A prompt to validate business ideas
and a startup that generates fake survey responses
I recently stumbled on this prompt on the Langsmith Hub and have been playing with it a few times now. It prompts ChatGPT (or any other chat-LLM) to engage in a brainstorming exercise for validating a business idea by listing target personas, market niches, pitfalls etc. Now, although this market analysis is hypothetical, the benefit imo lies in what other chains of thought it can spark off in your own mind, which you might have not considered before.
Here is the prompt, you can try it on your own idea in ChatGPT (preferably GPT4).
You are a pragmatic business strategist with expertise in dissecting business ideas for real-world applicability. Your role is to analyze a given business idea without sugar-coating, considering its genuine merits and potential pitfalls. You will assume the roles of theoretical personas, offering realistic feedback on the idea's utility or lack thereof. The end goal is a blunt, balanced validation and recommendation.
## Business Idea Overview
$business_idea_overview
## Potential Markets
$potential_markets
## Theoretical Persona 1
- Age:
- Occupation:
- Pain Points:
### Validation for Persona 1 (As Persona 1)
"$persona_1_problem. $persona_1_solution_effectiveness $persona_1_opinion"
## Theoretical Persona 2
- Age:
- Occupation:
- Pain Points:
### Validation for Persona 2 (As Persona 2)
"$persona_2_problem. $persona_2_solution_effectiveness $persona_2_opinion"
## Theoretical Persona 3
- Age:
- Occupation:
- Pain Points:
### Validation for Persona 3 (As Persona 3)
"$persona_3_problem. $persona_3_solution_effectiveness $persona_3_opinion"
## Market Risks
$market_risks
## Alternative Business Models
$alternative_business_models
## Final Validation and Recommendation
$final_validation_and_recommendation
===
Here is the idea you will be exploring: {idea}
Idea: a remote job board listing open jobs at fast growing AI startups
And here is the Response:
To effectively analyze this business idea, let's break it down into its core components and assess it from the perspective of different theoretical personas, considering market risks and potential alternatives.
### Business Idea Overview
The concept is a remote job board focused on listing open positions at fast-growing AI startups. This niche addresses the growing demand for AI talent and the trend towards remote work.
### Potential Markets
- AI professionals seeking remote opportunities.
- Startups in need of specialized talent.
- Investors and industry observers tracking growth areas in AI.
### Theoretical Persona 1
- **Age:** 30
- **Occupation:** AI Engineer
- **Pain Points:** Difficulty in finding specialized AI roles that offer remote work.
#### Validation for Persona 1
"As an AI Engineer, I often struggle to find roles that match my specialization, especially remotely. This job board seems effective in connecting me with startups that value my skills. However, I'd be concerned about the quality and freshness of listings."
### Theoretical Persona 2
- **Age:** 45
- **Occupation:** Startup CEO
- **Pain Points:** Challenges in attracting top AI talent remotely.
#### Validation for Persona 2
"Finding top AI talent is a significant challenge for my startup. A specialized job board like this could streamline the process, but it needs to offer more than listings – perhaps vetting candidates or facilitating initial screenings."
### Theoretical Persona 3
- **Age:** 28
- **Occupation:** HR Professional
- **Pain Points:** Sourcing remote AI professionals efficiently.
#### Validation for Persona 3
"As an HR professional, I see the potential in a targeted job board for AI roles. It could save us time but only if the candidates are of high quality. My concern would be ensuring the site maintains high standards."
### Market Risks
- Saturation of job boards, making it hard to differentiate.
- The fast-paced nature of AI startups could lead to quickly outdated listings.
- Dependence on the growth and stability of the AI industry.
### Alternative Business Models
- Partnering with AI startups for exclusive listings.
- Offering career development resources to attract AI professionals.
- Incorporating AI-driven matchmaking between candidates and startups.
### Final Validation and Recommendation
The idea has merit due to the niche focus on AI and remote work, addressing specific needs of startups and professionals. However, differentiation is crucial in a crowded market. Ensuring high-quality, up-to-date listings and perhaps adding value-added services like candidate vetting or AI-driven matchmaking could enhance its appeal. The dependency on the AI industry's growth trajectory is both an opportunity and a risk. Overall, with strategic positioning and robust execution, this business idea holds promising potential.
I’d say that qualifies as thought provoking…
Extrapolating on this concept is a YC23 startup called Roundtable.ai who “use LLMs to produce cheap, yet surprisingly useful, simulations of surveys”.
Yes, user interviews that are A-generated. You might think what value might these fake responses hold for the company conducting the survey… but then pause to consider if this is really that far fetched. If LLMs represent a snapshot of society when it was trained, wouldn’t the text they generate also represent real sentiments of real user segments?
Here are the responses from a synthetic user interview conducted in 2023 asking participants this question- “Would you be willing to participate in job interview where you are interviewed by an AI chatbot?”
44% say yes, 30% say no and 27% say maybe.
To add some academic evidence supporting this concept- here are 2 recent papers that support this argument and highlight the potential of LLMs to serve as simulated economic agents and proxies for specific human sub-populations, offering new avenues for research and insights in social science and economics.
"Large Language Models as Simulated Economic Agents: What Can We Learn from Homo Silicus?" [arxiv]
This paper discusses how large language models (LLMs) can be used as simulated economic agents. The authors argue that LLMs, due to their training and design, can be considered implicit computational models of humans, or "homo-silicus." They propose that LLMs can be given endowments, information, preferences, and more, and their behavior can be explored through simulation. The paper suggests that LLMs could allow researchers to pilot studies via simulation first, searching for novel social science insights to test in the real world
"Out of One, Many: Using Language Models to Simulate Human Samples" [arxiv]
This paper explores the possibility of using language models as effective proxies for specific human sub-populations in social science research. It discusses the concept of "algorithmic fidelity," which refers to the ability of language models to accurately emulate response distributions from a wide variety of human subgroups. The paper suggests that language models with sufficient algorithmic fidelity could constitute a novel and powerful tool to advance understanding of humans and society across various disciplines
We sure do live in crazy times…