Unlocking AI Coding Reliability with Traffic Replay
Discover why AI coding agents need traffic replay to bridge the gap between stochastic AI and deterministic software engineering.
Posts by Matthew LeRay
Matthew LeRay is a contributor to the Speedscale blog. • 8 posts published
Speeding up AI Coding Assistants using Deterministic Feedback
Every engineering leader has seen it: a senior developer is “in the zone”…then Slack pings, CI fails, or an AI suggestion derails everything.
5 Tips for Agent-to-Model Mocking
The near-ubiquity of LLM systems in 2025 has changed the game in many ways. While Large Language Models have been around for some time...
Take Control of Your AI Routing: Mocking Claude, Gemini, and GPT-4
A few short years ago, the idea of using a Large Language Model was relegated to some specific models and implementations for a given industry or use case.
Catch Prompt Misfires Before They Burn Trust in LLM
Large Language Models (LLMs) are incredibly powerful, but they are also incredibly fragile.
AI Code: How AI Is Changing How We Write and Test It
As a software engineer, I’ve always leaned on a solid foundation of code reviews, unit tests, and CI pipelines to ensure quality.
4 Tips for Developing Model Context Protocol Server
The Model Context Protocol (MCP) is rapidly becoming the connective tissue for agentic AI systems and IDE tooling.
Get Ahead of the Game: LLM Compliance and Mocking
As Large Language Models (LLMs) become increasingly integrated into enterprise applications, organizations face new challenges around compliance.
Try Speedscale free
Choose the desktop proxymock or the hosted cloud trial to get started.