Competitor Teardown Prompt
Deep-dive one competitor from public artifacts.
/ quick answer
Run against a target competitor URL + LinkedIn + reviews. Deep-dive one competitor from public artifacts.
Teardown of {{competitor}}.
Sections:
- Positioning (1 sentence, in their own words if possible).
- Pricing (with tiers if visible).
- Ideal customer (inferred from casebooks + reviews).
- 3 differentiators (with proof).
- 3 weaknesses (from reviews + missing features).
- One angle to compete on.
Sources: {{sources}}[Structured teardown with proof-linked claims]
What does the Competitor Teardown Prompt prompt do?
Run against a target competitor URL + LinkedIn + reviews.
Which AI models work with this prompt?
It is model-agnostic: it works with any capable general model. Replace the bracketed variables with your own context before running it.
What output should I expect?
[Structured teardown with proof-linked claims].
/ continue exploring
Related concepts
The vocabulary this page depends on.
- →Deep Research (AI)
Long-running AI research task that produces a cited multi-page report.
- →Research Automation
Research automation turns a question into a sourced, structured answer using search, retrieval, extraction and synthesis agents.
Related workflows
Turn this into a repeatable process.
- →Automated Competitor Research
From a product description to a structured competitor matrix in under 10 minutes.
- →Personal Research Assistant Workflow
A repeatable system to research any topic deeply in under 30 minutes.
- →AI Market Research Report in One Afternoon
From blank page to sourced, structured 20-page market report in ~4 hours.
- →Turn Deep Research Into a Weekly Executive Brief
Use an AI Deep Research agent every Monday to produce a cited market brief in 20 minutes.
Related tool stacks
The tools that run it in production.
- →AI Research & Knowledge Stack
Default toolset for analysts, founders and creators doing deep research with AI.
- →Research Automation Stack
Search, fetch, extract and synthesise sourced briefs on a schedule.
- →AI Crypto Research Stack
A read-only research stack combining an AI assistant, web search, market data and on-chain analytics to screen assets quickly.
- →On-chain Research Stack
Explorer, indexer and analytics layers combined so wallet and token questions get answered with verifiable data.
Related prompts
Reusable prompts for this job.
- →Deep Research Prompt Template
Reusable Deep Research prompt that produces cited, structured reports every time.
- →Sourced Research Brief Prompt
Produces a structured brief where every claim carries a citation.
- →Market Research Synthesizer
Compress 10-20 sources into a 1-page decision-grade brief.
- →Buyer Persona Builder Prompt
Generate a detailed persona from a product description and target market.
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.
- →AI Research vs Traditional Research
AI research compresses breadth and drafting; traditional research supplies verification and accountability for the claims you act on.