The Developer’s Guide to Debugging AI-Generated Code
Master debugging AI-generated code by spotting flawed logic, removing deprecated APIs, and catching hallucinated functions before they ship.
Posts by Matt Tanner
Matt Tanner is a contributor to the Speedscale blog. • 6 posts published
Train on Gold, Not Garbage - Making Powerful AI Models from Golden Data
In 2025, training AI and Large Language Models is no longer just about scale - it’s about the quality of the signal. Artificial intelligence (AI) is a field...
Enterprise Vibe Coding
_Expanded explanations, guardrails, and practical check-lists included._ Vibe coding is a new approach to building software that emphasizes rapid...
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...
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 –...
How to Mock AI APIs Using Proxymock
Master AI API mocking with Proxymock. Learn essential strategies for testing AI applications, reducing costs, and building reliable AI integrations.
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