LLM

Fast Code Generation with Agents, Rails, and MongoDB

| Gen AI |

Agents generate useful code quickly when the project is simple, documented, and predictable. Rails helps because it has strong conventions. MongoDB helps when the data already exists and the app does not need SQL migrations. The main rule is still KISS: complexity is the enemy. Use README as the Source of Truth The best optimization… more

RAG in Practice: Anti-Patterns, Best Practices, and Why Simplicity Wins

| Gen AI | ,
RAG in Practice: Anti-Patterns, Best Practices, and Why Simplicity Wins - LLM, rag

Retrieval-Augmented Generation (RAG) promises to combine external knowledge sources with the capabilities of large language models. In theory, the concept is simple: retrieve the right information, provide it to the model, and generate an answer. In practice, many implementations fail to deliver the expected results. The problem is rarely the model itself. It is rarely… more

Why Law Firms Need Their Own LLM/RAG

| Gen AI |
Why Law Firms Need Their Own LLM/RAG - LLM

The legal industry faces a digital transformation challenge. Generative AI models offer tremendous potential – from automating document analysis to supporting legal opinion preparation. However, standard solutions like ChatGPT or public models carry risks that law firms cannot afford. A proprietary LLM/RAG system is the answer to these challenges. Why It’s Worth Investing in Your… more