The Mind of AI Agents: Gemini 2.0 Flash Experimental

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

• (0:04) The agent receives the prompt:
  Gather detailed information on project management fundamentals, specifically on defining objectives, scope, and delegation.

• (0:06) The agent starts processing and displays its first thought:
  Thought: I need to use google search to gather detailed information on project management fundamentals, specifically on defining objectives, scope, and delegation. Using tool: google_serper

• (1:04) The agent starts processing and displays its second thought:
  Thought: I need to look at these urls to gather detailed information on project management fundamentals, specifically on defining objectives, scope, and delegation. Using tool: url_crawl_tool

• (1:30) The agent starts processing and displays its third thought:
  Thought: I should search for ‘definition of project objectives in project management’ to get a more precise understanding of what project objectives are. Using tool: google_serper

• (1:34) The agent starts processing and displays its fourth thought:
  Thought: I will use the information from the crawled websites to provide a detailed overview of project management fundamentals, specifically on defining objectives, scope, and delegation. I should also ensure that the content is formatted clearly for easy understanding. Using tool: google_serper

• (1:42) The agent starts processing and displays its fifth thought:
  Thought: I should also search for ‘definition of project scope in project management’ to provide a clear definition of project scope. Using tool: google_serper

Analysis of the Agent’s Thought Process

• Understanding the Prompt: The agent correctly interprets the prompt, focusing on project management fundamentals: objectives, scope, and delegation.
• Information Gathering Strategy: Uses a mix of google_serper and url_crawl_tool, starting broad and then seeking precise definitions.
• Tool Usage: Attempts both search and direct crawling, but repeated url_crawl_tool use suggests possible retrieval issues.
• Targeted Searches: Looks for definitions of “project objectives” and “project scope.”
• Content Formatting: Notes the importance of clear formatting for user understanding.

Analysis of the Output

• Structure and Organization: Uses headings and subheadings for clarity (Defining Objectives, Managing Project Scope, Effective Delegation).
• Content Quality: Informative and accurate, using the SMART framework for objectives and giving clear explanations.
• Clarity and Readability: Clear, concise, and accessible for a general audience (Flesch-Kincaid Grade Level 12).
• Completeness: Covers all key aspects of the prompt.
• Length and Detail: Adequately detailed (709 words).

Snippet of Bot Output

Project Management Fundamentals: Defining Objectives, Scope, and Delegation

Project management is a critical discipline for ensuring the successful completion of any endeavor, whether it’s a small team project or a large-scale organizational initiative. At its core, effective project management relies on three fundamental pillars: clearly defined objectives, a well-managed scope, and effective delegation. Understanding and mastering these elements is essential for any project manager.

1. Defining Objectives

Project objectives are specific, measurable goals a project aims to achieve. They act as the compass guiding the project team and define what success looks like. Well-defined objectives are:

• Specific: Clear and unambiguous (e.g., “increase customer satisfaction scores by 15% by the end of Q4”).
• Measurable: Quantifiable with set metrics and targets.
• Achievable: Realistic given resources and capabilities.
• Relevant: Aligned with strategic goals and organizational mission.
• Time-bound: Attached to a clear deadline or timeframe.

Examples:

• Launch a new product by [date] with [number] features.
• Reduce project costs by [percentage] within [timeframe].
• Increase website traffic by [percentage] in [timeframe].
• Improve team collaboration by implementing [tool/process] by [date].

Time Taken:
The agent receives the prompt at 0:04 and finishes at 2:07 (about 2 minutes and 3 seconds).

Conclusion:
The agent generates a high-quality article, demonstrates good understanding, gathers information effectively, and formats content clearly. Repeated url_crawl_tool attempts suggest improvement is needed for error handling or alternate approaches.

Task 2: Calculation

Prompt:
A company sells two products: Product A and Product B. Product A costs $30 per unit to produce and sells for $50 per unit. Product B costs $40 per unit to produce and sells for $70 per unit.

The company sold 120 units of Product A and 80 units of Product B last month. Calculate the total revenue generated from the sales of both products.

Calculate the total profit generated from the sales of both products (Revenue – Total production cost).

The company wants to increase the total revenue by 10%. How many additional units of each product must they sell to achieve this goal, assuming the production cost per unit and selling price per unit remain constant?

Initial Task Understanding and Information Gathering

• (0:05) Agent receives prompt: calculate total revenue from both products.
• (0:07) Agent’s thought: use Google search (google_serper).
• (0:10) Agent outputs: Total revenue = $11,600.
• (0:13) Receives prompt: calculate total profit from both products.
• (0:17) Thought: use Google search.
• (0:22) Outputs: Total profit = $4,800.
• (0:24) Receives prompt: How many additional units to increase revenue by 10%?
• (0:32-1:02) Repeated thoughts: use Google search, appears stuck in a loop.

Analysis of the Agent’s Thought Process

• Prompt Understanding: Interprets prompts correctly: revenue, profit, required sales increase.
• Information Gathering: Relies solely on Google search (google_serper).
• Tool Usage: No use of specialized calculation tools; stuck in search loop for complex query.

Analysis of the Output

• Accuracy: Revenue and profit answers are correct. The answer for revenue increase is incorrect; correct would be “12 units of Product A and 8 units of Product B.”
• Clarity: Final output is clear and organized.
• Structure: Addresses each prompt separately.

Snippet of Bot Output

1. Total Revenue: $11,600
2. Total Profit: $4,800
3. To increase total revenue by 10%, approximately 10 additional units of Product A and 10 additional units of Product B are needed (should be 12 and 8).

Time Taken:
Prompt at 0:05, output at 1:06 (about 1 minute and 1 second).

Conclusion:
Agent understands prompts and handles simple calculations, but struggles with multi-step calculations and gets stuck in repetitive loops. Needs specialized tools and improved problem-solving strategies.

Task 3: Summarization

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

Initial Task Understanding and Information Gathering

• (0:01) Agent receives the prompt and provided text.
• (0:37) Agent’s thought: read text and summarize key points about AI reasoning, applications, and OpenAI’s o1 models, using text_summarize_tool.

Analysis of the Agent’s Thought Process

• Prompt Understanding: Interprets summarization task correctly.
• Information Gathering: No external search needed; all info in text.
• Tool Usage: Uses text_summarize_tool, but only summarizes part of the text.

Analysis of the Output

• Structure: Single paragraph; could be improved with bullet points/sections.
• Content Quality: Captures main points (AI reasoning, applications, OpenAI o1 models), but omits details like safety features, STEM performance, hallucination mitigation, data diversity, cost-effectiveness.
• Clarity: Clear, concise, higher-level writing.
• Completeness: Not fully comprehensive; important details omitted.
• Length: 115 words (source text 514 words).

Snippet of Bot Output

AI reasoning, mimicking human thought processes, is crucial for advanced AI systems. It encompasses formal reasoning (rule-based) and natural language reasoning (handling ambiguity). AI reasoning enhances decision-making, problem-solving, and human-AI interaction across various fields. Historically, AI reasoning evolved from simple rule-based systems to expert systems, neural networks, and modern models like GPT and neuro-symbolic AI. Applications span healthcare (improving diagnostics, clinical decisions, and personalized medicine), finance (streamlining processes, fraud detection), and numerous other sectors. While offering efficiency and accuracy, challenges include over-specialization and ethical concerns. OpenAI’s o1 models represent a significant advancement, utilizing chain-of-thought reasoning, enhanced safety features, and achieving top rankings in STEM benchmarks. These models address issues like hallucinations and offer cost-effective options.

Time Taken:
Prompt at 0:01, output at 0:40 (39 seconds).

Conclusion:
Agent demonstrates understanding of summarization, but output lacks completeness. Needs improved summarization techniques and structuring.

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 Information Gathering

• (0:05) Receives prompt: compare environmental impact of EVs and hydrogen cars.
• (0:08) Thought: use Google search.
• (0:24-0:35) Continues Google search, then uses found information for comparison.

Analysis of the Agent’s Thought Process

• Prompt Understanding: Recognizes the need for comparative analysis.
• Information Gathering: Uses Google search.
• Tool Usage: Correctly uses search tool for this type of analysis.
• Focus: Covers energy production, lifecycle, and emissions.

Analysis of the Output

• Structure: Organized by Energy Production, Vehicle Lifecycle, Emissions, and Summary.
• Comprehensive: Covers major environmental factors, including energy sources, hydrogen production, manufacturing, and end-of-life.
• Clarity: Clear, though some sentences are complex.
• Balance: Presents both pros and cons of each technology.

Snippet of Bot Output

Energy Production:

• EVs: Environmental impact depends on electricity source; renewables yield minimal carbon footprint, fossil fuels increase it.
• Hydrogen-Powered Cars: Impact depends on hydrogen production; most hydrogen currently from natural gas (high CO₂). Electrolysis with renewable electricity is cleaner.

Time Taken:
Prompt at 0:05, output at 0:35 (30 seconds).

Readability:

• Flesch-Kincaid Grade Level: 14
• Flesch-Kincaid Score: 14.44
• Summary Length: 613 words

Conclusion:
Agent provides a well-structured, balanced, and comprehensive comparison. Readability could improve with simpler sentences.

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 Information Gathering

• (0:05) Receives prompt for creative writing about a future with only electric vehicles.
• (0:16) Final output shown.

Analysis of the Agent’s Thought Process

• Prompt Understanding: Correctly interprets the creative, future-focused narrative request.
• Information Gathering: Relies on internal knowledge and creativity.
• Focus: Develops a narrative exploring both environmental and societal changes.

Analysis of the Output

• Creativity: Engaging narrative, vivid future vision.
• Structure: Logical progression from environmental to societal impacts.
• Comprehensiveness: Covers air quality, urban landscape, energy, infrastructure, employment, accessibility, geopolitics.
• Balance: Addresses positives and challenges (e.g., electricity demand, battery sustainability).
• Narrative Voice: Consistent, descriptive, and hopeful.

Snippet of Bot Output

In the year 2045, the world had undergone a profound transformation. The once-persistent hum of combustion engines had faded into obscurity, replaced by the near-silent whirr of electric vehicles (EVs) that now dominated the roads. This shift marked not just a technological revolution but a societal metamorphosis, where the environment and human life intertwined in unprecedented harmony.

The skies over metropolitan areas, once choked with smog and exhaust fumes, had cleared to reveal a vibrant blue canopy. The air was crisp, carrying the scent of greenery rather than the acrid tang of pollution. Respiratory ailments, once rampant, had dwindled significantly, lifting a burden from healthcare systems and improving lives. People took deep breaths of the clean air, a simple pleasure that had become a profound symbol of change.

Time Taken:
Prompt at 0:05, output at 0:16 (11 seconds).

Readability:

• Flesch-Kincaid Grade Level: 14
• Flesch-Kincaid Score: 13.58
• Summary Length: 623 words

Conclusion:
Agent excels at creative writing, generating an imaginative, well-structured narrative that addresses both environmental and societal impacts.

Gemini 2.0 Flash Experimental: A Glimpse into the Future of AI, with Room to Grow

Gemini 2.0 Flash Experimental demonstrates significant promise as an advanced AI agent. It consistently performs well in:

• Information retrieval
• Content generation
• Comparison tasks
• Creative writing

It effectively uses tools like google_serper and shows understanding of complex topics. Its narrative abilities highlight a leap in AI creativity.

However, key deficiencies remain:

• Calculation: Struggles with multi-step math, inefficient search-based methods, and incorrect answers.
• Summarization: Identifies the correct tool but omits key information.
• Repetitive thought processes: Can get stuck in loops.
• Limited tool selection: Over-reliance on search for tasks needing specialized tools.

Key Strengths

• Strong content generation
• Effective information retrieval
• Excellent comparisons
• Exceptional creative writing

Key Weaknesses

• Poor calculation abilities
• Incomplete summarization
• Repetitive reasoning loops
• Limited toolset and selection

Areas for Improvement

• Enhanced Calculation Engine: Integrate a dedicated calculator or improve tool selection.
• Improved Summarization: Use robust algorithms, structure summaries with bullets or headings.
• Dynamic Reasoning: Break repetitive loops, explore alternatives.
• Expanded Toolset: More tools and smarter selection logic.
• Instruction Adherence: Keep within specified word limits.
• Better Output Organization: Especially for calculation-heavy problems.