Over the years, Block's iOS engineers have felt the pain of technical debt accumulating. Feature flags are a specific example of this. Even when successfully rolled out, they tend to linger in the codebase, each one a small weight slowing down development.

In the early stages of 2025, with a renewed focus on developer acceleration, the Foundation iOS team decided to organize 'Feature Flag Removal Month' - an opportunity for teams in the large iOS monorepo to come together and delete possibly hundreds of thousands of lines of dead code.

With the serendipitous launch of Goose recipes around the same time, the team wondered could a dedicated recipe aid this effort? Gemma Barlow, a newer iOS engineer on the team, wanted to find out.

You shouldn’t need a credit card to vibe code with Goose. While Goose is completely free to use, the reality is that most performant LLMs aren't. You want to experience Goose in action without breaking the bank or jumping through hoops. We've been thinking about how to make that first step easier for newcomers to Goose.

That's why we're thrilled about our newest provider integration: Tetrate's Agent Router Service. From August 27th through October 2nd, new Goose users can get $10 in credits to use Goose with any model on the Tetrate platform.

Remember when people shared recipes by passing handwritten cards between neighbors? You trusted Grandma's apple pie recipe because you knew Grandma. But what happens when strangers start sharing recipes online? You need someone to taste-test them first.

That's exactly the challenge we face with Goose recipes. We're building a community cookbook where you can try Goose recipes from other users with confidence that they're safe. But we needed a way to make sure every recipe was safe to run.

The days of endless text walls in AI agent conversations are numbered. What if instead of reading through paragraphs of product descriptions, you could browse a beautiful, interactive catalog? What if booking a flight seat could be as simple as clicking on your preferred spot on a visual seat map? This isn't science fiction. It's happening right now with MCP-UI.

In a recent Wild Goose Case episode, we dove deep into MCP-UI with its creators Ido Salomon and Liad Yosef from Monday.com, alongside Block's own Andrew Harvard, to explore how this groundbreaking technology is reshaping the future of agentic interfaces.

Kim is fresh out of the academy and has spent only 18 months learning development. When I asked her how she felt about Goose she had mixed reactions. While she found it cool that it could do so much for her, she wasn’t actually sure of what it was doing for her half the time, and also why. When she asked Goose to fix a broken build, or chase a bug, It would complete the task and claim ‘Success!’. Which is great, however she felt she wasn’t actually learning as much as when she was in the academy. Add on that sometimes she didn’t even know what to ask Goose to do sometimes.

That afternoon I started to see if I could get Goose to be more than just a ‘magic box’ for my Junior Devs. What if Goose could instead act as a mentor and also teach as well as speeding up development?

Working with AI tools can feel like working with a flaky, chaotic, but overconfident coworker. You know, the kind who forgets tasks, lies unprovoked, starts new projects without telling you, then quits halfway through. It's enough to make you say: "Forget it. I'll do it myself." But before we write off AI entirely, it's worth understanding what's actually happening under the hood so we can avoid common pitfalls and make AI tools worth using.

I taught a vibe coding workshop at UC Berkeley and informed the students that we'd be spinning up 7 subagents. Someone quickly raised their hand and asked "what is a subagent?". At that moment, I realized we're just throwing out terms like agent, multi agent, and subagent, and not really taking the time to explain what these are. So, here goes... a 101 breaking down these various coordination patterns and when to use them.

A website to me is a corner of the internet where I can be who I am, share my work, and ultimately a place I can do whatever I want with. For it to be anything but my personality personified, especially as an ex-nerdy blog designer (in my middle school and high school days), felt so sad! Until suddenly, what started out as a harmless "404 Day" challenge quickly turned into making that website in basically no time.

"The best AI agent workflows go beyond demos. They deliver real productivity."

The DevRel team at Block is a huge fan of PulseMCP. Their weekly newsletter has been an amazing way for us to discover trending MCP servers and stay in the loop with any changes within the ecosystem. When the PulseMCP creators, Mike and Tadas, shared their goals of using Goose to help automate the boring parts of their newsletter workflow, we were excited to see what they'd build.

Their implementation showcased exactly why we built Goose's feature set the way we did, and they documented the entire journey to help others learn from their experience.

When building Model Context Protocol (MCP) servers, most development focuses on tool functionality, ensuring tools execute and return expected results. But just as critical is the quality of tool metadata: descriptions, tooltips, and input schemas. These elements form the "interface language" between tools and AI agents like Goose.

Yet metadata often goes untested. This can break tool discovery and silently degrade agent behavior. In this post, we’ll show how to automate metadata validation using composable Goose recipes, turning manual QA into modular, repeatable workflows that:

• Validate tool discoverability and parameter accuracy
• Detect regressions early
• Safely reduce token usage

All while maintaining the quality that AI agents depend on.