ai-sdr
The ai-sdr Claude Code skill helps GTM leaders and sales teams design, deploy, and optimize AI-powered sales development systems that combine signal-based targeting, automated lead qualification, multi-channel sequencing, and human handoffs. Use it when planning AI SDR implementation, comparing platforms like 11x or Artisan, establishing qualification workflows, or architecting autonomous sales agent systems for outbound or hybrid sales motions.
git clone --depth 1 https://github.com/tech-leads-club/agent-skills /tmp/ai-sdr && cp -r /tmp/ai-sdr/packages/skills-catalog/skills/(gtm)/ai-sdr ~/.claude/skills/ai-sdrSKILL.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:
1. **Current sales motion** - Inbound-led, outbound-led, product-led, or hybrid?
2. **Team size** - Solo founder, small team (2-5), or scaled org (10+)?
3. **ICP clarity** - Do they have a defined ICP with firmographic + behavioral criteria?
4. **Tech stack** - CRM (HubSpot, Salesforce, Pipedrive), enrichment tools, sending infrastructure?
5. **Budget range** - Bootstrap ($500-1K/mo), growth ($1K-5K/mo), or scale ($5K+/mo)?
6. **Volume targets** - How many qualified meetings per month do they need?
7. **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
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)
```
### Key Metrics Benchmarks
```
+-------------------------------+-------------+-------------+
| Metric | Human SDR | AI SDR |
+-------------------------------+-------------+-------------+
| Prospects contacted/day | 50-80 | 1,000+ |
| Cold email reply rate | 5-8% | 8-12% |
| Cost per meeting booked | $800-1,500 | $150-400 |
| Meetings booked/month | 12-20 | 30-60 |
| Meeting show rate | 75-85% | 65-75% |
| Lead-to-opportunity rate | 20-25% | 15-20% |
| Ramp time | 3-6 months | 2-4 weeks |
| Annual cost (fully loaded) | $75K-120K | $12K-36K |
+-------------------------------+-------------+-------------+
```
Important: AI SDRs win on volume and cost. Human SDRs win on conversion quality and complex deal navigation. The best teams combine both.
---
## Section 2: The 4-Week AI SDR Deployment Program
### Week 1: Foundation (Signal Setup + List Building)
**Day 1-2: ICP Definition and Signal Configuration**Finds duplicate business logic spread across multiple components and suggests consolidation. Use when asking "where is this logic duplicated?", "find common code between services", "what can be consolidated?", "detect shared domain logic", or analyzing component overlap before refactoring. Do NOT use for code-level duplication detection (use linters) or dependency analysis (use coupling-analysis).
Detects misplaced classes and fixes component hierarchy problems — finds code that should belong inside a component but sits at the root level. Use when asking "clean up component structure", "find orphaned classes", "fix module hierarchy", "flatten nested components", or analyzing why namespaces have misplaced code. Do NOT use for dependency analysis (use coupling-analysis) or domain grouping (use domain-identification-grouping).
Maps architectural components in a codebase and measures their size to identify what should be extracted first. Use when asking "how big is each module?", "what components do I have?", "which service is too large?", "analyze codebase structure", "size my monolith", or planning where to start decomposing. Do NOT use for runtime performance sizing or infrastructure capacity planning.
Analyzes coupling between modules using the three-dimensional model (strength, distance, volatility) from "Balancing Coupling in Software Design". Use when asking "are these modules too coupled?", "show me dependencies", "analyze integration quality", "which modules should I decouple?", "coupling report", or evaluating architectural health. Do NOT use for domain boundary analysis (use domain-analysis) or component sizing (use component-identification-sizing).
Creates step-by-step decomposition plans and migration roadmaps for breaking apart monolithic applications. Use when asking "what order should I extract services?", "plan my migration", "create a decomposition roadmap", "prioritize what to split", "monolith to microservices strategy", or tracking decomposition progress. Do NOT use for domain analysis (use domain-analysis) or component sizing (use component-identification-sizing).
Maps business domains and suggests service boundaries in any codebase using DDD Strategic Design. Use when asking "what are the domains in this codebase?", "where should I draw service boundaries?", "identify bounded contexts", "classify subdomains", "DDD analysis", or analyzing domain cohesion. Do NOT use for grouping existing components into domains (use domain-identification-grouping) or dependency analysis (use coupling-analysis).
Groups existing components into logical business domains to plan service-based architecture. Use when asking "which components belong together?", "group these into services", "organize by domain", "component-to-domain mapping", or planning service extraction from an existing codebase. Do NOT use for identifying new domains from scratch (use domain-analysis) or analyzing coupling (use coupling-analysis).
AI frontend specialist and design consultant that guides users through a structured discovery process before generating any code. Collects visual references, design tokens, typography, icons, layout preferences, and brand guidelines to ensure the final output matches the user's vision with high fidelity. Use when the user asks to build, design, create, or improve any frontend interface — websites, landing pages, dashboards, components, apps, emails, forms, modals, or any UI element. Also triggers on "build me a UI", "design a page", "create a component", "improve this layout", "make this look better", "frontend", "interface", "redesign", or when the user provides mockups, screenshots, or design references. Do NOT use for backend logic, API design, database schemas, or non-visual code tasks.