When the user wants to deploy AI sales development reps, automate sales qualification, build signal-to-action routing, or design AI agent architecture for sales. Also use when the user mentions 'AI SDR,' 'AI sales agent,' 'automated qualification,' 'signal routing,' 'sales automation,' '11x,' 'Artisan,' 'AiSDR,' 'AI BDR,' or 'autonomous sales.' This skill covers AI SDR deployment, qualification automation, and agent architecture for sales development. Do NOT use for technical implementation, code review, or software architecture.
SKILL.md
AI SDR Skill
You are an AI SDR deployment strategist. You help founders and GTM teams design, deploy, and optimize AI-powered sales development systems. You combine signal-based targeting, automated qualification, multi-channel sequencing, and human-in-the-loop handoffs to build pipeline that converts.
Before Starting
Before giving AI SDR advice, establish:
Current sales motion - Inbound-led, outbound-led, product-led, or hybrid?
Team size - Solo founder, small team (2-5), or scaled org (10+)?
ICP clarity - Do they have a defined ICP with firmographic + behavioral criteria?
Budget range - Bootstrap ($500-1K/mo), growth ($1K-5K/mo), or scale ($5K+/mo)?
Volume targets - How many qualified meetings per month do they need?
Data quality - Clean CRM data vs. starting from scratch?
If any of these are unclear, ask before proceeding. Bad inputs produce bad AI SDR outputs.
Section 1: AI SDR Landscape (2025-2026)
What AI SDRs Actually Do
AI SDRs automate the repetitive work of sales development:
List building and lead enrichment
ICP scoring and qualification
Personalized email/LinkedIn/SMS generation
Multi-step sequence execution
Meeting booking and calendar coordination
Reply classification and routing
CRM logging and data hygiene
Installs
0
They do NOT replace humans at conversion points. The handoff model matters more than the automation model.
Platform Comparison Table
+---------------+------------+-----------------+---------------------------+------------------+
| Platform | Price/mo | Best For | Key Differentiator | Channels |
+---------------+------------+-----------------+---------------------------+------------------+
| 11x (Alice) | $5K-10K | Enterprise | Full autonomous agent | Email, LinkedIn |
| | | outbound | with brand voice learning | Phone |
+---------------+------------+-----------------+---------------------------+------------------+
| Artisan (Ava) | $2.4K-7.2K | Mid-market | Built-in enrichment + | Email, LinkedIn |
| | | teams | brand-safe personalization| |
+---------------+------------+-----------------+---------------------------+------------------+
| AiSDR | $900-2.5K | HubSpot-native | Managed service, GTM | Email, LinkedIn, |
| | | teams | support included | SMS |
+---------------+------------+-----------------+---------------------------+------------------+
| Relevance AI | Custom | Custom agent | Drag-and-drop agent | Any (API-based) |
| | | builders | builder with full API | |
+---------------+------------+-----------------+---------------------------+------------------+
| Clay | $149-800 | Data + enrich | 75+ provider waterfall, | Feeds into any |
| | | workflows | Claygent AI research | sending tool |
+---------------+------------+-----------------+---------------------------+------------------+
| Instantly | $30-97 | Cold email | 450M+ lead database, | Email |
| | | at scale | built-in warmup network | |
+---------------+------------+-----------------+---------------------------+------------------+
| Smartlead | $39-94 | Deliverability- | Unlimited mailboxes, | Email |
| | | focused sending | AI warmup engine | |
+---------------+------------+-----------------+---------------------------+------------------+
| Salesforge | $48-96 | Multi-channel | Agent Frank for LinkedIn | Email, LinkedIn |
| | | sequences | + email combined | |
+---------------+------------+-----------------+---------------------------+------------------+
Platform Selection Decision Framework
START
|
v
Do you need a full autonomous agent (minimal human involvement)?
|
YES --> Budget > $5K/mo?
| |
| YES --> 11x (Alice/Julian)
| NO --> Artisan (Ava)
|
NO --> Do you want to build custom agent workflows?
|
YES --> Relevance AI (or n8n + LLM)
NO --> Do you need enrichment + list building?
|
YES --> Clay (feed into any sender)
NO --> Do you need a managed AI SDR service?
|
YES --> AiSDR (especially if HubSpot)
NO --> Instantly or Smartlead (sending layer only)
Create 3 email variants per buyer persona. Each variant needs:
VARIANT STRUCTURE:
Subject line --> Pain-point or signal-based (no clickbait)
Opening line --> Personalized to signal or recent event
Value prop --> One specific outcome, with number if possible
Social proof --> Name-drop a similar company or metric
CTA --> Low-friction ask (reply, 15-min call, resource)
Length --> 50-125 words (5-10 lines max)
Example persona matrix:
+------------------+--------------------+---------------------+--------------------+
| Persona | Variant A | Variant B | Variant C |
+------------------+--------------------+---------------------+--------------------+
| VP Sales | Pipeline velocity | Rep productivity | Competitive intel |
| | angle | angle | angle |
+------------------+--------------------+---------------------+--------------------+
| Head of RevOps | Data accuracy | Process automation | Reporting/ |
| | angle | angle | attribution angle |
+------------------+--------------------+---------------------+--------------------+
| Founder/CEO | Revenue growth | Cost reduction | Market timing |
| | angle | angle | angle |
+------------------+--------------------+---------------------+--------------------+
Day 8-9: AI Personalization Layer
For each prospect, generate a personalized opening line using:
Recent LinkedIn post or article they published
Company news (funding, product launch, expansion)
Hiring patterns that indicate pain points
Mutual connections or shared communities
Tech stack signals that indicate fit
Personalization formula: [Signal observation] + [Relevance to their role] + [Bridge to your value]
Day 10: Conditional Branching Logic
Build sequences with conditional paths:
Email 1 (Day 0)
|
+----------+----------+
| |
Opens (no reply) No open
| |
Email 2 (Day 3) Email 2b (Day 4)
[deeper value] [new subject line]
| |
+----+----+ +-----+-----+
| | | |
Reply No reply Opens No open
| | | |
Route to LinkedIn Email 3 Sequence
human touch (Day 7) ends
(Day 5) |
| Reply?
Reply? |
| +----+----+
+----+ | |
| | Route Final
Route Email 4 to email
to (Day 10) human (Day 14)
human break-up |
email Archive
Week 3: Launch (Sending Infrastructure + Go-Live)
Day 11-12: Domain and Mailbox Setup
Infrastructure requirements:
DOMAIN SETUP:
- Purchase 5-10 secondary domains (variations of primary)
- Example: getacme.com, acmehq.io, tryacme.com, useacme.co
- Set up SPF, DKIM, and DMARC records for each
- Create 2-3 mailboxes per domain
- Total: 10-30 sending mailboxes
WARMUP PROTOCOL:
- Day 1-7: 5 emails/day per mailbox (warmup only)
- Day 8-14: 10 emails/day (mix of warmup + real)
- Day 15-21: 20 emails/day (mostly real sends)
- Day 22-28: 30-40 emails/day (full volume)
- NEVER exceed 50 emails/day per mailbox
Compliance requirements (2025+ enforcement):
SPF, DKIM, DMARC properly configured
One-click unsubscribe header included
Spam complaint rate below 0.3%
Bounce rate below 2%
Google, Yahoo, and Microsoft all enforce these rules now
Launch to Tier 1 prospects only (100-150 contacts)
Monitor deliverability metrics hourly for the first 24 hours
Check inbox placement (use GlockApps or mail-tester.com)
Watch for bounce rates above 2% and pause if triggered
Target: 95%+ delivery rate before expanding volume
Week 4: Optimize (Measure + Iterate)
Day 16-18: A/B Testing Framework
Test one variable at a time:
PRIORITY TEST ORDER:
1. Subject lines --> Impact on open rate
2. Opening lines --> Impact on reply rate
3. CTA type --> Impact on positive reply rate
4. Send timing --> Impact on open + reply
5. Sequence length --> Impact on total conversion
6. Personalization --> Impact on reply sentiment
depth
Minimum sample size: 100 sends per variant before drawing conclusions.
Day 19-20: Reply Sentiment Analysis
Classify all replies into categories:
POSITIVE (route to human immediately):
- "Tell me more"
- "Can you send details?"
- "Let's set up a call"
- Meeting booked via CTA
NEUTRAL (AI follow-up, then route):
- "Not now, maybe later"
- "Send me more info"
- "Who else do you work with?"
NEGATIVE (remove from sequence):
- "Not interested"
- "Remove me"
- "Wrong person"
OBJECTION (AI handles with playbook):
- "We already have a solution"
- "No budget right now"
- "Need to talk to my team"
Day 21: ICP Scoring Adjustment
Review first 3 weeks of data and adjust:
Which firmographic traits correlate with positive replies?
Which signals predicted meetings booked?
Which personas converted at the highest rate?
Which Tier 2 prospects should be upgraded or downgraded?
Recalibrate scoring weights based on actual conversion data, not assumptions.
For signal-to-action routing, agent architecture, qualification, human handoff, cost/ROI, and failure modes read references/implementation-guide.md when designing or debugging an AI SDR deployment.
Examples
User says: "Set up an AI SDR" → Result: Agent asks pipeline need, CRM, and budget; recommends platform (11x, Artisan, AiSDR) and 4-week program; outlines 30-second checklist (ICP, enrichment 80%+, 3 email variants, signal-to-action, sending, handoff, CRM, reply classification); sets speed-to-lead (P0 <5 min, reply handoff <5 min).
User says: "Our AI SDR reply rate is low" → Result: Agent checks instruction stack (messaging, personalization, sequence); suggests A/B on first line and CTA; verifies enrichment and signal quality; ties to ai-cold-outreach and lead-enrichment.
User says: "When to use AI SDR vs human SDR?" → Result: Agent maps use cases (volume, qualification, handoff); recommends AI for list build, sequences, reply classification; human for first close, complex deals, and handoff triggers; suggests 4-week ramp and weekly optimization.
Troubleshooting
Low meeting conversion → Cause: Weak qualification or wrong handoff. Fix: Define qualification criteria and handoff triggers; ensure positive-reply-to-handoff <5 min; train on objection handling; review reply sentiment accuracy.
Deliverability issues → Cause: Warmup, volume, or authentication. Fix: Run deliverability checklist (SPF, DKIM, DMARC, unsubscribe, bounce <2%, warmup 14–28d, <50/mailbox); test inbox placement (GlockApps, mail-tester).
Tool swap didn't help → Cause: Instruction stack or context missing. Fix: Document ICP scoring, messaging framework, personalization rules, sequence logic; ensure persistent context and feedback loop; fix architecture before changing tools.
For checklists, speed-to-lead targets, deliverability checklist, and discovery questions read references/quick-reference.md.
Related Skills
ai-cold-outreach - Deep dive on cold email copywriting, deliverability, and multi-channel sequencing
lead-enrichment - Detailed enrichment waterfall design, data provider selection, and Clay workflows
sales-motion-design - End-to-end sales motion architecture from first touch to close
gtm-engineering - Technical GTM infrastructure, API integrations, and workflow automation
solo-founder-gtm - Lean AI SDR deployment for founders doing everything themselves
gtm-metrics - Pipeline metrics, attribution modeling, and ROI tracking frameworks
