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Qualify scraped leads and write personalized openers

Claude Code researches company news for icebreakers, qualifies leads from scraped lists and writes personalized opener variations.

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Use case overview

Claude Code researches company news for icebreakers, qualifies leads from scraped lists and writes personalized opener variations.

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Reported experience

  1. What they did

    In the thread, the concrete use described is feeding Claude Code a prospect list plus recent company news so it can automate research-heavy prospecting. The poster says it uses that context to qualify scraped leads and generate personalized opening-line variations, while humans still review the output because it can invent details.

  2. How it went

    The claimed upside was handling much more context than ChatGPT and producing openers that did not read like obvious AI. The stated limitation was hallucinations, so it was described as solid for research-heavy work but not safe to trust without review.

  3. Worth knowing

    The main catch the post highlights is mandatory human review of every output because Claude Code can hallucinate company details.

Example prompts

Try with Claude Code
Take my scraped lead list at [path/to/file] and qualify each lead against these criteria: [your criteria]. For the qualified ones, look up recent company news and write [3] variations of a personalized opener that reference it, with the source link for each. Save the results to a new file and tell me how many leads passed; don't send anything.

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