If you’ve been building with LLMs over the last year, you’ve likely hit the “Agent Wall.” You build a cool agent, give it a massive system prompt, and it works… until it doesn’t. As you add more capabilities, the context window gets bloated, the agent gets confused, and porting that logic to another platform (like […]
Read More →Large Language Models (LLMs) all predict text, but they differ a lot in how they follow instructions, use context, handle tools, and optimize for safety, speed, or cost. If you treat them as interchangeable, you’ll ship brittle prompts. If you treat them as different runtimes with different affordances, you’ll get reliable results. This post explains the major differences across […]
Read More →Listen up, engineers. We are past the “wow” phase. You know what an LLM is. You’ve likely integrated an API, generated some boilerplate code, and maybe even built a RAG pipeline. But here is the hard truth: if you are pasting the exact same prompt into GPT, Claude Sonnet, and Llama using the same strategy, […]
Read More →The AI Toolkit for Visual Studio Code is a game-changer for developers and AI engineers looking to simplify the creation of AI applications. This powerful extension streamlines the entire process, from development and testing to deployment, by seamlessly integrating with generative AI models both locally and in the cloud. Supporting a wide range of commercially […]
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