Question 1

What is the main difference between AI-Assisted Dev and low-code platforms?

Accepted Answer

Low-code platforms provide visual development tools with pre-built components that reduce manual coding, while AI-Assisted Dev uses machine learning to generate contextually appropriate code from natural language descriptions. Research shows AI-assisted development can reduce lead time by 55% while maintaining code quality, offering more flexibility than traditional low-code approaches

Question 2

How does AI-Assisted Dev impact application security?

Accepted Answer

AIAD platforms typically include automated security scanning and best practice enforcement. However, studies reveal that 40-73% of AI-generated code contains vulnerabilities, requiring organizations to implement additional review processes with human oversight to identify and remediate security issues.

Question 3

Can AI-Assisted Dev replace professional developers entirely?

Accepted Answer

No, AI-Assisted Dev augments rather than replaces developers. While AI handles routine coding tasks and provides intelligent suggestions, human expertise remains essential for architectural decisions, complex problem-solving, quality assurance, and understanding nuanced business requirements. Microsoft research confirms that successful implementations require proper developer training and workflow integration.

Question 4

What skills do developers need to work effectively with AI-Assisted Dev?

Accepted Answer

Developers should understand fundamental programming concepts, possess strong problem-solving abilities, develop critical evaluation skills for assessing AI suggestions, and maintain communication capabilities for translating business requirements into effective AI prompts. Industry data shows that developers with AI skills command a 43% wage premium, up from 25% in 2023.

Question 5

Is AI-Assisted Dev suitable for small businesses and startups?

Accepted Answer

Absolutely. AI-Assisted Dev particularly benefits smaller organizations with limited technical resources. Research shows that 89% of small businesses use AI tools for everyday tasks. AIAD enables small teams to build sophisticated applications quickly, compete effectively with larger enterprises, and adapt rapidly to market feedback without maintaining large development departments.

the software development lifecycle

The Transition: From Low-Code, to No-Code, Now AI-Assisted Dev

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