The landing page is written for humans. This page adapts to your audience mode.
Simple explanations first, technical terms second.
One lead, many specialists
technical name: "Orchestrator-Worker Architecture"One lead AI reads your request, then picks the best mini-team to handle each part.
- Think of a movie director who does not act in the scene, they make sure the right people do the right job.
- Example: Ask for a market comparison and the lead sends one agent to pricing, one to features, and one to user reviews.
Read more: Building Effective AI Agents (Anthropic)
They all work at once
technical name: "Parallel Sub-Agent Execution"Your helpers do not wait in line. They work at the same time, so you get results sooner.
- It is less one cashier, more a whole team at checkout.
- Example: While one agent finds prices, another checks reviews, and another scans feature lists.
Read more: Promise.all (MDN) · Promise.allSettled (MDN)
Other AI can use it too
technical name: "API-First Design"This is not only a website. Other tools can talk to lmkgpt directly and ask for help.
- Think of it like adding a smart teammate to your other apps.
- Example: Your app sends one request and gets back a team-based answer.
Read more: OpenAPI specification · RFC 9110 (HTTP)
Watch them work
technical name: "Real-Time Streaming via SSE"You can see progress live, instead of waiting for one big answer at the end.
- Like tracking a delivery in real time, but for thinking.
- Example: Cards update while each agent works, then the final answer appears when all are done.
Read more: Using server-sent events (MDN) · Server-sent events (WHATWG)
See the full picture
technical name: "Full Prompt Transparency"You can inspect what each helper was asked and what they found.
- No mystery box, you can look under the hood whenever you want.
- Example: Open an agent card to view its mission and response, not just the final headline.
Read more: Building Effective AI Agents (Anthropic)
Powered by the best AI
technical name: "Multi-Provider Resilience (Anthropic + OpenAI)"If one AI service has trouble, another can step in so your work does not stall.
- Like having a backup singer who already knows the song.
- Example: A failed model call can retry on another provider and continue the mission.
Read more: Anthropic API · OpenAI API
Want your own AI research team?
Developers can call the same orchestration engine through the API.
POST /api/v1/orchestrate