Garrett Scott

Head of Marketing

articles published

Garrett Scott is a marketing leader focused on go-to-market strategy for the AI and integration infrastructure space. He specializes in positioning technical products for two distinct audiences: AI-native companies building agentic systems, and established enterprises modernizing their stack around AI. His work centers on the infrastructure layer that connects products and AI agents to the tools and data they depend on, an area that has become foundational as agents move from demos into production. He brings a working understanding of how integration platforms enable agents to take real actions across systems, why reliable connectivity is a prerequisite for trustworthy AI, and how technical decision makers evaluate this category. Across his career he has led demand generation, messaging, and positioning at high-growth software companies, translating complex technical capabilities into clear value for developers and buyers. He combines hands-on fluency with the modern marketing and data stack with a strategic view of how the AI and integration markets are evolving.

Comparison

The Best Way to Give an AI Agent Tool-Calling Access to Hundreds of SaaS Apps

The best way to give an AI agent tool-calling access to hundreds of SaaS apps: build in-house, open-source MCP, or a tool provider. Compared, with criteria.

Comparison

What Are the Top Unified APIs?

A side-by-side look at the top unified APIs (Nango, Merge, Apideck, Unified.to, Paragon) with architecture, connectors, MCP support, and who each fits.

Integrations

I Need Integrations for Agents. What are My Options?

The four ways to give AI agents integrations: tool calling, RAG data ingestion, workflow builders, and bidirectional sync. Compared, with platforms for each.

Thought Leadership

Should I Buy an Integrations Platform or Build In-House?

Build integrations in-house when you need only a few simple, stable connections your team can maintain without pulling focus from the core product. Buy an integrations platform once customers request many integrations, maintenance starts eating engineering time, or missing connections slow sales and onboarding.

Engineering

How to Build Connectors for RAG

A RAG connector must authenticate securely with the source system, extract the right content, normalize it into a consistent format, preserve user and tenant permissions, and keep indexed data fresh over time.

Engineering

How to Optimize Tool Calling for AI Agents

To optimize tool calling, improve the full path from user request to tool selection, input generation, and task completion. The biggest gains usually come from clearer tool descriptions, simpler schemas, atomic tools, dynamic tool filtering, model-and-harness testing, and ongoing evals rather than simply switching to a larger model.