Tech Stack
A tech stack refers to the combination of programming languages, frameworks, tools, and platforms that developers use to build applications. In the context of AI agents, tech stacks have become increasingly important as developers integrate machine learning models, APIs, and specialized libraries into their workflows. Understanding which tools and technologies are most commonly adopted provides insight into industry trends and best practices.
Survey Methodology
The Pragmatic Engineer 2025 survey and the Artificial Analysis survey both assessed developer adoption of AI tools and technologies, though they differed in scope and focus. These surveys capture snapshots of the tools developers actively use when building AI-powered systems, revealing patterns in language preferences, framework selection, and platform choices across different segments of the developer community.
Key Findings
Both surveys identified Python as the dominant programming language for AI development, reflecting its established ecosystem of machine learning libraries and frameworks. The surveys also tracked adoption of various AI platforms, APIs, and development tools, showing which solutions have gained traction among practitioners building AI agents and related applications. Differences between the two surveys often reflected their distinct respondent bases—whether focused on enterprise adoption, startup environments, or the broader developer community.
Practical Implications
The data from these surveys helps developers make informed decisions about which technologies to learn and invest in for AI projects. By examining adoption patterns, teams can better understand ecosystem maturity, community support availability, and integration possibilities when selecting components for their own AI agent tech stacks.
Source Notes
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