AI delivery gut check:

% to prod in 24h?
Review time?
Failure rate?

That’s the bottleneck. See how you compare: https://circle.ci/3NASptw

Most engineering roadmaps are built around certainty, but that model is beginning to break down.

When the way people interact with software is changing this quickly, exploration stops being a side project and starts becoming the day-to-day.

Tune in: https://circle.ci/4sAZadU

How to Grow your Software Factory Rules, modules, and the path to AI leverage

More code doesn't always mean better outcomes.

The teams winning have built systems AI can rely on, not just better prompts.

Luca Rossi breaks down what AI maturity actually looks like. 👇

Not on Chunk's watch

Long test suites slow everything down. But by running only the tests that matter, we cut one project’s suite from 30 minutes to about a minute and a half, which makes feedback way faster!

Learn how faster feedback loops drive more stable delivery: https://circle.ci/3YiQgEx

Your best engineers want to solve hard problems, not spend their day reviewing code they didn't write.

The top teams in our 2026 research figured out how to make that possible: https://circle.ci/4aygjgQ

Your CI pipeline is the new bottleneck, but don’t fret! Chunk can fix it.

Our autonomous CI/CD agent reads your build history → rewrites your config → opens a PR. You just merge it.

Here’s the full demo: https://circle.ci/4dhM3df

Our State of Software Delivery Report sponsor, @thoughtworks.com, shared their take on the report: AI increases code throughput, but delivery systems haven’t caught up.

More code ≠ more shipped software.

Read their perspective: https://circle.ci/4sm03Y0

Chunk headed to Toronto for AgentCon this weekend and had a great time! 🇨🇦

We loved chatting with so many developers and catching a session from our team on agentic delivery and what happens when CI stays in the loop while AI agents build.

Where should Chunk go next? ✈️

Customer story | CircleCI | Claude See how CircleCI used the Claude Agent SDK to build Chunk, an AI agent that autonomously fixes build failures and validates code changes before humans review.

90% of our engineering team uses Claude Code daily.

But the more meaningful number: a team of 8 built Chunk, our fully autonomous agent in just a few weeks. Closed loop, auto-triggered, validated PRs.

@anthropic.com published the full story:

MCP vs. CLI for AI-native development - CircleCI The MCP vs. CLI debate misses the point. The right answer depends on where you are in the development loop. Here's a practical framework for deciding.

CLI vs. MCP for AI-assisted dev isn't an either/or.

CLI = inner loop. Fast iteration, zero overhead, model already knows the tools.

MCP = outer loop. Auth, structured JSON, cross-system coordination.

Full breakdown 👇

Junior devs are generating code at senior speed. Senior devs are buried in PRs.

The bottleneck didn't disappear, it just moved to your review queue.

Read the 2026 State of Software Delivery Report: https://circle.ci/4aygjgQ

AI ships working software, but it doesn't always ship software people love.

That gap is the moat now.

More from Loïc and Rob here: https://circle.ci/4sAZadU

The goal isn’t just fixing incidents faster, it’s learning from them.

While AI can surface insights, improvement only happens when you carry that learning into future code.

Here's the full conversation: https://circle.ci/491BGr6

Want a peek at what we're shipping next? 👀

Join us at our live product roadmap session on March 5 to discover what we're shipping now, what's coming next, and how engineers are using CircleCI to move quickly (without breaking things).

Register: https://circle.ci/4u7a8cr

This is what closing the AI delivery gap looks like.

Chunk detects flaky tests, fixes them, validates the change, and opens a PR automatically. No manual cleanup required!

▶️ Demo: https://circle.ci/4oEksER

📣 PSA: Shipping faster is not the same as delivering value.

If your sales, marketing, or legal teams aren't ready, AI just shifts the bottleneck instead of removing it.

Watch the full convo to learn how teams are improving flow end to end: https://circle.ci/491BGr6

AI writes code at machine speed. Your validation doesn't.

That gap is the AI Delivery Bottleneck, and it may be costing you!

Our 2026 State of Software Delivery Report fully breaks it down: https://circle.ci/4aygjgQ

AI boosted feature branch activity across the board last year. 📈
But for the typical team, main branch throughput actually went down 7%. 📉

We dug into 28M workflows to understand why in the latest Confident Commit: https://circle.ci/49HdjQ7

The Era of the Software Factory 🏭 A reflection based on the latest State of Software Delivery report

Rob sat down with Luca Rossi to chat about one big takeaway from this year’s State of Software Delivery report: AI is increasing change volume, but only teams with strong delivery systems are converting that into shipped software.

The 2026 State of Software Delivery is here, and this year’s data makes one thing clear: AI has accelerated how fast we write code, but most delivery systems have not kept pace.

Read the report: https://circle.ci/4aygjgQ

Even when AI speeds up coding, delivery becomes the limiting factor. Small improvements in delivery time can reduce queueing and keep work moving.

Watch the full AI Is Breaking the SDLC session to see it in action: https://circle.ci/3YiQgEx

The biggest costs in CI rarely show up on a budget line. They show up as lost time, delayed delivery, and senior engineers being pulled into work that could have been handled earlier.

When you model that impact, the economics change quickly.

Find the full example: https://circle.ci/3L643vd

Most teams don’t notice this day to day, as it usually shows up as waiting on feedback, context switching, and stalled momentum.

But over time, it can turn into a real cost for engineering teams.

Full breakdown: https://circle.ci/4cdyXwT

When a test passes and fails on the same SHA, that’s genuine flakiness. Here’s how teams can surface it quickly and cut down recovery time.

Full demo: https://circle.ci/4oEksER

This isn’t about working faster. It’s about autonomous validation removing the friction that pulls engineers away from meaningful work.

When delivery systems adapt to each change, that time adds up quickly.

Learn more: https://circle.ci/4ag5H5U

When you look at CI throughput growth by team performance, a clear gap shows up.

🏆 Top 5% of teams increased throughput by 97%
🚀 Top 10% grew by 47%
⚖️ Median team grew 4%

AI is increasing development activity, but the gains aren’t evenly spread. We dig into why here: https://circle.ci/49HdjQ7

Ever wonder where the time goes in CI? ⏳

Rob walks us through how small delays in feedback, failures, and reviews add up to real cost for engineering teams.

Average daily CI throughput is up 59% YOY across all projects, the largest jump we’ve ever seen. 😮

What’s less obvious is how uneven those gains are and why more activity doesn’t always translate into feeling faster or more effective.

Read on: https://circle.ci/49HdjQ7

Teams expected AI-assisted coding to lighten the load, but what if it's actually making software delivery more unstable?

▶️ Watch the full session of AI is Breaking the SDLC here: https://circle.ci/3YiQgEx