Missing puzzle piece to LLM Enterprise Augmentation
Since early last year, when we led the development of an enterprise-level GenAI-as-a-service platform, we have understandably been bombarded with questions like “What are the art of possibles for …” or “Can LLM do …”
In this blog post, we will dive into a critical skill that will enable you to answer all these questions better — computational thinking. By the end of this blog post, you will have the answers to:
- What is computational thinking?
- Why is this relevant to developing LLM use cases?
- What is a four-step process that allows us to inject computational thinking into LLM use case development?
Computational thinking is a problem-solving framework that algorithmically breaks down a task into what I like to call atomic tasks. It involves designing a step-by-step algorithmic approach to solving a problem, identifying similarities and inefficiencies, and evaluating the relative importance of each step.
Imagine cooking a dish.
Recipe sourcing, grocery shopping, ingredient prep, cooking steps, and dishing are the atomic tasks…
