Rizel Scarlett

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.

"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 my team launched Goose in early January 2025, we knew we had something special. We built a free, open source AI agent that leverages the Model Context Protocol. It was inventive in its approach, offering developers a local solution with the flexibility to bring their LLM of choice.

The LLM Cost Problem​

After using the product internally for a few months, my teammates were eager to share Goose with the developer community through workshops and hackathons. We wanted to provide hands-on experiences where people could actually build with Goose, because that's how developers fall in love with a product.

But we hit a thorny challenge: while Goose is free, high-performing LLMs are not.

I built Postman meets Google Docs for 10-year-olds.

Cue record scratch.

Cue freeze frame.

Cue movie cliché.

You're probably wondering how I got here.

Developers deserve to have fun. There was a time when the internet felt magical. I remember going to the library just to create a character on The Doll Palace. At home, I'd spend hours changing fonts with WordArt. But as I grew up, the industry did too. We've shifted away from marquees and glittery cursors. Grown-up me started using ones and zeros to build reliable systems for insurance, banking, and healthcare companies. There's pride in that, but it's harder to justify doing something just because it's fun.

That's why I tapped into my inner child and used Goose to build a UI that reacts to users' emotions.

Localhost Ports Hoarding​

I'm perpetually drowning in open tabs. Yes, I do need Bluesky, ChatGPT, Claude, Goose, Cursor, Discord, Slack, Netflix, and Google Docs all open at the same time. I've learned that tab management isn't my only vice.

"Hi, my name is Rizel, and I'm a localhost ports hoarder. 👋🏿"

Ratatouille isn't just a heartwarming (and slightly unhygienic) film about a rat chef. It's also analogous to a popular tech trend: AI agents and the Model Context Protocol (MCP).

"Stop using AI," reads yet another viral post. I get it. It's frustrating to review a colleague's auto-generated work, filled with AI's classic giveaways like generic code comments and phrases like "In today's fast-paced world..."

Still, AI plays a pivotal role in my career. I don't rely on AI to do my work, but I use it to help me brainstorm and work more effciently. The introduction of Model Context Protocol (MCP) has made this even easier. MCP is an open standard that gives AI tools the context they need to be useful in the real world. It enables AI agents to interact with APIs, apps, and systems in a structured way. I use Codename goose, an open source AI agent built on MCP.

Here are 11 real ways I use AI Agents without sacrificing authenticity, creativity, or quality:

On Feb 2, 2025, Andrej Karpathy coined the phrase "vibe coding". Vibe coding represents a new approach to coding where developers ask an AI agent to build something, and they go with the flow.

The Model Context Protocol (MCP) makes this practice possible. Before MCP, developers copied and pasted context between applications. This workflow fell short of the promised AI agent automation that everyone claimed. Today, AI agents can work autonomously using MCP and integrate with any application, from GitHub to Cloudflare, YouTube, and Figma.

This shift democratizes coding. For example, it's empowered:

• Web developers to create video games with Unity
• Designers and product managers to prototype full-stack applications
• Business owners to transform their visions into functional products

It's a freeing experience. But too often, we're Icarus with the keyboard, vibe coding too close to the sun.

Question: What happens when you bring 70+ AI enthusiasts, open source contributors, and curious learners together in one room?

Answer: You get an electric night filled with great conversations, hands-on hacking, and mind-blowing insights into agentic systems.

This week, we hosted our very first Goose Meetup in Boston at the Cambridge Innovation Center. The turnout and energy exceeded all expectations! From first-time Goose users to seasoned AI engineers, attendees gathered to explore how Goose and the Model Context Protocol (MCP) are shaping the future of AI automation.