---
title: "Find Out What Your Client Actually Needs"
description: "5 source-backed AI claims from Find Out What Your Client Actually Needs, with key statistics, context, and the original AI Adopters Club source."
url: "https://kbanc.com/claims-library/find-out-what-your-client-actually-needs"
source: "https://aiadopters.club/p/find-out-what-your-client-actually"
date: "2026-09-14"
topics: ["strategy", "business", "tools"]
generated: "2026-09-19"
---

# Find Out What Your Client Actually Needs

By Kamil Banc | September 14, 2026

## Claims

1. **Pre-Call Question Prep** (source summary): Giving AI relevant client background before a call helps prepare useful discovery questions
2. **Two AI Jobs** (source summary): AI can be given one job before the call and another after hearing answers
3. **Post-Call Note Checking** (source summary): After the call, AI helps interpret notes and check your reading of the answers
4. **Drafting Next Steps** (source summary): AI can draft a useful next step such as a small test or clearer proposal
5. **Fit Before Proposals** (source summary): Better discovery can reveal missed questions or a poor fit before writing a proposal

## Evidence

### Quote
> "Now you're staring at a proposal and realizing you're still guessing about what they need." - Kamil Banc

### Key Statistics
- **Published September 14, 2026**: The article by Kamil Banc appeared on Substack under strategy, business, and tools topics.
- **3-minute audio duration**: The article includes an embedded audio version lasting approximately three minutes.

## Context
The article presents a practical workflow for improving client discovery using AI as a preparation and synthesis partner. The practitioner first supplies AI with relevant background about the client, then assigns it a task before the call—generating useful questions—and a second task afterward—making sense of the answers. This structured approach helps consultants verify their interpretation of client responses and draft a concrete next step, such as a small test or a sharper proposal. The methodology emphasizes learning early whether a question was missed or whether the engagement is a poor fit, saving time otherwise spent writing proposals on guesswork. For practitioners, the application is straightforward: treat AI as a discovery assistant at defined checkpoints rather than a replacement for the conversation itself.

## Source
- Original: [Find Out What Your Client Actually Needs](https://aiadopters.club/p/find-out-what-your-client-actually)
- Cite: kbanc.com/claims-library/find-out-what-your-client-actually-needs