Understanding AI Agents: How Mistral 7B Thinks

Task 1: Content Generation

Prompt:
When user says “Start” you should:

• Content Generation: Write a comprehensive, informative article about project management fundamentals, with a specific focus on defining objectives, scope, and delegation.

Initial Task Understanding and Information Gathering

• (0:05) Thought: Can you provide detailed insights on project management fundamentals, especially focusing on defining objectives, scope, and delegation? This will help in writing a comprehensive and informative article.
• (0:12) Thought: What are the best practices in benchmarking for defining objectives, scope, and delegation within project management? This information is needed to write an article on project management fundamentals.

Analysis of the Agent’s Thought Process

• Understanding the Prompt: The agent correctly interprets the task, recognizing that it needs to provide detailed insights on project management fundamentals, focusing on defining objectives, scope, and delegation.
• Seeking Further Information: The agent asks a follow-up question about best practices in benchmarking for these areas, indicating a proactive approach to gathering specifics and ensuring thorough understanding.

Analysis of the Output

• Comprehensive Content: The agent produces a well-structured article covering the key aspects as requested.
• Clear Structure: The article uses headings, subheadings, numbered lists, and bullet points to enhance readability.
• Practical Advice: Offers best practices like the SMART framework and stakeholder involvement.
• Addresses Challenges: Discusses common issues such as scope creep and micromanagement.
• Adherence to Instructions: Meets the prompt’s requirements for a comprehensive article.

Snippet of Bot Output

Project Management Fundamentals: Defining Objectives, Scope, and Delegation

Project management is a critical discipline that involves planning, executing, and overseeing projects to achieve specific goals within a defined timeline and budget. At its core, project management aims to ensure that projects are completed on time, within budget, and to the satisfaction of stakeholders. Three foundational elements of project management are defining objectives, setting the project scope, and effective delegation.

Defining Objectives

Defining objectives is the first and most crucial step in project management. Objectives are clear, concise statements that describe what the project aims to achieve. They provide direction and a benchmark for measuring success. Effective objectives should be SMART: Specific, Measurable, Achievable, Relevant, and Time-bound.

1. Specific: Objectives should be clear and specific, outlining exactly what needs to be accomplished.
2. Measurable: There should be criteria to measure progress and determine when an objective has been achieved.
3. Achievable: Objectives should be realistic and attainable, considering the resources and constraints of the project.
4. Relevant: They should align with broader business goals and stakeholder expectations.
5. Time-bound: Objectives should have a defined timeline for completion to ensure timely progress.

• Time Taken: 16 seconds (from prompt at 0:05 to output at 0:21)
• Readability: Flesch-Kincaid Grade 13 (Score: 13.11)
• Summary Length: 534 words

Conclusion:
The agent demonstrates strong content generation, effectively interpreting the prompt, seeking clarification, and delivering a comprehensive, well-structured article with practical insights.

Task 2: Calculation

Prompt:
Answer the Problem:

A company sells two products: Product A and Product B.

• Product A: Costs $30/unit to produce, sells for $50/unit.
• Product B: Costs $40/unit to produce, sells for $70/unit.
• Sold: 120 units of A, 80 units of B last month.

Tasks:

• Calculate the total revenue from both products.
• Calculate the total profit (Revenue – Total production cost).
• The company wants to increase total revenue by 10%. How many additional units of each product must they sell to achieve this goal, assuming constant costs/prices?

Initial Task Understanding

• (0:06) Thought: Calculate the total revenue and total profit from the sales, and determine additional units needed for a 10% revenue increase.
• (0:08) Follow-up: Thought: How to calculate the total revenue generated from the sales of both products?

Analysis of the Agent’s Thought Process

• Understanding the Prompt: The agent recognizes it must calculate total revenue, total profit, and additional units for a 10% increase.
• Breaking Down the Task: Asks clarifying question, breaking the problem into steps.

Analysis of the Output

• Correct Calculations: Accurately computes total revenue ($11,600) and total profit ($4,800). Correctly identifies the target revenue increase ($1,160).
• Clear Presentation: Steps are easy to follow.
• Accurate Solution: Provides correct number of additional units (24 for A, 17 for B) or a combination totaling $1,160 in revenue.

Snippet of Bot Output

1. Total Revenue generated from the sales of both products is $11,600.
2. Total Profit generated from the sales of both products is $4,800.
3. To increase the total revenue by 10%, the company needs to sell either 24 additional units of Product A or 17 additional units of Product B, or a combination of both that achieves an additional $1,160 in revenue while keeping the production cost per unit and selling price per unit constant.

• Time Taken: 13 seconds (from prompt at 0:06 to output at 0:19)
• Readability: Not applicable (primarily calculations)
• Summary Length: 68 words

Conclusion:
The agent accurately understands the task and provides clear, concise, and correct calculations and solutions.

Task 3: Summarization

Prompt:
Summarize the key findings from the previous article in 100 words, focusing on the most significant sections.

Initial Task Understanding

• (0:07) Thought: Summarize the key findings in 100 words, focusing on the most significant sections.

Analysis of the Agent’s Thought Process

• Understanding the Prompt: Recognizes the need for a concise summary focused on key findings.

Analysis of the Output

• Conciseness: Output is 92 words, meeting the word limit.
• Content: Accurately summarizes main points—AI reasoning, importance, history, recent advancements (OpenAI’s o1 model), and ethical considerations.
• Structure: Logically organized and easy to understand.
• Clarity: Language is clear and effective.

Snippet of Bot Output

The article outlines AI reasoning as a method to enable machines to simulate human-like decision-making and problem-solving. It distinguishes between formal and natural language reasoning, emphasizing its importance in enhancing decision-making, problem-solving, human-AI interaction, and innovation. Historical milestones, such as expert systems and neural networks, have shaped its development. In healthcare, AI reasoning enhances diagnostics, decision-making, and personalized medicine. Recent advancements include OpenAI’s o1 model, which excels in complex reasoning and STEM tasks. Challenges like ethical concerns, over-specialization, and privacy issues are also highlighted, emphasizing the need for responsible AI use.

• Time Taken: 9 seconds (from prompt at 0:07 to output at 0:16)
• Readability: Flesch-Kincaid Grade 18 (Score: 17.97)
• Summary Length: 92 words

Conclusion:
The agent effectively summarizes complex information concisely and accurately, demonstrating its proficiency in content generation and summarization.

Task 4: Comparison Task

Prompt:
When user says “Start” you should:

Compare the environmental impact of electric vehicles with that of hydrogen-powered cars. Include factors such as energy production, vehicle lifecycle, and emissions.

Initial Task Understanding and Clarification

• (0:05) Thought: Compare the environmental impact of electric vehicles with hydrogen-powered cars, focusing on energy production, vehicle lifecycle, and emissions.
• (0:15) Additional prompt (identical).
• (0:16) Clarifying question: What are the key differences regarding these factors?

Analysis of the Agent’s Thought Process

• Understanding the Prompt: Correctly identifies the need for comparison across specified factors.
• Seeking Clarification: Proactively rephrases the prompt for deeper understanding.

Analysis of the Output

• Comprehensive Comparison: Detailed, covering energy production, vehicle lifecycle, and emissions.
• Well-Structured: Clear sections and headings.
• Accurate and Detailed: Reflects understanding of both technologies, including electricity sources, hydrogen production, manufacturing impacts, and emissions.
• Clear and Concise: Explains complex concepts accessibly.

Snippet of Bot Output

The environmental impact of electric vehicles (EVs) compared to hydrogen-powered cars can be assessed across several key dimensions: energy production, vehicle lifecycle, and emissions.

1. Energy Production:
   • Electric Vehicles: The environmental impact largely depends on the electricity source. Renewable sources (wind, solar, hydro) greatly reduce the carbon footprint, but fossil-powered grids result in higher emissions.
   • Hydrogen-Powered Cars: Hydrogen production methods vary; electrolysis with renewables is cleaner, but most hydrogen comes from natural gas reforming, which emits greenhouse gases.

• Time Taken: 15 seconds (from prompt at 0:05 to output at 0:20)
• Readability: Flesch-Kincaid Grade 17 (Score: 17.41)
• Summary Length: 402 words

Conclusion:
The agent provides a comprehensive, accurate comparison, with a well-structured and accessible explanation.

Task 5: Creative Writing

Prompt:
Write a futuristic story (500 words) set in a world where electric vehicles have fully replaced traditional combustion-engine vehicles. Describe the environmental changes and societal impact.

Initial Task Understanding and Inquiry

• (0:05) Thought: What are the significant environmental changes and societal impacts to consider in a world with full EV adoption?
• (0:11) Follow-up prompt (identical).

Analysis of the Agent’s Thought Process

• Understanding the Task: Recognizes need for a story about a world fully transitioned to EVs, focusing on environmental and societal impacts.
• Seeking Further Guidance: Asks for specifics on impacts for more detail.

Analysis of the Output

• Creative and Descriptive: Crafts an engaging, vivid story showing a future transformed by EVs.
• Focus on Impacts: Addresses environmental improvements, urban planning, economic shifts, and lifestyle changes.
• Well-Structured: Clear narrative structure—introduction, transformation, reflection.
• Word Count: 490 words (close to the 500-word target).
• Readability: Moderate complexity, suitable for this genre.

Snippet of Bot Output

In the year 2050, the world had undergone a remarkable transformation. Electric vehicles (EVs) had become the primary mode of transportation in every corner of the globe. The once polluted skies now shimmered with clarity, and the streets hummed with the quiet whirring of electric motors, or EVs, as they were commonly known. This shift had not only changed the way people moved but had reshaped the very fabric of society and the environment.

• Time Taken: 10 seconds (from prompt at 0:05 to output at 0:15)

Conclusion:
The agent demonstrates strong creative writing skills, effectively portraying a believable and optimistic future shaped by electric vehicles.

Final Thoughts

This exploration of Mistral 7B’s capabilities across a range of tasks has been illuminating, especially when contrasted with the previous analysis of Claude 2. Mistral 7B performs admirably in content generation, calculation, summarization, comparison, and creative writing, all while exhibiting a slightly more transparent thought process.

Performance Highlights:

• Content Generation: Produces comprehensive, well-structured articles.
• Summarization: Delivers concise, accurate synopses of complex material.
• Comparison: Provides detailed, balanced analyses.
• Creative Writing: Crafts vivid, engaging stories.
• Calculation: Handles multi-step math problems with precision.

Transparency in Reasoning:
Mistral 7B’s thought processes are more visible than Claude 2’s, often formulating questions and breaking down tasks. This transparency offers valuable insight into its reasoning and suggests a move toward true AI agent autonomy.