ETExamTower
Sign in
810-110Updated 1d ago · Sep 4, 2026

Cisco AI Technical Practitioner (AITECH)

98 questions across 1 topics, with suggested answers, explanations where available, and imported community discussion. The first 9 questions are free to preview.

Browse questions Practice mode

Topics

#TopicQuestionsFree
1Development and Workflow Automation989

Preview

9 of 98 accessible
Question 1 · Development and Workflow Automation Open

A team uses AI to scaffold a new microservice. What does this process involve?

Answer: B Scaffolding in software development means generating the initial skeleton or boilerplate structure for a project—such as base file/folder layout, starter classes, and configuration—that developers then build upon. When AI is used to scaffold a microservice, it is producing this initial structure automatically, which is a common use case for AI coding assistants and generators. This is different from refactoring (removing redundant logic), quality assurance (testing final code), or DevOps automation (deployment scripts).
Question 2 · Prompt Engineering Open

A practitioner is tackling a complex architectural problem by dividing it into four prompts that run in sequence, where the output of each prompt becomes the input for the next prompt in the chain. Which prompt engineering technique does this describe?

Answer: C Prompt chaining is the technique of decomposing a complex task into a sequence of smaller, linked prompts, where the output generated by one prompt is used as the input to the next prompt in the sequence. This allows a large or multi-step problem to be solved incrementally, with each prompt handling a discrete subtask and passing its result forward. This differs from few-shot prompting (providing example input/output pairs within a single prompt), meta-prompting (using prompts to generate or optimize other prompts), and chain-of-thought prompting (eliciting step-by-step reasoning within a single prompt/response rather than across multiple sequential prompts).
Question 3 · Data Research and Analysis Open

A practitioner is using AI to analyze customer support tickets and usage data in order to compare complaint patterns across different customer segments. Following the 4-step EDA (Exploratory Data Analysis) methodology, what should be done immediately after producing a high-level summary of the feedback data?

Answer: D After establishing a high-level data summary during the orient step, feedback patterns should be visualized to expose distributions, trends, outliers, and differences among customer segments. Correlation and hypothesis development follow this exploratory visualization.