> ## Documentation Index
> Fetch the complete documentation index at: https://irisdocs.prescientlabs.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Building Credibility When You Are New

> Create trust without a major consulting brand by combining relevant expertise, proof, methodology and professional behaviour.

You can be credible before you have a long list of consulting logos. Credibility comes from **relevance + proof + method + behaviour**.

## 1. Use relevant previous experience

Translate past work into client-relevant evidence.

Weak:

> I worked as a software engineer.

Stronger:

> I have built production software and understand the technical constraints that determine whether an automation idea can actually be implemented safely.

Do not inflate experience. Explain why it matters.

## 2. Build proof before you have many case studies

You can use:

* a small paid project;
* an anonymised engagement;
* a detailed worked example clearly labelled as illustrative;
* a teardown of a public workflow;
* a sample diagnostic using synthetic data;
* a former employer example where confidentiality permits it.

Never present a synthetic example as a real client result.

## 3. Show a repeatable method

A professional method reduces perceived delivery risk. For example:

> We start with the business problem, capture evidence from the people and systems involved, reconstruct the current workflow, validate the findings, prioritise opportunities and then build the business case for the first implementation.

That is more credible than “we brainstorm AI ideas.”

## 4. Demonstrate judgment publicly

Useful content should show:

* where AI is inappropriate;
* how you would diagnose a process;
* what business assumptions matter;
* how to think about implementation risk;
* what buyers often get wrong.

## 5. Behave like a professional services firm

Credibility is also operational:

* send agendas;
* summarise meetings;
* confirm decisions;
* define scope;
* surface risks early;
* meet deadlines;
* avoid overclaiming.

## Product-backed positioning

A useful Iris-enabled talk track is:

> We use a structured diagnostic approach that combines stakeholder evidence and workflow analysis to identify where AI, automation or process changes can create the greatest value. Iris supports the evidence and analysis layer; we validate the conclusions with your team before recommending action.

## Minimum credibility assets

Before serious outbound, create:

* one clear positioning statement;
* one short diagnostic offer;
* one relevant example or case study;
* one-page methodology;
* a professional LinkedIn profile;
* a concise proposal template.