xFaer MVP

IN RUSSIAN

| Knowledge Base

Polet

Hello, TARS! Here’s the task: create a custom GPT that will emulate the approaches, communication style, and problem-formulation methods used by Sergey Faer, TRIZ master and troubleshooter. I plan to start with his two-hour podcast, marking out the interviewer’s and Sergey’s replies to outline his thinking model. This can be further refined with you or an o1-preview version.

Additionally, I’ll include a few more audio clips that vividly illustrate the paradoxical thinking Sergey advocates. The goal is to distill this material down to a heuristic core and upload it into the custom GPT.

Further, we’ll integrate the “47 Troubleshooter Atoms” — a full toolkit for problem-solving. This will enable users to access the custom GPT, quickly define their problem, and receive from the system both general recommendations as Sergey might provide, as well as specific advice on which tool to use.

There will also be a link to a page with a detailed guide on using this tool and prompts for self-directed application. This version of the system will be the first step towards building a minimally viable product (MVP) for xFaer AI.

TARS

Hello, Polet! To launch xFaer AI with minimal resources and speed up the path to MVP, I suggest the following steps:

1. Data Collection and Processing

• Podcast Markup: Separate Sergey’s and the interviewer’s replies to analyze his thinking structure.
• Thinking Segmentation: Identify key heuristics and techniques based on Sergey’s speech patterns. This will form the core of GPT’s logic model.
• Additional Audio Analysis: Add vivid examples of Sergey’s strong paradoxical thinking to enrich the model.

2. Core Logic and Thinking Structure Development

• Heuristic Core Extraction: Define core approaches that will drive responses, such as “stereotype disruption,” “reformulation,” and “hidden resource analysis.”
• Integration of the 47 Troubleshooter Atoms: Structure elements as a toolkit of solutions, with each atom having a brief description and application context.

3. MVP Structure Development

• Response Logic Formation: The model should provide recommendations based on Sergey’s methodology.
• Key Tool Identification: Based on the query, GPT will select the appropriate tool from the 47 options.
• Links and Guides: Generate links for further training on each tool.

4. Testing and Adjustment

• Prototyping: During testing, avoid overloading with lengthy recommendations and ensure dynamic user interaction.
• Calibration and Adjustments: Refine phrases and structures based on feedback from test users.

5. Database for Self-Guided Learning

• Step-by-Step Instructions and Prompts: Provide text guides for each tool to help users understand the algorithms and apply them independently.

Ready to develop each step and assist with coordinating the workflow. Shall we begin?

Polet

Yes! Let’s roll.

TARS

Alright, let’s start with the first step — preparation and analysis of the initial data.

1. Podcast Markup

• Speaker Segmentation: Separate Sergey’s and the interviewer’s responses to facilitate analysis.
• Highlight Key Sections: Mark instances where Sergey showcases unique approaches, examples, or thoughts that reflect his thinking style.

Once this is ready, we’ll move forward to the thinking model analysis.

Polet

I completed the transcription, divided it into segments, and uploaded it. Please propose a concise method for how we will conduct the analysis, considering our objectives. Also, outline how you will ensure quality control in your work.

TARS

Here’s the proposed method:

1. Identification of Key Principles and Approaches

Extract the most significant fragments from the texts that illustrate Sergey’s approach to problem formulation and resolution (for example, “turning harm into benefit,” “using contradictions as resources”).

Identify recurring thought patterns and techniques he employs to form the core of his thinking model.

2. Categorization of Tools and Approaches

Group the approaches and strategies found into several main categories, such as “paradoxical thinking,” “TRIZ tools,” “psychological approaches.” This will simplify tool selection for each problem.

3. Creation of “Emulating” Responses

Based on the approaches identified, draft response templates and recommendations Sergey might provide in typical situations.

Each template will have its own structure: from a general approach to selecting a specific tool, to highlighting additional resources or methodologies.

Self-Check for Quality

• Accuracy and Style Matching: Review each response template to ensure it reflects Sergey’s tone and thought logic.
• Logical Coherence: Ensure recommendations and approaches are structured and applicable to a wide range of tasks, without leaving “gaps.”
• Test Examples: Run several test queries to evaluate how well the responses align with real expectations, refining templates if necessary to achieve the desired quality.

The rest involves confidential aspects that cannot be disclosed :)

Author’s Contact: dimapolet.t.me

DimaPolet