I Started Learning Forward Deployed Engineering — And My First Lesson Was to Question the Requirement
I recently started learning Forward Deployed Engineering alongside my System Design studies. I expected the first lessons to be mostly about Generative AI, LLMs, tools and application architecture. Instead, one of the first lessons was much more fundamental: Before building the requested solution, understand the problem behind the request. That sounds obvious. But it changes how I think about…
The author of the article emphasizes the importance of understanding the underlying business problem before jumping into engineering solutions, using the example of an e-commerce company requesting an AI chatbot. Initially, the engineer might focus on choosing an LLM, framework, and designing the API. However, the company might actually be struggling with long customer-support resolution times, repetitive work for support executives, inconsistent answers, increasing support costs, and lack of support outside business hours.
The author suggests that the real requirement should be to reduce the time required to resolve customer problems without reducing accuracy or customer trust. This distinction leads to a more effective engineering flow, which includes understanding the business problem, existing workflow, constraints, designing a technical solution, integrating with existing systems, testing and evaluating, and finally deploying the system.
The article also highlights the limitations of LLMs and the need for additional components, such as authorization checks, order validation, and audit trails, to ensure a successful implementation.
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