how applications share context with large language models (LLMs). MCP provides a standardized way to connect AI models to different data sources and tools, enabling them to work together more effectively.
translates into a series of tokens. The model processes these input tokens, generates its response as tokens and then translates it to the user’s expected format.
on codebase size, query complexity, and conversation length. The average cost is $6 per developer per day, with daily costs remaining below $12 for 90% of users.
curating and maintaining the optimal set of tokens (information) during LLM inference, including all the other information that may land there outside of the prompts.
relying on them to actually do the right thing, not just sound like they are. That trust is hard to build and easily eroded; something to keep in mind as we hand them more and more autonomy. Trust Gunnar Morling