Before
Every client session came with a second job: writing it up by hand. Documentation took an hour or more each time. Notes were unstructured, hard to compare across sessions, and hard to hand over to a team member or mentor.
“Imagine documenting all your client sessions in just minutes – without losing a single detail and simultaneously measuring and analysing your clients' growth, value, and progress across various coaching sessions.”
In their own words
The turning point
In the program they did a detailed breakdown of their manual workflow to see where the time went. Then they built a Custom GPT and trained it to follow strict protocols, structuring each session into predefined categories. They tested it again and again, refining it with real user feedback until the output was clear and accurate.
After
Now a session is documented in 5–7 minutes, without losing detail. The same system handles lead management and general notes, and an Airtable database is being built as its home, with an API connection in progress. They are already planning what comes next, including a knowledge base in Tana and a private language model to protect sensitive client data.
What it lets people do
Coaches can capture a session quickly and see a client's growth and progress measured across sessions. Client data can be handed to team members or mentors with consistency and transparency.
What they learned
They learned that automating repetitive work saves time and also makes it more accurate. Building in small steps and listening to feedback kept the tool practical, and thinking about privacy early built trust into the system from the start.
“Iterative innovation: The importance of iterative development and user feedback cannot be understated, as it ensures that the automation tool remains relevant and practical.”
In their own words
Automated Client Session Documentation was built during AI Mastery.
Read the full submission
Imagine documenting all your client sessions in just minutes – without losing a single detail and simultaneously measuring and analysing your clients' growth, value, and progress across various coaching sessions. This project offers efficiency and lays the foundation for growth, better client retention, and absolute transparency.
Achievements
- Revolutionised session documentation: Reduced manual documentation time from 1 hour or more to just 5–7 minutes by automating structured client session notes.
- Streamlined workflows for different UseCases: Developed a highly efficient process for automating the documentation of client sessions, lead management, and general notes using a Custom GPT tailored for specific categories.
- Enhanced scalability: Designed a framework that supports the seamless handover of client data to team members or mentors, ensuring consistency and transparency in collaborative coaching environments.
- Visionary integration roadmap: Planned and initiated an API-based integration with Airtable, enabling real-time synchronisation of session data into the new CRM built on Airtable (or to prove another provider, in clarification)
- Structured innovation: Implemented a system that transforms unstructured input into actionable, categorised data, improving data quality and decision-making.
Tools
- Custom GPT:
- Engineered to structure session notes into predefined categories, such as challenges, discussed topics, Aha-moments, and progress analysis.
- Iteratively tested and optimised to adapt to different use cases, ensuring flexibility and precision.
- Airtable Database:
- Currently being developed as the backbone of data storage and CRM integration.
- Provides a scalable and user-friendly platform for organising session notes and tracking client progress.
- API Integration (in progress):
- Enables the automatic transfer of data from Custom GPT outputs to Airtable, CRM, and other tools, ensuring seamless workflows and eliminating manual data entry.
- in Future building
- Knowledgebase on Tana to analyse and deepen the problems and struggles of the client to build new offers and products for the client
- Inspiration for Social Media Content
- Security thoughts: Implement a personal LLM to protect sensitive client data.
- Coaching-as-a-Service Model: Developing a licensing model so external coaches can utilise the system to automate their processes
Methodology
- Process analysis: Conducted a detailed breakdown of manual documentation workflows to identify inefficiencies and areas for automation.
- GPT optimisation: Trained the Custom GPT to follow strict protocols for session structuring, ensuring consistency and reducing human error.
- Iterative development: Incorporated real-time user feedback to refine outputs, improving clarity and accuracy in the generated documentation.
- Integration focus: Built a roadmap for API-based connections to CRM tools, allowing for the automatic integration of client session data into broader management systems.
- Security-first approach: Envisioned the development of a personal Large Language Model (LLM) for enhanced privacy and data security, addressing the needs of sensitive client data management.
Learnings
- Automation is key: Automating repetitive documentation tasks saves time and ensures accuracy and scalability, highlighting the transformative potential of AI in coaching processes.
- Client progress tracking: Structured, automated documentation allows for visualising client growth, creating measurable results that enhance coach and client engagement.
- Iterative innovation: The importance of iterative development and user feedback cannot be understated, as it ensures that the automation tool remains relevant and practical.
- Future-proofing: Identifying the need for secure and scalable data management early on has established long-term sustainability and trust in the system.
RELEVANT URL: https://www.loom.com/share/576e6558bb7244e786833d0ca286873f?sid=17e8ced1-c567-4701-80ef-75c48123649c
Written 21 January 2025· Submitted by the storyteller
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