👋 Hi, I’m Andre and welcome to my newsletter Data Driven VC which is all about becoming a better investor with Data & AI. ICYMI, check out some of our most read episodes:
Welcome to another edition of our Sunday “Resources” stream where we share our most valuable data & resources across four rotating formats:
For 1. and 3., we collaborate with best-in-class partners to ensure you get the highest quality data. For 2. and 4., we leverage our ever-growing product portfolio and share selective snapshots of the most sought-after resources from The Lab.
Resources Start Compounding
In past “Resources” episodes we shared our top prompts for startup sourcing, screening & due diligence, and deal winning & closing, and various lists with active 312 family offices, 59 pension funds, 1513 angel investors, and 997 accelerators you should know.
Access these and more resources like our 50+ masterclasses, automation templates, Notion templates, copilots, and more via The Lab.
Why You Cannot Afford to be an Average Prompter
I continue to get very positive feedback on our prompt library but what surprises me most is that so many readers still struggle to maximize value from ChatGPT & co by prompting yourself. Therefore, I decided to share all my learnings & best practices of prompting below!
In this episode, we’ll cover:
The Basics of Great Prompting
Key Prompt Writing Frameworks
Advanced Prompting Techniques
Special Hacks to Improve the Output
Summary + More Resources
This guide is designed as a practical manual and covers the full spectrum of what makes a great prompt. By the end, you’ll have everything to stop being an average prompter and get the most of ChatGPT, Gemini, Claude and others.
Let’s jump in!
Part 1: The *Basics* of Great Prompting
Specificity Wins
Bad: “Tell me about SaaS.”
Good: “Compare European vertical SaaS companies in healthcare vs. logistics, founded after 2018, that raised Series A in 2024. Output: table with founders, funding, core differentiation, and top customers.”
👉 Rule of thumb: If you wouldn’t ask it in a partner meeting, don’t ask it in a prompt.
Structure the Output
Always define:
Format: table, bullets, executive summary.
Depth: overview vs. deep dive.
Audience: investor, customer, founder, LP.
Length: word count, paragraph count, slide count.
👉 Example: “2-paragraph summary in LP memo style.”
Iteration Is the Real Superpower
Think of prompting as a loop, not a one-shot:
Draft initial request.
Inspect output.
Refine constraints.
Push deeper.
👉 This mimics how you develop an investment thesis.
Anchor With Examples
AI learns better when you show it samples.
Provide a sample memo for style.
Provide a mock-up table for format.
Provide a tone reference (“write like Stratechery, not like a PR press release”).
👉 Helps the model to limit the option room.
Layer Perspectives
Ask the AI to role-play as:
A founder defending their strategy.
A competitor critiquing weaknesses.
An LP testing your thesis.
A customer evaluating ROI.
👉 This surfaces blind spots early.
Progression: Information → Insight → Action
Most people stop at information retrieval.
Level 1: “Summarize fintech trends in Europe.”
Level 2: “Rank trends by probability of collapse in 3 years.”
Level 3: “Translate into 3 investment theses with example startups.”
👉 The edge lies in pushing one step further than others.
Part 2: Key Prompt Writing *Frameworks*
The RICCE Framework (Role – Instruction – Context – Constraints – Examples)
This is one of the most reliable scaffolds for precise, high-quality prompts.
Role: Who should the AI “be”? (analyst, founder, LP, lawyer)
Instruction: What exactly should it do? (summarize, analyze, brainstorm, critique)
Context: What background does it need? (company details, market conditions, user persona)
Constraints: What boundaries should apply? (word count, tone, format, exclusions)
Examples: Show what “good” looks like (sample memo, outline, or tone guide).
Example Prompt: “You are a VC analyst (Role). Create an investment memo (Instruction) on a seed-stage AI infra startup raising Series A (Context). Limit to 500 words, bullet point format, no jargon (Constraints). Use the style of the Sequoia scout memo attached below (Example).”
👉 Best for structured outputs like memos, reports, or research summaries.
COTAR Framework (Context – Objective – Task – Action – Result)
Designed for problem-solving and analysis where reasoning matters.
Context: Set the stage with relevant background.
Objective: Define the end goal clearly.
Task: Specify the concrete work the model should do.
Action: Instruct how to approach the task (step by step, with comparisons, etc.).
Result: Define the expected output format or deliverable.
Example Prompt: “Context: We are analyzing the Series B SaaS market in Europe. Objective: identify top 5 investment opportunities. Task: compare companies by traction, team, and market size. Action: think step by step, then rank them with justification. Result: provide a ranked table with scores for each factor.”
👉 Best for evaluations, rankings, or decisions where the model needs to “think out loud.”
P-R-A-T Framework (Persona – Request – Audience – Tone)
A lighter framework ideal for communication prompts (emails, LP updates, blog posts, tweets).
Persona: Who’s speaking? (VC partner, founder, thought-leader, marketer)
Request: What’s the specific writing task? (draft, rewrite, summarize)
Audience: Who is it for? (LPs, founders, Gen Z users, enterprise buyers)
Tone: How should it sound? (formal, persuasive, optimistic, urgent, witty)
Example Prompt: “Persona: VC partner. Request: Draft an email update about our new investment in Company X. Audience: LPs. Tone: crisp, confident, professional.”
👉 Best for tone-sensitive writing — where the how matters as much as the what.
Summary: When to Use Which Framework
Together, these 3 frameworks give you scaffolds for every major use case:
RICCE → structured research/analysis
COTAR → problem-solving & reasoning
PRAT → communication & writing
