complete, defensible implementation. The extra lines cost ten minutes; the robustness they add is worth hours of debugging time.
Several mistakes appear consistently when engineers encounter AI for Prospecting for the first time. Recognizing them now costs nothing; encountering them in production costs hours.
Two intensive days (Thu–Fri) with an instructor who has taught thousands of engineers. Cohorts in 5 cities, June–June–October 2026 (Thu–Fri).
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