Design an AI Research Agent for Market Analysis
Create a specification for an AI agent that autonomously researches market trends, compiles competitor data, and generates weekly market intelligence reports.
Design an autonomous research agent that replaces 10 hours/week of manual market research with structured, actionable intelligence.
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Prompt objective
Design an autonomous research agent that replaces 10 hours/week of manual market research with structured, actionable intelligence.
Real use case
A strategy team at a fintech startup needs weekly reports on 5 competitors, regulatory changes, and market trends. Currently a junior analyst spends 10 hours/week compiling this from various sources.
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Prompt
Act as an AI solutions architect. Design a complete AI research agent specification for [COMPANY NAME] in the [INDUSTRY] sector.\n\n**Context:**\n- Research scope: [NUMBER] competitors, [NUMBER] market segments, [NUMBER] regulatory bodies\n- Data sources: [SOURCE 1], [SOURCE 2], [SOURCE 3], [SOURCE 4]\n- Report frequency: weekly on [DAY]\n- Report audience: [EXECUTIVE TEAM/STRATEGY TEAM/ALL]\n\n**Deliverables (numbered):**\n1. Agent architecture: role definition, capabilities, tools/APIs the agent can access, decision boundaries, and escalation triggers\n2. Research methodology: how the agent collects data (web scraping, API calls, RSS feeds), validates sources (credibility scoring), and cross-references information\n3. Report structure: executive summary (max 300 words), competitor moves (new features, pricing changes, partnerships), regulatory updates, market trend analysis, strategic recommendations\n4. Tool integration: list of APIs and services the agent needs (news APIs, SEC filings, social listening, [OTHER]), rate limits, and authentication\n5. Quality controls: fact-checking mechanism (minimum 2 sources per claim), confidence scoring, human-in-the-loop review points, hallucination prevention\n6. Output format: structured JSON for dashboard consumption + formatted PDF/Notion page for human reading\n7. Safety guardrails: topics to avoid, data handling policies, source attribution requirements, and maximum automation level before human approval\n\n**Constraints:**\n- Must cite all sources with URLs and access dates\n- Must flag information older than [DAYS] days as potentially stale\n- Must never fabricate data or fill gaps with assumptions
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