What Developers Use and Search in 2026: Survey Data

If you ask "what are developers searching for these days", the honest answer is not a list of keywords. Search volume data from Google is not public in a form anyone can quote reliably, and most "top search" lists online are guesses. What can be checked is what developers say they use, how they look for answers, and what they actually push to GitHub. Two large reports landed in the last five weeks: the Stack Overflow Developer Survey 2026 (published 6 October) and GitHub's Octoverse 2026 (published 28 October). This article pulls out the numbers that matter for working developers and says what each one does and does not tell you. Where developers look for answers has changed This is the headline for anyone who writes or reads technical content. From the Stack Overflow 2026 survey, which had more than 30,000 respondents: 83% search online for answers, and 70% ask an AI agent. Many do both. 64% visit Stack Overflow less often for simple questions. 16% visit Stack Overflow more often, to check where an AI answer came from. 93% say source attribution is needed for them to trust AI output. What do developers do after an AI answer arrives? The survey asked (about 13,000 answers, multiple choices allowed): Next step after an AI response Share Run it locally 76.5% Compare against the codebase 63.9% Inspect tests and security implications 53.0% Read official documentation 38.0% Search Stack Overflow 12.2% Ask a coworker 6.9% Use as-is 9.6% Only about one in ten uses the answer without checking it. Verification, not generation, is where the search effort has moved. The trust question points the same way: 48.0% said they trust AI output when they can easily verify it, 12.3% do not trust it for most work tasks, and 6.6% trust it for many tasks including important decisions. The languages and databases in daily use The survey's technology page gives these shares of respondents: Language Share Database Share JavaScript 62.0% PostgreSQL 57.9% SQL 58.4% SQLite 42.1% HTML/CSS 58.2% MySQL 35.1% Python 58.0% Redis 28.3% Bash/Shell 51.3% Microsoft SQL Server 27.1% TypeScript 43.8% MariaDB 20.3% Java 27.6% MongoDB 19.0% C# 27.1% Elasticsearch 14.8% Three things stand out. SQL moved ahead of HTML/CSS, but by 0.2 percentage points, which is within the noise of a survey. PostgreSQL is used by well over half of respondents, far above MySQL. And Redis and MariaDB each sit in the top seven databases, so the "classic" stack of PHP or Python with MySQL, MariaDB and Redis is a long way from disappearing. Rust moved up to 12th place among languages, though the survey summary gives no percentage for it. What GitHub's own data adds Surveys record what people say. GitHub records what they push. Octoverse 2026 covers the year from 1 October 2025 to 30 September 2026: Volume: 17.9 billion pushes, 34.3 billion commits (public and private) and 1.3 billion merged pull requests. GitHub reports more than 225 million developers. Languages: TypeScript is first, Python second and JavaScript third, the same order as 2025, when TypeScript passed Python for the first time. Net monthly contributor gains over the year were 3.62 million for TypeScript, 3.23 million for Python and 1.82 million for JavaScript. Rust "doubled" over the past year, per GitHub. Agents: more than 40% of pull requests started with an agent's first draft in September 2026, up from 17% in March 2026. That is 110 million agent-started pull requests in a single month. Fastest-growing projects: the lists are dominated by AI tooling, with anthropics/claude-code, ggml-org/llama.cpp, vllm-project/vllm and openai/codex among those named. Note that the Octoverse language ranking counts contributors, which is a different measure from the survey's "used in the past year". That is why JavaScript leads the survey while TypeScript leads GitHub. GitHub also reports that, among repositories created in 2026, those with an agent configuration file logged eight times as many commits as those without. That is a correlation: projects that adopt agent tooling may simply be the more active ones. AI tools in practice Among the survey respondents who use AI coding assistants or agents (12,255 answered), the most used agents were: Tool Share Claude Code 65.5% GitHub Copilot 58.7% OpenAI Codex 29.5% Cursor 25.5% Google Antigravity 16.0% Gemini Code Assist 14.6% Of those who use AI tools, 73% use them daily, and 31% of the daily users spend four or more hours a day with them. The main uses are generating code in familiar areas (67%) and debugging (61%). Only 20% use AI for deploying, operating or troubleshooting production systems. Treat the tool ranking with care: the respondents chose to take a Stack Overflow survey and are not a random sample of developers, and the figures are shares of people who answered that question. What this means if you build or write for developers The following points are my reading of the numbers above, not extra data: Short factual questions are going to AI chat, and the checking is going to documentation. Pages that survive are those with something a chat answer cannot easily give: tested commands, real output, version-specific behaviour, and sources that can be cited. With 93% asking for attribution, citing the official docs is no longer optional. Verification skills are in demand. Three out of four developers run AI-generated code locally before trusting it. Tutorials on testing, reading stack traces, reviewing diffs and security checks fit that behaviour. SQL and PostgreSQL knowledge keeps its value. Both are at or near the top of the survey, and AI tools produce queries that still need a person who can read an execution plan. TypeScript is the default for new work on GitHub, with Python close behind. GitHub's own 2025 report argued that type checking helps catch errors in AI-generated code. That is their explanation, not a settled fact. Old stacks still matter. MySQL, MariaDB, Redis and Bash are all in the survey's top ten for their category. (The survey figures I read do not break out PHP, so I make no claim about it.) Maintenance, upgrade and troubleshooting topics for them have a steady audience, but I have no search volume data to put numbers on that. What these numbers do not tell you They are not search volumes. A technology that few people "use" can still draw many searches because it is hard to configure. Survey samples are self-selected, and the survey pages do not always say which population a chart covers. Where they do not, I say so above. Octoverse counts activity on GitHub, including private repositories, so it leans toward teams that host code there. For actual search demand on a topic, use Google Search Console for your own site and a keyword tool you trust. I did not use one here. Frequently asked questions What is the most popular programming language in 2026? It depends on the measure. JavaScript leads the Stack Overflow survey at 62.0% of respondents, and TypeScript leads GitHub by monthly contributors, ahead of Python and JavaScript. Is Stack Overflow still relevant? The survey says 64% visit it less often for simple questions, while 16% visit more to check AI-provided sources. It is used less for quick answers and more as a reference to verify them. What database do developers use most? PostgreSQL, at 57.9% of respondents in the survey, followed by SQLite (42.1%) and MySQL (35.1%). Are AI agents replacing developers? The data shows something narrower: agents now open a large share of pull requests (over 40% in September 2026), and developers are still the ones reviewing, merging and verifying. Nothing in these reports measures replacement. Originally published on DEV Talk.