JetBrains TeamCity

Introducing TeamCity CLI 🎉 It includes over 60 commands. Use it to investigate a failed build, find the root cause of a problem, or fix and re-trigger. Read more about how TeamCity CLI can help: jb.gg/n7v5pg

AI is changing how teams build, test, and ship software; CI/CD needs to evolve, too. Join our upcoming livestream for a deep dive into TeamCity 2026.1 🚀 We’ll cover: 🔵 The new TeamCity CLI with Agent Skills 🔵 MCP integration for AI agents 🔵 UI updates for TeamCity Pipelines 📆 May 12 at 6:00 PM CEST Register now 👇 jb.gg/6u3izo

Ernst invites you to join us for our upcoming livestream: “Introducing TeamCity 2026.1: AI, Pipelines, and Enterprise CI/CD.” We'll cover: 🔵 The TeamCity CLI – with Agent Skills 🔵 MCP for AI Agents 🔵 UI updates – TeamCity Pipelines Register now: 📆 May 12 at 6:00 pm CEST 🔗 jb.gg/6u3izo

TeamCity Product Manager Ernst Haagsman shares his key takeaways from Google Next 👇 • AI skepticism among developers is gone • Developer workflows are rapidly shifting toward AI-first tools • CI/CD conversations are changing, with teams actively reconsidering legacy setups like Jenkins • Speed of execution and delivering the right message at the right moment matter more than ever A candid look at how AI is reshaping developer tooling and what it means for the future of CI/CD 🚀

Developers now use AI for nearly everything, except the part that actually ships code. As AI-generated code increases, delivery pipelines become more important, not less. Read more about AI trends in DevOps 👉 jb.gg/ai-devops

Do you use AI agents in your CI/CD workflows? Now you can! We just introduced the TeamCity CLI that includes agent skills for popular AI coding agents like Claude Code, Codex, and @jetbrains Junie. Join us for a livestream where we'll show how the CLI works and what you can do with it. Register now: 📆 May 12 at 18:00 CEST 🔗 jb.gg/6u3izo

TeamCity 2026.1 introduces many great improvements, including support for both the Kotlin DSL and YAML in pipelines. Join us for the livestream to learn more. Register here: 📆 May 12 at 6:00 pm CEST 🔗 jb.gg/6u3izo

Join us for our upcoming livestream: “Introducing TeamCity 2026.1: AI, Pipelines, and Enterprise CI/CD”. We'll cover plenty, including: 🔵 The TeamCity CLI – with Agent Skills 🔵 MCP for AI Agents 🔵 UI updates – TeamCity Pipelines Register now: 📆 May 12 at 6:00 pm CEST 🔗 jb.gg/6u3izo

Today! 🥳 🍿 Join us and 400+ other folks for a YouTube livestream "Evaluating AI Coding Agents with TeamCity and SWE-bench", hosted by @DataTalksClub. Ernst Haagsman from @jetbrains TeamCity will walk through building a reproducible evaluation pipeline using SWE-bench and TeamCity. You'll see: 🟢 How to run agents on real open-source issues 🟢 How to validate fixes with automated tests in Docker 🟢 How to track performance across agent versions 🟢 How to compare cost and success metrics Sign up here: luma.com/f6zc5lr6

7/7 Chapter 7: The Trust Layer The future of AI in DevOps is not “let the model ship.” It is reliable validation, policy checks, access controls, audit trails, and human approval where it matters. CI/CD is becoming the trust layer. Read the full article 👇 blog.jetbrains.com/teamcity/2026/…

6/7 Chapter 6: Agents Raise The Stakes As AI moves from copilots to agents, it can propose PRs, generate changes, and respond to pipeline feedback. That makes CI/CD more critical, not less. The more AI creates, the more pipelines must constrain and approve. ↓

5/7 Chapter 5: Where AI Actually Works The strongest CI/CD use cases are not about replacing decisions. They are about improving signals: Failure diagnosis. Security fix suggestions. Test optimization. AI helps most when it makes validation faster, not weaker. ↓

4/7 Chapter 4: The Adoption Gap 73% of organizations do not use AI in CI/CD pipelines. 60% cite unclear use cases or value. 36% cite lack of trust. 33% cite data privacy concerns. Teams are not asking “can AI do it?” They’re asking: “can we trust it?” ↓

3/7 Chapter 3: CI/CD Has Different Rules A pipeline is not just automation. It is an evidence system. Builds prove code compiles. Tests validate behavior. Logs, scans, and deployment outcomes all point to one decision: Is this safe to release? ↓

2/7 Chapter 2: Why AI Took Off Upstream In the IDE, AI has a forgiving environment. Feedback is immediate. Errors are cheap. Suggestions can be tested, edited, or thrown away. That’s why AI fits coding, refactoring, debugging, docs, and knowledge discovery. ↓

1/7 Chapter 1: The Real AI Bottleneck AI has already moved into dev workflows. It writes, debugs, and explains unfamiliar systems. But one part still resists: CI/CD. Not because AI is useless there. Because this is where software stops being an experiment. 👇🧵

When AI agents write more code than humans ever did before, how do you ensure the code quality? On May 13, join us for a live demo "Take Control of Your AI Quality in CI", hosted by the @Qodana team. You'll learn how to automatically analyze AI-generated code, enforce quality standards, and reduce bottlenecks. Sign up 👉 jb.gg/6gpc3u

For now, it has a .NET project, and we're planning to add more projects soon. Stay tuned! 🔔

If you ever wanted to take a look at TeamCity but didn't want to connect your own repos, this is for you. We set up a demo instance of TeamCity that you can check out without connecting your own data: 👉 see.teamcity.com, login as guest.

When you see "build agent" in the context of CI/CD, what comes to your mind first?