Products · 6 min · Updated 2026-05-28

Get started with Lexopedia AI

Lexopedia AI is the DeepBrainz production surface for autonomous knowledge work. Start with a real question from your current work, let specialized agents research and reason with the depth you need, review the evidence, and keep useful outputs in a reusable project or thread.

1. Start with one real question

The best first session is not a demo prompt. Bring one real research, product, engineering, or decision question from your current work so you can judge the output against reality.

A useful first question has stakes, constraints, and a next action. For example: choose between two technical options, explain a confusing stack trace, compare vendors for an India-first budget, turn notes into a memo, or identify what evidence is missing before a decision.

  • Good first jobs: compare options, explain a technical concept, synthesize sources, review tradeoffs, or structure a decision memo.
  • Weak first jobs: vague curiosity prompts with no real use.

2. Give enough detail to make the answer useful

Lexopedia works better when the request names the goal, the audience, the constraints, and the output format. You do not need a giant prompt. You need enough detail that the system is solving the right problem.

A strong request usually has this shape: here is the objective, here is what I already know, here are the constraints, here is the risk or decision, and here is the output I need back. That gives knowledge agents clearer boundaries than a long instruction full of vague preferences.

  • Say what you are deciding or producing.
  • Name constraints such as geography, budget, stack, time range, or source quality.
  • Ask for the output shape you need: comparison, memo, plan, checklist, code direction, or summary.

3. Use depth intentionally

Start lighter when you need orientation. Go deeper when the answer will be reused, shared, or relied on for a real decision. If the result matters, ask for sources, assumptions, risks, and what still needs verification.

4. Treat outputs as working material

Lexopedia is most useful when agent work becomes a reusable asset. Save useful outputs into the right project or working thread instead of leaving them as disposable chat history.

  • Keep source trails visible.
  • Name projects by outcome, not vague topic names.
  • Separate exploration from final deliverable threads.

5. Ask for help when access or workflow blocks you

Use the Help Center or in-app chat if you cannot access the workspace, a feature is not behaving as expected, or you are unsure whether Lexopedia or another DeepBrainz product is the better fit.