Native First
Claude auto-checks 150+ integrations + how to save 30x on model costs
This course explains the methodology behind AutoClaygent. The tool handles all of this automatically—you don't need to do any of this manually. Understanding the "why" helps you get better results and debug edge cases.
The Most Common Claygent Mistake
Before you write a single line of prompt, you need to check if Clay already has a native integration that does what you want. This is the #1 mistake I see people make.
Clay has 150+ native integrations that are cheaper, faster, and more reliable than Claygent. Always check these first.
AutoClaygent automatically checks Clay's 150+ integrations before building any Claygent. No hunting around Clay's interface—no dealing with Clay's terrible search. Claude Code does the lookup for you and recommends the best option.
The integrations catalog is updated automatically, so you'll always know about Clay's newest integrations without having to search for them.
Native vs. Claygent: When to Use Each
| Criteria | Native Integration | Claygent |
|---|---|---|
| Cost | Lower | Higher |
| Speed | ~1-2 seconds | ~10-30 seconds |
| Reliability | Very high | Variable |
| Flexibility | Fixed schema | Fully customizable |
| Best for | Data behind paywalls, HTML-based data (tech stacks via BuiltWith) | Custom logic, multi-source synthesis, fallbacks |
The Native-First Checklist
AutoClaygent runs this checklist automatically. Claude Code checks all 150+ integrations for you—much faster than Clay's built-in search.
Before building any Claygent, ask yourself:
- Does Clay have a native integration for this?
Check the integrations panel for providers like FullEnrich, Swordfish, Harmonic.ai, etc. - Can I chain multiple native integrations?
Often a waterfall of 2-3 native providers beats one Claygent. - Do I need custom logic?
Only use Claygent when you need logic that native integrations can't provide.
Common Use Cases: Native vs. Claygent
Finding Emails & Phones
Use Native: Clay has 10+ contact providers (FullEnrich, Swordfish, LiveData, etc.). Set up a waterfall and you'll get better results than any Claygent.
Company Enrichment
Use Native: Harmonic.ai, Dealroom.co, or The Swarm for company data. Only use Claygent if you need very specific data these don't provide.
Tech Stack Detection
Use Native: BuiltWith reads the actual HTML/JavaScript source of websites—something Claygent can't do since it only sees rendered content. Native integrations like BuiltWith access data that's invisible to AI web browsing.
Custom Website Scraping
Use Claygent: When you need to extract specific data from a website that no provider offers, Claygent is the right tool.
When you do use Claygent, use it as a fallback after native integrations. This way you get the speed and cost benefits of native for most rows, and Claygent only runs when needed.
Model Cost Savings
AutoClaygent flips the economics of AI: use the smartest model once to build the prompt, then run it on the cheapest model thousands of times.
| Model | Cost per Claygent run | Use case |
|---|---|---|
| Claude Opus | 15 credits | Building/evaluating prompts (AutoClaygent) |
| GPT-4.1-Nano | 0.5 credits | Running prompts at scale (your Clay table) |
That's a 30x cost difference. By using Claude Opus to BUILD the prompt (once), you can RUN it on GPT-4.1-Nano (thousands of times) and get the same quality at 1/30th the cost.
BYOK (Bring Your Own Key)
For even more savings, bring your own OpenAI API key to Clay. Go to Settings → Integrations → OpenAI and add your API key. Claygent runs then cost your OpenAI pricing, not Clay credits. This is especially powerful for high-volume use cases.
Key Takeaways
- AutoClaygent auto-checks Clay's 150+ native integrations before building any prompt
- Native integrations are faster and more reliable—use them when possible
- Some data (like tech stacks) requires native integrations because Claygent can't read HTML source
- Use Claygent for custom logic, fallbacks, or data no provider offers
- Save 30x on model costs by building prompts once with Opus, running them with GPT-4.1-Nano