R-RAG: Building a Resilient Retrieval-Augmented Generation Service
Retrieval-augmented generation (RAG) has quickly become the architecture of choice for enterprises building AI applications that require access to external...
Posts about ai development
Browse 9 posts in this category
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...
From External Chaos to Business Value: The Power of AI Mocking
In today’s interconnected software landscape, applications rarely live in isolation. They depend on a multitude of external services and third-party APIs –...
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. Using LLMs in a production environment requires a lot of things to...
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. But AI has changed the game.
Unlock Cheaper & Faster AI Testing: Mocking Claude and MCP
Generative AI is quickly becoming ubiquitous in the software development space, with tools like Anthropic’s Claude offering rapid methodologies for code...
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. Whether you're building a dev tool that...
How to Mock OpenAI's APIs with Speedscale's ProxyMock
Developing APIs can often be a complex web of dependencies, external dependencies, and murky network traffic. In order to build better...