All built with Command. Vibe code prod-ready agents with Command. Try it now:.

Math solver agent. Solves math problems in real-time. Paste a problem or upload a photo — get a step-by-step solution.

Text extraction agent. OCR-powered agent that pulls text from images. Digitize receipts, notes, or any document instantly.

Smart travel agent. Get a full travel itinerary with budget planning. Just prompt it with a rough destination and budget and done!

HackerNews intel agent. Gather insights and trends from HackerNews effortlessly. From API fetches → analysis → intel generation.

AI resume generator agent. Create a complete resume by simply entering your name. It researches you online and builds your resume.

5 AI agents to vibe code this weekend (with 👇.

We built Langbase to help teams build real AI products — fast. See how we can help:.

Fundamentals are the same. The fundamentals of great products haven't changed:.• Enhancing user experience.• Building something people want.• Offering robust support. There are no shortcuts; don’t forget the fundamentals.

Avoid short-lived problems. Don't build for gaps that base models will patch in months. You might need to predict what future models will look like. Base your product roadmap around them.

Context is king. Stop treating LLMs like interns waiting for instructions. Provide them with curated context to guide their thinking. The smarter the context, the smarter the output.

Go niche. Go deep. Everyone's building general-purpose AI assistants. Not many specialize in niche areas. Own a narrow problem. Solve it better than anyone.

Building AI products is not the same as building a traditional product. Models move really fast. One day, you have a product — the next, it's just a feature in ChatGPT. That's why we need a new playbook 👇.

What actually matters when building useful AI products 🧵.

You can build any AI agent with AI primitives. Command uses AI primitives to vibe code AI agents. Try it now:.

With primitives, you can build:. • Augmented LLMs — agents using memory, threads, and tools.• Prompt chaining — chained agents working sequentially.• Router-based agents — delegate tasks to specialized agents. Among other agent architectures. Built with primitives.

Primitives aren't just code. They come with infrastructure baked in. Example: Memory doesn't just define storage, it is a scalable vector store. You can throw terabytes of data into it, and it just works.

What are AI primitives?. They're low-level, plug-and-play building blocks like:.• Memory - persistent vector store.• Agent - runtime LLM agent.• Workflow - orchestrate all operations.• Tools - Web search or crawler. Primitives are composable like React components.

Frameworks are great — until they aren't. In a fast-moving space like AI, frameworks quickly become bottlenecks. Abstractions that used to help now get in the way. You don't need more "magic". You need composable primitives.

Why the best AI agents aren't built on frameworks but on primitives. 🧵.