Enterprise AI deployments using “context stuffing” anti-patterns cost 100x more per agent run than tool-based architectures—a $0.50 versus $0.005 difference that TrueFoundry’s new MCP Gateway infrastructure aims to eliminate.

TrueFoundry’s announcement positions the Gateway as critical infrastructure for a market realizing that maximum context does not equal maximum intelligence. The platform directly targets the deployment bottlenecks that prevent organizations from scaling agent systems beyond experimental pilots.

Problem: The 100x Cost of the ‘Context Stuffing’ Anti-Pattern

A fundamental architectural flaw emerged from the “Context Window Wars” of 2024-2025: instead of building robust tool integrations, many early agent deployments adopted “context stuffing”—forcing models to process entire datasets in-prompt to find specific information.

Developers can build an AI chatbot in minutes, but deploying a production agent with tools and guardrails still takes weeks. Despite the explosion of AI model capabilities, the infrastructure layer that connects models to real-world tools remains surprisingly primitive. Dedalus Labs’ $11 million seed round, co-led by Kindred Ventures and Saga Ventures with Y Combinator participation, signals recognition that developer infrastructure—not model performance—has become the primary bottleneck in AI agent adoption.