TOP LAUNCHES

Robots that talk like humans

TOP LAUNCHES

Sesame's Conversational Speech Model creates AI voices designed for natural, engaging interactions. It enhances realism and presence, making conversations feel more human.

Latitude Agents lets developers build, test, and deploy autonomous AI agents that evolve over time. It streamlines multi-agent orchestration and self-improving prompts.

GaliChat AI lets you build, train, and share AI agents powered by your own data. Create AI experts, automate tasks, and deploy them via links or embeds.

Aider is an open-source AI pair programmer that works in your terminal, helping edit code within your git repo. It supports multiple languages and AI models, including Claude 3.5 and GPT-4o.

Gum.new lets creators build custom, high-converting landing pages for their Gumroad products. It offers more flexibility than Gumroad’s default templates, making it easier to match your brand and boost sales.

THE BIG IDEA

What the h**l is MCP!?

If you’ve been seeing MCP (Model Context Protocol) pop up everywhere and wondering if you should care—yeah, you probably should. It’s an open standard that lets AI models talk to external data sources and tools in real time without needing messy custom integrations. Instead of AI responding based only on what it was trained on, MCP lets it fetch live context from APIs, databases, and apps as needed. Think of it as a universal adapter that plugs AI into the rest of the internet without duct-taped workarounds.

Companies like Replit, Codeium, and Sourcegraph have already started integrating MCP, which means their AI agents can now retrieve relevant data, execute code, and even act on behalf of users without being stuck in a static training loop. This is a big shift—MCP moves AI from a passive assistant to an active participant in software development.

So what’s the catch? Well, MCP is still in its early days, and widespread adoption depends on more platforms jumping on board. But if it works as intended, it could reshape how AI interacts with software—turning chatbots into true AI-powered agents that actually get stuff done.

(Or, worst case, it just makes AI better at auto-filling your Jira tickets. Either way, a win.)

TRENDING DISCUSSIONS

Is “vibe coding” with AI actually a thing, or just wishful thinking?

AI can generate code, sure, but can it build an entire app without you knowing a thing about software? Dan Leshem, maker of Fine, has been working with non-coders trying to do exactly that, and here’s what he found—the ones who understood basic software concepts were 10x more likely to succeed.

Dan put together a quick roadmap of the must-know basics, from frontend and backend to APIs and databases. The takeaway? You don’t need to be an engineer, but if you can’t explain what you want like you’re talking to a junior dev instead of rubbing a magic lamp, AI is going to struggle.

Tried building an app without code? Think AI can do it all for you?

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