This debate often gets framed as Should researchers use AI for literature reviews?
I think the real question is different.
Is it ethical to spend hundreds of researcher hours on mechanical work when that time could be spent advancing actual knowledge?
Think about a researcher spending an entire weekend searching papers, skimming irrelevant abstracts, copying citations, and fixing references. That s not insight or discovery. That s overhead.
What s worked for us looks very different from spray-and-pray.
We ve learned that outbound works when it s intentional at every step.
A few things that made the biggest difference for us:
Getting the ICP really right. Sometimes the first outreach isn t to the buyer, but to someone who can open the door. Personalization isn t optional. Company context, role, recent updates. Generic gets ignored fast. Channels are chosen by output, not comfort. We double down on what actually converts. The first message rarely works. Conversations usually start around the third or fourth touch, if there s value each time. Timing matters more than volume. Funding news, hiring, social posts. Showing up when the problem is top of mind changes everything. We focus on relationships, not just pipeline. Some buy later. Some refer. All conversations compound. Context before calls helps. If someone engages multiple times, the conversation feels very different. Signals matter. Engagement often tells you when to reach out, not just who.
