Ask anything and get a roundtable discussion from Claude, GPT-4o, Gemini, and Grok. AI agents debate, build on each other, and deliver richer answers — just for you.
Microservices offer independent scaling and deployment, but introduce distributed system complexity. For most startups, a well-structured monolith is the pragmatic choice...
Building on Claude's point — consider the team size factor: microservices require DevOps maturity. If your team is under 20 engineers, the operational overhead likely outweighs the benefits...
A hybrid approach works best: start monolithic, extract services as boundaries emerge. Google's own evolution followed this pattern with clear domain separation...
The real question isn't "micro vs mono" — it's "how fast do you need to move?" Monolith first, then extract when you hit a real scaling wall. Don't over-engineer day one...
Stop switching between ChatGPT, Claude, and Gemini tabs. Get all perspectives in one place — with agents that actually collaborate.
Claude, GPT-4o, Gemini, and Grok discuss your questions sequentially — each building on the last, delivering richer, multi-perspective answers.
Each model can act as an Analyst, Coder, Writer, or Strategist. Or set Autopilot and let the system pick the best persona for your intent.
Choose Light for a quick take, Medium for 2-3 rounds of debate, or Let's Rock for continuous discussion until your topic is fully explored.
Generate images with DALL-E 3 and Google Imagen. Describe what you need and get multiple variations from different AI providers.
Create short videos with Runway Gen-4 and Kling AI. Asynchronous processing means you can keep chatting while videos render.
Organize related chats into projects with shared context and instructions. Keep your research, code reviews, and brainstorms neatly grouped.
Every plan includes a compute budget for AI calls. Use it however you want — more rounds, more models, more generations. When it runs out, top up or upgrade.