The Art of the Follow-Up: Using AI to Nurture Your Network

Great relationships are built between posts - in the quiet follow-ups. Use AI to help with structure, tone, and speed; then add a human first line so it feels like you. Below is a complete system: timing, templates, prompts, etiquette, measurement, and scaling.

1) DM after a comment (convert public interest into a warm chat)

When someone comments on your post, reply publicly, then DM while context is fresh. Thank them, callback something specific they said, and offer a relevant micro-asset.

• Pattern: Thanks → specific callback → optional micro-asset → gentle question.
• Avoid generic “thanks!” - it stalls the conversation.

2) Post-call recap (reduce friction, confirm momentum)

Send a concise recap within 24 hours. Make it skimmable and confirm the next step with a date. AI can tighten your notes; you add the human context.

• 3 bullets: problem → suggestion → next step/date.
• Ask permission before sending heavy docs or links.

Thanks for today!
• Goal: shorten onboarding by ~30%
• Plan: reduce steps + add day-1 prompts
• Next: share draft by Tue 10:00
OK to send a 1-pager now?

Turn these call notes into a 3-bullet recap.
Be concrete, remove fluff, end with 1 confirmation question.

3) Re-engage dormant threads (value first, no pressure)

If a promising chat cooled off, re-enter with new value: a small win, a benchmark, or a template. Keep it optional and respectful.

• Reference time or topic to jog memory (“Since we last spoke about X…”).
• Offer something small and useful - not a pitch.

4) Micro-assets that unlock replies (give first, then ask)

Micro-assets are tiny, high-signal artifacts you can offer without commitment. Use AI to draft them fast, then polish with specifics.

• 1-pager checklist (e.g., onboarding steps, review cadence).
• Short SOP snippet (3–5 steps).
• Before/after mini-story with 1 number.

5) Timing, cadence, and prioritisation

Consistent timing outperforms random bursts. Prioritise by intent + fit; don’t chase every thread.

• Cadence: 24–48h → 7–14 days → 30 days → park.
• Signals to prioritise: specific questions, shared metrics, mutual connections.
• Low-intent signals: emoji replies, generic praise - respond, but deprioritise.

6) AI etiquette & compliance (keep it human)

• No mass DM automation. Draft with AI; you approve and send.
• Personalise line 1 yourself. Avoid deceptive claims; add qualifiers if needed.
• Respect privacy: don’t quote private messages without consent.

7) Templates you can adapt

Appreciate your take on [specific point].
Curious: how are you handling [related detail]?
If useful, I can share a 4-line checklist we used.

Since we last spoke about [topic], we tested [X] and saw [Y].
Happy to share the short SOP we used if that helps - no pressure.

8) Objection handling (friendly, pressure-free)

• “Now’s not a good time.” “All good - shall I send a one-pager you can skim later?”
• “We already use a tool.” “Makes sense. If useful, I can share the 3 checks we run alongside tools to avoid blind spots.”
• “What’s the ROI?” “Typical win we’ve seen: [metric]. If you want, I can send a quick calc model.”

9) Measurement that actually matters

Optimise for depth and pipeline, not vanity.

• Depth: reply rate, average response length, # of back-and-forths.
• Velocity: time from post/comment → first DM → booked call.
• Outcomes: discovery calls, trials, referrals - tie back to the originating post.

10) Scale without losing the human touch

• Create 4-6 DM “blocks” (openers, callbacks, offers, closers). Mix-and-match.
• Use AI to propose 3 variants per block; you choose one and tweak specifics.
• Keep a living doc of best-performers (open rate, reply rate, call rate).