'debate' 검색 결과

Master AI debate techniques with comprehensive counter-arguments against slop criticism, safety concerns, philosophical objections, and political rhetoric

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Conversation patterns and interaction protocols for multi-agent systems. Covers request/response, pub/sub, blackboard, delegation chains, debate, critique, consensus, fan-out/fan-in, supervisor-worker, and peer negotiation. Deep analysis of AutoGen conversation patterns, CrewAI delegation, LangGraph state passing, and FIPA-ACL performatives. Teaches how to design what agents say to each other and in what order. Activate on: "agent conversation", "agent protocol", "multi-agent debate", "agent delegation", "supervisor worker pattern", "agent voting", "consensus protocol", "fan-out fan-in", "agent negotiation", "blackboard pattern", "agent dialogue", "conversation topology", "agent handoff". NOT for: wire format or serialization (use agent-interchange-formats), orchestration infrastructure (use agentic-infrastructure-2026), single agent behavior (use agentic-patterns).

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Multi-agent structured debate with anti-groupthink mechanisms — Devil's Advocate, minority opinion protection, 2-round hard cap. Use when divergent perspectives matter more than consensus (architecture decisions, design tradeoffs, contested specifications).

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Multi-agent brainstorming: async opinion collision with expert personas. Mixed Codex/Claude Code engine. Use when multiple AI agents need to collaboratively discuss, debate, and converge on solutions through structured dialog. Triggers: brainstorm, multi-perspective discussion, opinion collision, expert debate, war room, collective intelligence, 头脑风暴, 多视角讨论, 集思广益.

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Debate multi-agente: 2-4 perspectivas (PM, Arquiteto, QA, Security) debatem decisao tecnica. Output: decisao + rationale + dissenting opinions → ADR. Inspirado no Party Mode do BMAD-METHOD.

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Multi-agent debate orchestration for Architecture Decision Records. Automatically triggers on ADR create/edit/delete. Coordinates architect, critic, independent-thinker, security, analyst, and high-level-advisor agents in structured debate rounds until consensus.

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Have agents with different roles challenge a proposed approach, exposing weak assumptions, missed interactions, and unnecessary complexity. Surviving findings go to a dedicated planning agent, which produces sequenced tasks with explicit success criteria.

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• Checking assumptions before committing to a plan
• Finding integration risks and overlooked edge cases
• Challenging unnecessary complexity in a design

Stress-test ideas, strategies, and plans by breaking them into individual claims for parallel expert agents to challenge. Receive the strongest supporting case, surviving counterarguments, and findings ranked by severity with suggested ways to address weaknesses.

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• Challenge assumptions in a business strategy
• Find weaknesses in a software architecture proposal
• Prepare strong objections to a pricing decision

Have Claude and GPT critique each other's answers, revise their positions, and work toward a combined response. Choose the number of rounds and see what changed, where they agree, and which disagreements remain.

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• Stress-testing a proposal from two perspectives
• Finding weaknesses in competing answers
• Combining agreement while preserving unresolved differences

Summarize popular Hacker News stories or find discussions on a specific topic. Get article highlights, scores, comment counts, and recurring discussion themes, including agreement, criticism, and related debates.

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• Reviewing the top ten Hacker News stories
• Summarizing an article and its discussion
• Finding Hacker News discussions on a topic

Simulate a decision meeting with three to five AI roles with different expertise and personalities. Follow their debate and receive a meeting record covering conclusions, supporting arguments, risks, and suggested next actions.

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• Compare technical architecture options
• Discuss pricing strategies for a new product
• Identify project risks and possible responses

Analyze public-company earnings after results are released, combining reported figures, guidance, estimates, and call evidence. Produces source-backed reports that examine recurring profitability, investment implications, key business drivers, and upcoming events to monitor.

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• Prepare a detailed report after an earnings release
• Check recurring profitability behind headline EPS
• Organize earnings-call quotes and investment debates

Use a panel of three to five agents to decide between options or assess a plan. Independent initial opinions and anonymous deliberation lead to one verdict with confidence, preserved dissent, a validation test, and a next action.

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• Deciding whether to build internally or buy a service
• Choosing between technical architecture options
• Testing a plan's assumptions before committing

Set up Diverga through an interactive researcher profile wizard. It records your discipline, experience, statistical tools, database access, and collaboration preferences, then saves configuration that guides explanations, code suggestions, and database recommendations.

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• Setting up a Diverga researcher profile
• Updating statistical software preferences
• Recording available academic databases

Run any question, idea, or decision through a council of 5 AI advisors who independently analyze it, peer-review each other anonymously, and synthesize a final verdict. Based on Karpathy's LLM Council methodology. MANDATORY TRIGGERS: 'council this', 'run the council', 'war room this', 'pressure-test this', 'stress-test this', 'debate this'. STRONG TRIGGERS (use when combined with a real decision or tradeoff): 'should I X or Y', 'which option', 'what would you do', 'is this the right move', 'validate this', 'get multiple perspectives', 'I can't decide', 'I'm torn between'. Do NOT trigger on simple yes/no questions, factual lookups, or casual 'should I' without a meaningful tradeoff (e.g. 'should I use markdown' is not a council question). DO trigger when the user presents a genuine decision with stakes, multiple options, and context that suggests they want it pressure-tested from multiple angles.

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Run a structured 5-day process to prototype, test, and validate product ideas with real users. Use when the user mentions "design sprint", "validate before we build", "rapid prototype", "test with users", or "should we build this". Also trigger when a team is stuck in endless debate over a high-stakes product decision, or wants to de-risk a costly idea before investing in development. Covers mapping, sketching, deciding, prototyping, and testing across Monday-Friday. For ongoing experimentation and MVPs, see lean-startup. For customer job analysis, see jobs-to-be-done. For non-leading user interviews, see mom-test.

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Comprehensive multi-perspective review using specialized judges with debate and consensus building

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哈耶克 × 米塞斯 × Claude 三人对话。奥派经济学视角的多角色讨论。 触发方式：/dbs-chatroom-austrian、/chatroom-austrian、/奥派、「奥派聊天室」 Austrian economics chatroom. Hayek × Mises × Claude debate. Trigger: /dbs-chatroom-austrian, /chatroom-austrian, /奥派, "Austrian chat"

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Compare independent opinions from several models or contexts without inflating agreement. Use when: wanting a second opinion or debate, or summarizing several reviewers' results.

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Implements missing-data sensitivity analyses for confirmatory clinical trials including MMRM under MAR (with Kenward-Roger correction), reference-based multiple imputation (J2R, CR, CIR, LMCF per Carpenter-Roger 2013), Permutt delta-adjustment / tipping-point analysis, pattern-mixture identifying restrictions (CCMV, NCMV, ACMV), and the Cro vs Bartlett variance debate. Use when handling missing primary or secondary endpoint data in regulatory submissions following NRC 2010 and ICH E9(R1).

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Prepares statistical reports for clinical trials following CONSORT 2025, SPIRIT 2025, ICH E9(R1) estimands, and FDA 2023 covariate adjustment guidance. Covers Table 1 generation, analysis populations (ITT/FAS/PP/Safety), the 5 ICH E9(R1) intercurrent-event strategies, MMRM under MAR (mmrm), reference-based MI (rbmi J2R/CR/CIR), Permutt tipping-point sensitivity, and Rubin's-rules vs frequentist variance debate. Use when preparing regulatory submissions, defining estimands, or implementing missing-data sensitivity analyses.

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5 expert personas debate proposed changes before implementation. Catches architectural, security, performance, and UX issues early. Use before major features or risky changes.

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Use when coordinating multiple AI agents with Agent Relay's workflow engine and need to pick the right orchestration pattern - covers the 10 core patterns (fan-out, pipeline, hub-spoke, consensus, mesh, handoff, cascade, dag, debate, hierarchical) plus 14 specialized ones, with decision framework and accurate SDK/YAML examples.

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Select and configure a structured discussion protocol matched to the purpose, topic, and group readiness. Use when planning classroom discussions, Socratic seminars, or structured debate.

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