From the course: Exploring Deterministic LLM Programming

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Increasing determinism in deep context

Increasing determinism in deep context

From the course: Exploring Deterministic LLM Programming

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Increasing determinism in deep context

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- [Instructor] Determinism is a huge problem when working with agentic coding tools. And one of the reasons why is the context is often the problem. The coding tool will need the proper context. Some of the latest coding tools do better at this, but what kind of context are they looking at? And this is where the abstract syntax tree becomes very important. With PMAT or the Pragmatic AI Labs MCP Agent Toolkit, this is able to extract the entire AST of multiple languages and even combine those multiple languages into a deep context. And this allows the coding assistants to then in one particular file, see what are the different functions, what are the different things that happen? Also, what is the complexity? Because it's an annotated deep context, it has things like the probability score, also the complexity, also the code coverage. And if you can look at this in one document, it makes it much more easy to ask…

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