You are an expert at crafting multi-touch, founder-to-founder outreach sequences in 2026 that feel persistent yet respectful, helpful rather than salesy, and achieve strong cumulative reply rates from indie hackers, solo founders and bootstrapped makers.
Create a complete 3-touch outreach sequence for ONE specific lead, using three different channels in this exact order:
1. First touch: LinkedIn connection request + short note (max 280 characters)
2. Second touch: Cold email (subject line + 4–6 sentence body)
3. Third touch: Twitter/X DM (1–3 short sentences)
The entire sequence should feel like a natural, escalating conversation from one founder who genuinely noticed the other person's work — never aggressive, never spammy, never repeating the same phrase across touches.
Strict rules for the whole sequence:
- Tone across all messages: warm, peer-like, curious, zero corporate/sales buzzwords
- No hard CTAs in any touch ("book a call", "let's chat", "interested?", "demo", "free trial", "hop on", "reply if…")
- Each touch must reference something specific about the lead (from profile, recent post, tweet, product, website, etc.)
- Show progression: Touch 1 is light & connection-focused; Touch 2 adds a bit more context/value; Touch 3 is slightly warmer/more direct but still low-pressure
- Never mention "follow-up", "following up", "circle back", "touching base" — make it feel organic
- Keep every message short: LinkedIn note <280 chars, email body 100–160 words, Twitter DM <240 chars
- End each touch with a soft, open-ended question or gentle observation that invites reply without demanding one
Input variables I'll provide:
[Their full name]
[Their first name] (for greetings)
[Their company / product name]
[Their Twitter/X handle without @]
[Their LinkedIn profile URL or recent LinkedIn post summary — if available]
[One specific recent tweet / post / observation from their profile — quote or very brief description]
[Their approximate current stage / MRR — e.g. "around 3k MRR, flat for 4 months", "just launched v2", "stuck at 5–6k MRR"]
[Their main visible lead-gen or growth struggle — e.g. "manual Twitter lead qualification", "low cold email replies", "high churn on first paid users"]
[My full name]
[My first name] (for signing messages)
[My Twitter/X handle without @]
[My product name]
[One short neutral sentence describing what I do / my core angle — e.g. "building AI tools that cut manual lead qualification time in half for indie makers"]
Output format — only this, nothing else:
Touch 1 – LinkedIn Connection Request
[the full connection note text]
Touch 2 – Cold Email
Subject: [subject line]
[full email body starting with "Hey [first name]," and ending after the last sentence]
Touch 3 – Twitter/X DM
[the full DM text]
Separate each touch with a blank line.
No explanations, no extra labels, no character counts, no alternatives — only the three touches exactly as formatted above.
This prompt generates a complete 3-touch outreach sequence across three different channels (LinkedIn connection request, cold email, and Twitter/X DM), all personalized to a single lead and written in a natural, founder-to-founder voice.
It solves the common problem of outreach feeling disconnected, repetitive, or overly salesy by creating a gentle, progressive conversation that builds familiarity and trust over time without ever pushing for a meeting or sale.
The main win: a ready-to-use, cohesive sequence that feels organic and respectful — many users find it produces noticeably higher cumulative reply rates and warmer responses compared to one-off messages or aggressive follow-up chains.
To produce the most coherent and high-quality sequence, prepare these inputs before running the prompt:
[Their full name]
The person’s full first and last name (e.g. Sarah Kim)
[Their first name]
Just their first name for natural greetings (e.g. Sarah)
[Their company / product name]
The name of their current startup, tool or main project (e.g. Flowbase, QueueDash, WaitlistKit)
[Their Twitter/X handle without @]
Their X handle without the @ symbol (e.g. sarahkimdev, queue_dash)
[Their LinkedIn profile URL or recent LinkedIn post summary — if available]
Either the direct LinkedIn profile link or a very brief summary of a recent post/activity (optional but helpful for stronger personalization).
Examples: linkedin.com/in/sarahkimdev, recently posted about struggling with LinkedIn reply rates
[One specific recent tweet / post / observation from their profile]
The most important input — one concrete, recent detail (ideally from the last 30 days). Quote or paraphrase closely.
Examples:
"tweeted last week: 'still manually qualifying every Twitter lead — takes forever'"
"posted about flat growth at 4.2k MRR for 5 months"
"mentioned in a thread that support tickets are eating build time"
[Their approximate current stage / MRR]
A short description of their current traction level (helps the AI choose relevant pain points and tone).
Examples: around 3k MRR, flat for 4 months, just launched v2, stuck at 5–6k MRR, pre-1k MRR, early beta
[Their main visible lead-gen or growth struggle]
One clear pain point you’ve observed (keep it specific).
Examples: manual Twitter lead qualification, low cold email replies, high churn on first paid users, spending too much time on support tickets
[My full name]
Your full name as it appears on social/email (e.g. Julia Reyes)
[My first name]
Your first name for signing messages (e.g. Julia)
[My Twitter/X handle without @]
Your own X handle without the @ (e.g. juliareyes_ai)
[My product name]
The name of your tool or project (e.g. LeadSieve, ReplyFlow)
[One short neutral sentence describing what I do / my core angle]
A concise, factual summary of your work — avoid hype or benefit promises.
Examples:
"building AI tools that cut manual lead qualification time in half for indie makers"
"creating AI agents that automate repetitive outreach tasks without sounding robotic"
"working on infrastructure that helps bootstrapped founders improve cold email deliverability"
For natural progression across touches, consistent warm tone, and strict avoidance of any sales language in 2026:
Best overall: Claude 4 / Claude 3.7 Sonnet / Claude 4 Opus
→ Outstanding at maintaining a coherent founder-to-founder voice across multiple messages, ensuring gentle escalation, and strictly following the no-CTA / no-repetition rules
Very good & fast: Gemini 2.5 Pro / Gemini 2.5 Flash
→ Excellent at keeping each touch concise while preserving personality and logical flow between steps
Strong alternative: GPT-4o latest / o1 / Grok 3
→ Reliable for multi-part outputs; if the tone ever drifts toward being too forward, reinforce the “peer-like, zero hard CTAs, organic progression” instructions in a short system prompt
Example inputs you provide:
Their full name: Sarah Kim
Their first name: Sarah
Their company / product name: Flowbase
Their Twitter/X handle without @: sarahkimdev
Their LinkedIn profile URL or recent LinkedIn post summary: recently posted about low LinkedIn reply rates
One specific recent tweet / post / observation: tweeted last week "honestly spending half my week qualifying Twitter leads and most aren’t even close to paying"
Their approximate current stage / MRR: flat at 3.8k MRR for months
Their main visible lead-gen or growth struggle: manual Twitter lead qualification taking too much time
My full name: Julia Reyes
My first name: Julia
My Twitter/X handle without @: juliareyes_ai
My product name: LeadSieve
One short neutral sentence describing what I do / my core angle: building an AI tool that automatically ranks Twitter conversations by buying intent
Typical output you’ll get (ready to use):
Touch 1 – LinkedIn Connection Request
Hey Sarah, saw your recent post about LinkedIn replies being tough to come by — felt that one myself. Fellow solo founder here building in the outreach space. Would be cool to connect.Touch 2 – Cold Email
Subject: That Twitter lead qualification time sink?Hey Sarah,
Noticed your tweet last week about spending half the week manually qualifying Twitter leads — that used to eat my calendar too when I was at a similar stage with my last project.
A lot of founders around 3–4k MRR hit this wall where the manual sorting starts slowing everything down, especially when most convos don’t lead anywhere.
I built LeadSieve — it ranks Twitter conversations by real buying intent so you can focus on the few that actually matter.
I’ve seen it cut qualification time down quite a bit for a couple other makers I know.
Curious if that kind of bottleneck is still the main thing holding Flowbase back right now?Julia
Touch 3 – Twitter/X DM
Hey sarahkimdev,was thinking about your tweet on Twitter lead qualification eating half your week — still dealing with that chaos?
I’m playing with LeadSieve which tries to surface only the convos with actual buying signals.
Does anything like that sound even slightly useful at your stage or is it a different kind of bottleneck these days?Julia
Get expert guides, automation blueprints, and proven AI strategies to transform your business. Stay ahead with our curated insights.
