Stack Overflow today made generally available an artificial intelligence (AI) tool that makes it possible to use natural language to search its repositories for code.

Company CTO and chief product officer Jody Bailey said AI Assist provides developers with a conversational search and discovery tool that enables them to more easily find relevant online content stored on the Stack Overflow and Stack Exchange sites.

After a summary is generated based on Stack Overflow’s ranking system, an AI agent embedded within AI Assist will also re-rank any answer provided for correctness and comprehensiveness to ensure verified code is surfaced with clear attributions, added Bailey.

Finally, if the search itself fails to yield any relevant community content, the AI agent is then instructed to answer the question using examples of code it finds outside of the Stack Overflow sites by invoking third-party large language models (LLMs). That hybrid approach, while prioritizing Stack Overflow content, ensures that a relevant answer to a question is always provided, said Bailey.

Many developers are, of course, relying on AI tools from OpenAI, Microsoft, Google and Anthropic to discover code they can reuse. The AI Assist tool created by Stack Overflow provides an alternative that generates more reliable content, including its original source, that makes use of the Stack Overflow ranking system to minimize any chance a hallucination will surface a snippet of code that actually doesn’t work or is deeply flawed, noted Bailey.

Going forward, Stack Overflow plans to integrate AI Assist via a Model Context Protocol (MCP) server with other Stack Overflow features and offerings, including its chat function and coding challenges, before adding extensions to integrated development environments (IDEs) and Discord servers. Longer term, AI Assist will also enable Stack Overflow to add additional education programs for developers, noted Bailey.

Since making AI Assist available in beta, Stack Overflow claims more than a quarter million IT professionals have already employed it.

It’s not clear how many developers are relying on AI to find and generate code, but as usage increases DevOps teams are starting to encounter more code that for one reason or another needs to be rejected. In some cases, it’s because a known vulnerability is discovered but just as often DevOps engineers are realizing that the overly verbose code generated by AI tools increases the amount of infrastructure required to run it. Over time, the code created by the AI tool will eventually significantly increase the total cost of IT.

The AI Assist tool developed by Stack Overflow helps minimize those issues by providing developers with examples of code that have already been vetted by their peers, noted Bailey.

There is little doubt that AI tools are making application developers more productive than ever. However, without the appropriate safeguards it’s also apparent that AI coding tools quickly become too much of a good thing. The challenge and the opportunity now is to find ways to apply much-needed guardrails to AI coding as early as possible in the software development lifecycle (SDLC).