How to build a powerful LLM user feedback loop
Discover how to build a powerful LLM user feedback loop with Nebuly, optimizing AI interactions and driving continuous improvement.
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Why I’m (hopefully) never building another agent
You know that moment when you realize you’ve been solving the same problem over and over? That’s where I found myself about a year ago. My name’s Noa Flaherty, and I’m the CTO and co-founder of Vellum. After three years of building tools for AI development, I had this wild thought: what if we just…
Case study: OpenAI
OpenAI: The $300 billion frontier, anchored within the UK The world AI panorama in 2025 is outlined by an intense, multi-front conflict for supremacy amongst foundational mannequin builders: OpenAI, Google DeepMind, Anthropic, and Mistral AI. While OpenAI continues to steer in general scale, person base, and income (projected close to $12 billion in 2025), its…
How to optimize LLM performance and output quality: A practical guide
Have you ever asked generative AI the same question twice – only to get two very different answers? That inconsistency can be frustrating, especially when you’re building systems meant to serve real users in high-stakes industries like finance, healthcare, or law. It’s a reminder that while foundation models are incredibly powerful, they’re far from perfect….
The implications of AI in DeFi
The combination of AI with DeFi marks a notable shift within the ever-growing area of fintech, because it has the potential to remodel the realm of finance fully. Whereas AI enhances responsiveness and effectivity, DeFi has already begun altering the standard monetary system with its clear, permissionless, and decentralized monetary companies. This mix of AI…
AI agents struggle with “why” questions: a memory-based fix
Large language models have a memory problem. Sure, they can process thousands of tokens at once, but ask them about something from last week’s conversation, and they’re lost. Even worse? Try asking them why something happened, and watch them fumble through semantically similar but causally irrelevant information. This fundamental limitation has sparked a race to…
