Automated Competitor Research
From a product description to a structured competitor matrix in under 10 minutes.
/ quick answer
Use an AI agent to discover competitors, scrape their positioning, and output a normalized comparison table. From a product description to a structured competitor matrix in under 10 minutes.
- 01Define your product in one sentence and your target customer.
- 02Run the competitor discovery prompt against a web-search-enabled agent.
- 03For each result, extract pricing, positioning, and 3 differentiators.
- 04Normalize fields into a single table.
- 05Generate a one-paragraph strategic summary.
- Run weekly as a cron to track competitor changes.
- Filter only to YC-backed companies in the same category.
What does the Automated Competitor Research workflow do?
Use an AI agent to discover competitors, scrape their positioning, and output a normalized comparison table.
What problem does Automated Competitor Research solve?
Manually researching competitors takes hours and produces inconsistent notes that are hard to compare.
How many steps does Automated Competitor Research take?
5 steps. It starts with define your product in one sentence and your target customer. and ends with generate a one-paragraph strategic summary..
Which tools does Automated Competitor Research need?
It uses agent-research-stack — each linked below with its own node.
/ continue exploring
Related concepts
The vocabulary this page depends on.
- →AI Agent
An autonomous AI system that plans and executes multi-step tasks.
- →Prompt Chaining
Pipelining LLM calls where each step's output feeds the next.
- →LLM Orchestration
Coordinating multiple model calls, tools, and data sources into one reliable system.
- →Agent Memory
Persistent context that lets agents retain preferences, decisions, and prior work.
Related workflows
Turn this into a repeatable process.
- →Continuous AI Competitor Monitoring
Track competitors' pricing, features, content and hiring in near-real-time with an AI digest.
- →Personal Research Assistant Workflow
A repeatable system to research any topic deeply in under 30 minutes.
Related tool stacks
The tools that run it in production.
- →Agent Research Stack
Web-search-enabled agent for autonomous research tasks.
- →AI Research & Knowledge Stack
Default toolset for analysts, founders and creators doing deep research with AI.
- →Solo Market Researcher Stack
One person running weekly market intel across 20+ companies.
- →Research Automation Stack
Search, fetch, extract and synthesise sourced briefs on a schedule.
Related prompts
Reusable prompts for this job.
- →Competitor Discovery Prompt
Surface and structure direct competitors for a given product.
- →Competitor Teardown Prompt
Deep-dive one competitor from public artifacts.
- →Market Research Synthesizer
Compress 10-20 sources into a 1-page decision-grade brief.
- →Deep Research Prompt Template
Reusable Deep Research prompt that produces cited, structured reports every time.
Related use cases
How people apply it, and what came out.
- →Tech Creator Replaces a Research Assistant With a Workflow
A YouTuber cut their research time per video from 8 hours to 90 minutes.
- →Research A Token With AI
A structured AI research pass cut token screening from three hours to 35 minutes and produced documented passes instead of impulse entries.
- →Build An AI Crypto Research Agent
A read-only research agent produced daily briefings on a 30-token watchlist, cutting a 90-minute manual routine to a 10-minute review.
Comparisons & alternatives
Pick between the options.
- →GPT vs Claude for Business Workflows
Choosing the right model family for production use.
- →AI Agent vs Workflow Automation
When to use autonomous reasoning and when to use deterministic automation.
- →AI Research vs Traditional Research
AI research compresses breadth and drafting; traditional research supplies verification and accountability for the claims you act on.