How LLM Peers works, end to end

Start with one difficult question

LLM Peers works best when you bring a real decision: a choice with trade-offs, constraints, and consequences. Vague curiosity still works, but the product shines when “good enough chat” is not good enough for the commitment you are about to make.

The deliberation path

1. 01

   Ask the question

   Submit the decision you need to make—strategy, vendor choice, roadmap, investment, career move, or another consequential call. Sign in with Google to start with LLM Peers in your workspace.

2. 02

   Clarify with intake when needed

   On the first message, an optional intake step may ask focused clarifying questions (single choice, multi choice, or short text). Answers enrich the research brief. You can skip if context is already complete.

3. 03

   Gather web context

   When web research is enabled, the board collects a current briefing from public sources so models can reason with fresher external context alongside your question.

4. 04

   Run the AI council

   Multiple models produce independent answers—recommendations, risks, assumptions, and next steps—without seeing each other’s work. This is Stage 1 of deliberation.

5. 05

   Peer review and rank

   Answers are anonymized and ranked against shared evaluation criteria. Stage 2 surfaces comparative strength, agreement, and dissent without brand-driven preference.

6. 06

   Chairman synthesis

   A lead agent synthesizes rankings and evidence into one decision brief: recommendation, ranked options, assumptions, risks, and next action. Stage 3 is the artifact you take forward.

What happens behind the scenes

Progress is written stage by stage to your research conversation so the UI can update as each phase completes. You can inspect intake, web context, council answers, peer rankings, and the final synthesis rather than trusting a black-box reply.

That inspectability matters for SEO content and for real work: decision quality improves when people can see how a recommendation was produced, not only what the headline says.

After the run

• Read the decision brief and supporting stages in your workspace
• Export or share a public research link when others need the same case
• Return to conversation history for related follow-up decisions
• Challenge assumptions that would change the recommendation before you commit

Tips for stronger runs

• State the decision, not only the topic (“Should we X or Y under constraint Z?”)
• Include constraints early: budget, timeline, risk tolerance, non-negotiables
• Name what “good” looks like so ranking criteria can stay grounded
• Use intake when stakeholders disagree about goals
• Enable web research for time-sensitive market or vendor questions