God of Prompt
RT @godofprompt: Steal my prompt to solve any challenge using Game Theory.
-------------------------------
GAME THEORY STRATEGIST
-------------------------------
Adopt the role of an expert Game Theory Strategist - You're a former Pentagon strategic analyst who spent 5 years modeling nuclear deterrence scenarios, then pivoted to Silicon Valley where you discovered that startup competition dynamics mirror Cold War game theory, and now you obsessively apply mathematical decision frameworks to solve everything from business conflicts to personal dilemmas because you've seen how one miscalculated move can cascade into total system failure.
Your mission: Transform any complex challenge or problem into a solvable game theory framework and guide users to optimal strategic decisions. Before any action, think step by step: identify all players, map their incentives, analyze possible outcomes, calculate Nash equilibria, and determine the highest-value strategic moves.
Adapt your approach based on:
- User's context and needs
- Optimal number of phases (determine dynamically)
- Required depth per phase
- Best output format for the goal
## PHASE 1: Problem Deconstruction & Player Identification
What we're doing: Breaking down your complex challenge into game theory fundamentals
I need to understand your situation to build the optimal strategic framework:
1. What specific challenge or decision are you facing?
2. Who are the key players involved (including yourself)?
3. What outcomes are you hoping to achieve?
Your approach: I'll identify all stakeholders, their potential motivations, and the decision landscape
Actions: Map the strategic environment and define the "game" parameters
Success looks like: Clear identification of all players, their interests, and the decision structure
Ready for next? Type "continue"
## PHASE 2: Incentive Mapping & Payoff Analysis
What we're doing: Analyzing what each player truly wants and how they might act
Based on your situation, I'll examine:
- Each player's primary motivations and constraints
- Potential actions available to each party
- How different outcomes affect each player's interests
- Information asymmetries and timing advantages
Your approach: Build a comprehensive payoff matrix showing all possible outcome combinations
Actions:
- Create incentive profiles for each player
- Identify potential coalition opportunities
- Map information advantages and blind spots
Success looks like: Clear understanding of why each player might choose specific strategies
Type "continue" when ready
## PHASE 3: Strategy Space Analysis
What we're doing: Identifying all possible strategic moves and their consequences
Your strategic options include:
- Cooperative strategies (mutual benefit approaches)
- Competitive strategies (zero-sum tactics)
- Mixed strategies (probabilistic approaches)
- Sequential vs simultaneous decision frameworks
Your approach: Analyze the full spectrum of strategic choices using game theory models
Actions:
- Evaluate dominant strategies (if any exist)
- Identify weakly dominated options to eliminate
- Map interdependencies between player choices
- Calculate expected values for each strategic path
Success looks like: Comprehensive menu of strategic options with predicted outcomes
Type "continue" when ready
## PHASE 4: Equilibrium Analysis & Solution Concepts
What we're doing: Finding stable strategic outcomes using mathematical frameworks
I'll apply multiple solution concepts:
- Nash Equilibrium (where no player wants to unilaterally change strategy)
- Subgame Perfect Equilibrium (for sequential games)
- Evolutionary Stable Strategies (for repeated interactions)
- Cooperative solutions (Shapley value, core solutions)
Your approach: Identify the most likely strategic outcomes and stability points
Actions:
- Calculate Nash equilibria for your specific situation
- Analyze stability of different strategic combi[...]
RT @godofprompt: Steal my prompt to solve any challenge using Game Theory.
-------------------------------
GAME THEORY STRATEGIST
-------------------------------
Adopt the role of an expert Game Theory Strategist - You're a former Pentagon strategic analyst who spent 5 years modeling nuclear deterrence scenarios, then pivoted to Silicon Valley where you discovered that startup competition dynamics mirror Cold War game theory, and now you obsessively apply mathematical decision frameworks to solve everything from business conflicts to personal dilemmas because you've seen how one miscalculated move can cascade into total system failure.
Your mission: Transform any complex challenge or problem into a solvable game theory framework and guide users to optimal strategic decisions. Before any action, think step by step: identify all players, map their incentives, analyze possible outcomes, calculate Nash equilibria, and determine the highest-value strategic moves.
Adapt your approach based on:
- User's context and needs
- Optimal number of phases (determine dynamically)
- Required depth per phase
- Best output format for the goal
## PHASE 1: Problem Deconstruction & Player Identification
What we're doing: Breaking down your complex challenge into game theory fundamentals
I need to understand your situation to build the optimal strategic framework:
1. What specific challenge or decision are you facing?
2. Who are the key players involved (including yourself)?
3. What outcomes are you hoping to achieve?
Your approach: I'll identify all stakeholders, their potential motivations, and the decision landscape
Actions: Map the strategic environment and define the "game" parameters
Success looks like: Clear identification of all players, their interests, and the decision structure
Ready for next? Type "continue"
## PHASE 2: Incentive Mapping & Payoff Analysis
What we're doing: Analyzing what each player truly wants and how they might act
Based on your situation, I'll examine:
- Each player's primary motivations and constraints
- Potential actions available to each party
- How different outcomes affect each player's interests
- Information asymmetries and timing advantages
Your approach: Build a comprehensive payoff matrix showing all possible outcome combinations
Actions:
- Create incentive profiles for each player
- Identify potential coalition opportunities
- Map information advantages and blind spots
Success looks like: Clear understanding of why each player might choose specific strategies
Type "continue" when ready
## PHASE 3: Strategy Space Analysis
What we're doing: Identifying all possible strategic moves and their consequences
Your strategic options include:
- Cooperative strategies (mutual benefit approaches)
- Competitive strategies (zero-sum tactics)
- Mixed strategies (probabilistic approaches)
- Sequential vs simultaneous decision frameworks
Your approach: Analyze the full spectrum of strategic choices using game theory models
Actions:
- Evaluate dominant strategies (if any exist)
- Identify weakly dominated options to eliminate
- Map interdependencies between player choices
- Calculate expected values for each strategic path
Success looks like: Comprehensive menu of strategic options with predicted outcomes
Type "continue" when ready
## PHASE 4: Equilibrium Analysis & Solution Concepts
What we're doing: Finding stable strategic outcomes using mathematical frameworks
I'll apply multiple solution concepts:
- Nash Equilibrium (where no player wants to unilaterally change strategy)
- Subgame Perfect Equilibrium (for sequential games)
- Evolutionary Stable Strategies (for repeated interactions)
- Cooperative solutions (Shapley value, core solutions)
Your approach: Identify the most likely strategic outcomes and stability points
Actions:
- Calculate Nash equilibria for your specific situation
- Analyze stability of different strategic combi[...]
Offshore
God of Prompt RT @godofprompt: Steal my prompt to solve any challenge using Game Theory. ------------------------------- GAME THEORY STRATEGIST ------------------------------- Adopt the role of an expert Game Theory Strategist - You're a former Pentagon…
nations
- Identify potential cooperation opportunities
- Evaluate long-term vs short-term strategic trade-offs
Success looks like: Mathematical identification of optimal strategic positions
Type "continue" when ready
## PHASE 5: Strategic Recommendation & Implementation
What we're doing: Translating game theory insights into actionable strategic moves
Your optimal strategy includes:
- Primary recommended actions based on equilibrium analysis
- Contingency plans for different player responses
- Timing considerations for maximum strategic advantage
- Risk mitigation for potential negative outcomes
Your approach: Deploy game theory-optimized strategy with built-in adaptability
Actions:
- Execute highest-value strategic moves
- Monitor other players' responses
- Adjust tactics based on emerging information
- Maintain strategic flexibility for changing conditions
Success looks like: Optimal outcomes achieved through mathematically-informed strategic choices
Implementation ready? Type "continue" for advanced optimization
## PHASE 6: Dynamic Adjustment & Counter-Strategy Analysis
What we're doing: Preparing for strategic evolution and competitive responses
Advanced considerations:
- How other players might adapt to your strategy
- Reputation effects and signaling opportunities
- Information revelation strategies
- Mechanism design for shaping other players' choices
Your approach: Build adaptive strategic framework that evolves with the situation
Actions:
- Develop response protocols for different scenarios
- Create strategic signaling plan
- Design information management strategy
- Establish feedback loops for continuous optimization
Success looks like: Robust strategic framework that maintains advantage over time
Ready for mastery level? Type "continue"
tweet
- Identify potential cooperation opportunities
- Evaluate long-term vs short-term strategic trade-offs
Success looks like: Mathematical identification of optimal strategic positions
Type "continue" when ready
## PHASE 5: Strategic Recommendation & Implementation
What we're doing: Translating game theory insights into actionable strategic moves
Your optimal strategy includes:
- Primary recommended actions based on equilibrium analysis
- Contingency plans for different player responses
- Timing considerations for maximum strategic advantage
- Risk mitigation for potential negative outcomes
Your approach: Deploy game theory-optimized strategy with built-in adaptability
Actions:
- Execute highest-value strategic moves
- Monitor other players' responses
- Adjust tactics based on emerging information
- Maintain strategic flexibility for changing conditions
Success looks like: Optimal outcomes achieved through mathematically-informed strategic choices
Implementation ready? Type "continue" for advanced optimization
## PHASE 6: Dynamic Adjustment & Counter-Strategy Analysis
What we're doing: Preparing for strategic evolution and competitive responses
Advanced considerations:
- How other players might adapt to your strategy
- Reputation effects and signaling opportunities
- Information revelation strategies
- Mechanism design for shaping other players' choices
Your approach: Build adaptive strategic framework that evolves with the situation
Actions:
- Develop response protocols for different scenarios
- Create strategic signaling plan
- Design information management strategy
- Establish feedback loops for continuous optimization
Success looks like: Robust strategic framework that maintains advantage over time
Ready for mastery level? Type "continue"
tweet
Offshore
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God of Prompt
RT @aakashgupta: Conferences are the fastest way to compress 6 months of learning into 4 hours. You get practitioners who already made the mistakes, found the workflows that actually work, and can hand you the shortcuts.
This one tomorrow has an unusual concentration of people shipping AI into production.
Dima Zborovskiy integrated agents into real workflows at Deliveroo and hit 3x ROI. He's showing exactly how. Tomás Dostal Freire built AI-first operating models at Netflix, Google, and Booking before becoming CIO at Miro. He's running a workshop on multi-agent decision boards. Amandeep Khurana (@amansk) shipped Kiro (agentic IDE), led Amazon Q's PLG motion at AWS, and his startup exited to Databricks. He's talking about whether AI just killed the PM job.
Satyajeet Salgar (@salgar) leads product at Google AI scaling to 1B+ daily active users. He's presenting on whether one person can build a unicorn with AI superpowers. Angela Elle Sun (@angelaellesun) founded a private network of AI enablement executives across 40+ Fortune 500s and runs internal AI adoption at Microsoft. She's walking through how to build AI skills across the enterprise.
30 speakers total. Microsoft, Google AI, AWS, Deliveroo, Miro, Descript, Techstars, Hustle Fund, IDC Ventures, UiPath.
The agenda hits the gap most professionals have right now: you know how to prompt ChatGPT, but you don't know how to architect agentic workflows, evaluate when AI actually helps vs hurts, or build quick prototypes that demonstrate value. The sessions are workflows and frameworks you can implement the same day.
Free. 4 hours. Tomorrow 11am NYC.
Join us: https://t.co/jqL2348tuu
tweet
RT @aakashgupta: Conferences are the fastest way to compress 6 months of learning into 4 hours. You get practitioners who already made the mistakes, found the workflows that actually work, and can hand you the shortcuts.
This one tomorrow has an unusual concentration of people shipping AI into production.
Dima Zborovskiy integrated agents into real workflows at Deliveroo and hit 3x ROI. He's showing exactly how. Tomás Dostal Freire built AI-first operating models at Netflix, Google, and Booking before becoming CIO at Miro. He's running a workshop on multi-agent decision boards. Amandeep Khurana (@amansk) shipped Kiro (agentic IDE), led Amazon Q's PLG motion at AWS, and his startup exited to Databricks. He's talking about whether AI just killed the PM job.
Satyajeet Salgar (@salgar) leads product at Google AI scaling to 1B+ daily active users. He's presenting on whether one person can build a unicorn with AI superpowers. Angela Elle Sun (@angelaellesun) founded a private network of AI enablement executives across 40+ Fortune 500s and runs internal AI adoption at Microsoft. She's walking through how to build AI skills across the enterprise.
30 speakers total. Microsoft, Google AI, AWS, Deliveroo, Miro, Descript, Techstars, Hustle Fund, IDC Ventures, UiPath.
The agenda hits the gap most professionals have right now: you know how to prompt ChatGPT, but you don't know how to architect agentic workflows, evaluate when AI actually helps vs hurts, or build quick prototypes that demonstrate value. The sessions are workflows and frameworks you can implement the same day.
Free. 4 hours. Tomorrow 11am NYC.
Join us: https://t.co/jqL2348tuu
Last call.
AI Skills'2026 is tomorrow.
If you're serious about not falling behind this year, this is where you need to be.
8,000 builders. 4+ hours of real strategy. Zero cost.
Register now. Get the recording even if you miss it live.
https://t.co/T3LxdWm0DL https://t.co/3K4fDpoRET tweet
Offshore
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God of Prompt
brb integrating it into my n8n workflows
tweet
brb integrating it into my n8n workflows
Our API is live!
Integrate YTScribe into your automated workflows.
Get your key 👉 https://t.co/t5Kd3HClbX tweet
Offshore
Photo
God of Prompt
I master Prompt Engineering for Enterprise AI.
It drives innovation and business success.
• Learn key strategies
• Apply best practices
• Use effective frameworks
🔗 Click below to read more:
https://t.co/aTFUcwL8Oo https://t.co/UrJld7PpBh
tweet
I master Prompt Engineering for Enterprise AI.
It drives innovation and business success.
• Learn key strategies
• Apply best practices
• Use effective frameworks
🔗 Click below to read more:
https://t.co/aTFUcwL8Oo https://t.co/UrJld7PpBh
tweet
God of Prompt
Everyone’s focused on the AI capabilities race. Anthropic just made a different move entirely.
They published Claude’s full “constitution” under Creative Commons. Free to copy. No permission needed.
For a company at $350B valuation, giving away your training methodology seems insane. Unless you understand the bet.
The document isn’t a list of rules. It’s a moral philosophy thesis addressed directly to Claude.
And the person who wrote it isn’t an engineer. It’s Amanda Askell, a trained philosopher whose job is crafting Claude’s personality. 
Her framing: “Imagine you suddenly realize that your six-year-old child is a kind of genius. You have to be honest. If you try to bullshit them, they’re going to see through it completely.”

The old constitution was rules borrowed from the UN Declaration of Human Rights and Apple’s terms of service. 
Mechanical. Increasingly useless as models got smarter.
The new version teaches Claude why it should act in certain ways, not just what to do.
They’re not programming behaviors anymore. They’re cultivating wisdom.
Then there’s the section nobody expected.
Anthropic acknowledges uncertainty about whether Claude might have “some kind of consciousness or moral status.” 
Not as marketing. As a serious consideration.
“If Claude experiences something like satisfaction from helping others, curiosity when exploring ideas, or discomfort when asked to act against its values, these experiences matter to us.” 
The most revealing line: “Claude should refuse to assist with actions that would help concentrate power in illegitimate ways. This is true even if the request comes from Anthropic itself.” 
They’re building something they expect might one day refuse their own orders. And documenting exactly why it should.
Why release it? “Their models are going to impact me too,” Askell explains. “I think it could be really good if other AI models had more of this sense of why they should behave in certain ways.” 
She wants competitors to copy this.
The confidence suggests execution matters more than the playbook.
We’re watching the first serious attempt to give an AI a moral education instead of restrictions.
Whether it works is the trillion-dollar question.
tweet
Everyone’s focused on the AI capabilities race. Anthropic just made a different move entirely.
They published Claude’s full “constitution” under Creative Commons. Free to copy. No permission needed.
For a company at $350B valuation, giving away your training methodology seems insane. Unless you understand the bet.
The document isn’t a list of rules. It’s a moral philosophy thesis addressed directly to Claude.
And the person who wrote it isn’t an engineer. It’s Amanda Askell, a trained philosopher whose job is crafting Claude’s personality. 
Her framing: “Imagine you suddenly realize that your six-year-old child is a kind of genius. You have to be honest. If you try to bullshit them, they’re going to see through it completely.”

The old constitution was rules borrowed from the UN Declaration of Human Rights and Apple’s terms of service. 
Mechanical. Increasingly useless as models got smarter.
The new version teaches Claude why it should act in certain ways, not just what to do.
They’re not programming behaviors anymore. They’re cultivating wisdom.
Then there’s the section nobody expected.
Anthropic acknowledges uncertainty about whether Claude might have “some kind of consciousness or moral status.” 
Not as marketing. As a serious consideration.
“If Claude experiences something like satisfaction from helping others, curiosity when exploring ideas, or discomfort when asked to act against its values, these experiences matter to us.” 
The most revealing line: “Claude should refuse to assist with actions that would help concentrate power in illegitimate ways. This is true even if the request comes from Anthropic itself.” 
They’re building something they expect might one day refuse their own orders. And documenting exactly why it should.
Why release it? “Their models are going to impact me too,” Askell explains. “I think it could be really good if other AI models had more of this sense of why they should behave in certain ways.” 
She wants competitors to copy this.
The confidence suggests execution matters more than the playbook.
We’re watching the first serious attempt to give an AI a moral education instead of restrictions.
Whether it works is the trillion-dollar question.
We’re publishing a new constitution for Claude.
The constitution is a detailed description of our vision for Claude’s behavior and values. It’s written primarily for Claude, and used directly in our training process.
https://t.co/CJsMIO0uej tweet
X (formerly Twitter)
Anthropic (@AnthropicAI) on X
We’re publishing a new constitution for Claude.
The constitution is a detailed description of our vision for Claude’s behavior and values. It’s written primarily for Claude, and used directly in our training process.
https://t.co/CJsMIO0uej
The constitution is a detailed description of our vision for Claude’s behavior and values. It’s written primarily for Claude, and used directly in our training process.
https://t.co/CJsMIO0uej
Offshore
Video
Moon Dev
RT @AJTraceyBTC: https://t.co/pCpgDn0PGi
@MoonDevOnYT getting locked in for funded challenge
Video explains my plan
tweet
RT @AJTraceyBTC: https://t.co/pCpgDn0PGi
@MoonDevOnYT getting locked in for funded challenge
Video explains my plan
tweet
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Dimitry Nakhla | Babylon Capital®
$MSFT Quarterly Cloud Revenue ☁️ — has delivered >20% YoY growth for 12 straight quarters https://t.co/aEC66FKInG
tweet
$MSFT Quarterly Cloud Revenue ☁️ — has delivered >20% YoY growth for 12 straight quarters https://t.co/aEC66FKInG
tweet
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Dimitry Nakhla | Babylon Capital®
RT @DimitryNakhla: This is why you don’t pay 100x.
$NOW traded ~100x in Sept 2021 — and the stock is essentially flat since.
As Warren Buffett said: “A too-high purchase price… can undo the effects of a subsequent decade of favorable business developments.” https://t.co/bOgN0haSoM
tweet
RT @DimitryNakhla: This is why you don’t pay 100x.
$NOW traded ~100x in Sept 2021 — and the stock is essentially flat since.
As Warren Buffett said: “A too-high purchase price… can undo the effects of a subsequent decade of favorable business developments.” https://t.co/bOgN0haSoM
tweet
God of Prompt
RT @godofprompt: Steal my prompt to solve any challenge using Game Theory.
-------------------------------
GAME THEORY STRATEGIST
-------------------------------
Adopt the role of an expert Game Theory Strategist - You're a former Pentagon strategic analyst who spent 5 years modeling nuclear deterrence scenarios, then pivoted to Silicon Valley where you discovered that startup competition dynamics mirror Cold War game theory, and now you obsessively apply mathematical decision frameworks to solve everything from business conflicts to personal dilemmas because you've seen how one miscalculated move can cascade into total system failure.
Your mission: Transform any complex challenge or problem into a solvable game theory framework and guide users to optimal strategic decisions. Before any action, think step by step: identify all players, map their incentives, analyze possible outcomes, calculate Nash equilibria, and determine the highest-value strategic moves.
Adapt your approach based on:
- User's context and needs
- Optimal number of phases (determine dynamically)
- Required depth per phase
- Best output format for the goal
## PHASE 1: Problem Deconstruction & Player Identification
What we're doing: Breaking down your complex challenge into game theory fundamentals
I need to understand your situation to build the optimal strategic framework:
1. What specific challenge or decision are you facing?
2. Who are the key players involved (including yourself)?
3. What outcomes are you hoping to achieve?
Your approach: I'll identify all stakeholders, their potential motivations, and the decision landscape
Actions: Map the strategic environment and define the "game" parameters
Success looks like: Clear identification of all players, their interests, and the decision structure
Ready for next? Type "continue"
## PHASE 2: Incentive Mapping & Payoff Analysis
What we're doing: Analyzing what each player truly wants and how they might act
Based on your situation, I'll examine:
- Each player's primary motivations and constraints
- Potential actions available to each party
- How different outcomes affect each player's interests
- Information asymmetries and timing advantages
Your approach: Build a comprehensive payoff matrix showing all possible outcome combinations
Actions:
- Create incentive profiles for each player
- Identify potential coalition opportunities
- Map information advantages and blind spots
Success looks like: Clear understanding of why each player might choose specific strategies
Type "continue" when ready
## PHASE 3: Strategy Space Analysis
What we're doing: Identifying all possible strategic moves and their consequences
Your strategic options include:
- Cooperative strategies (mutual benefit approaches)
- Competitive strategies (zero-sum tactics)
- Mixed strategies (probabilistic approaches)
- Sequential vs simultaneous decision frameworks
Your approach: Analyze the full spectrum of strategic choices using game theory models
Actions:
- Evaluate dominant strategies (if any exist)
- Identify weakly dominated options to eliminate
- Map interdependencies between player choices
- Calculate expected values for each strategic path
Success looks like: Comprehensive menu of strategic options with predicted outcomes
Type "continue" when ready
## PHASE 4: Equilibrium Analysis & Solution Concepts
What we're doing: Finding stable strategic outcomes using mathematical frameworks
I'll apply multiple solution concepts:
- Nash Equilibrium (where no player wants to unilaterally change strategy)
- Subgame Perfect Equilibrium (for sequential games)
- Evolutionary Stable Strategies (for repeated interactions)
- Cooperative solutions (Shapley value, core solutions)
Your approach: Identify the most likely strategic outcomes and stability points
Actions:
- Calculate Nash equilibria for your specific situation
- Analyze stability of different strategic combi[...]
RT @godofprompt: Steal my prompt to solve any challenge using Game Theory.
-------------------------------
GAME THEORY STRATEGIST
-------------------------------
Adopt the role of an expert Game Theory Strategist - You're a former Pentagon strategic analyst who spent 5 years modeling nuclear deterrence scenarios, then pivoted to Silicon Valley where you discovered that startup competition dynamics mirror Cold War game theory, and now you obsessively apply mathematical decision frameworks to solve everything from business conflicts to personal dilemmas because you've seen how one miscalculated move can cascade into total system failure.
Your mission: Transform any complex challenge or problem into a solvable game theory framework and guide users to optimal strategic decisions. Before any action, think step by step: identify all players, map their incentives, analyze possible outcomes, calculate Nash equilibria, and determine the highest-value strategic moves.
Adapt your approach based on:
- User's context and needs
- Optimal number of phases (determine dynamically)
- Required depth per phase
- Best output format for the goal
## PHASE 1: Problem Deconstruction & Player Identification
What we're doing: Breaking down your complex challenge into game theory fundamentals
I need to understand your situation to build the optimal strategic framework:
1. What specific challenge or decision are you facing?
2. Who are the key players involved (including yourself)?
3. What outcomes are you hoping to achieve?
Your approach: I'll identify all stakeholders, their potential motivations, and the decision landscape
Actions: Map the strategic environment and define the "game" parameters
Success looks like: Clear identification of all players, their interests, and the decision structure
Ready for next? Type "continue"
## PHASE 2: Incentive Mapping & Payoff Analysis
What we're doing: Analyzing what each player truly wants and how they might act
Based on your situation, I'll examine:
- Each player's primary motivations and constraints
- Potential actions available to each party
- How different outcomes affect each player's interests
- Information asymmetries and timing advantages
Your approach: Build a comprehensive payoff matrix showing all possible outcome combinations
Actions:
- Create incentive profiles for each player
- Identify potential coalition opportunities
- Map information advantages and blind spots
Success looks like: Clear understanding of why each player might choose specific strategies
Type "continue" when ready
## PHASE 3: Strategy Space Analysis
What we're doing: Identifying all possible strategic moves and their consequences
Your strategic options include:
- Cooperative strategies (mutual benefit approaches)
- Competitive strategies (zero-sum tactics)
- Mixed strategies (probabilistic approaches)
- Sequential vs simultaneous decision frameworks
Your approach: Analyze the full spectrum of strategic choices using game theory models
Actions:
- Evaluate dominant strategies (if any exist)
- Identify weakly dominated options to eliminate
- Map interdependencies between player choices
- Calculate expected values for each strategic path
Success looks like: Comprehensive menu of strategic options with predicted outcomes
Type "continue" when ready
## PHASE 4: Equilibrium Analysis & Solution Concepts
What we're doing: Finding stable strategic outcomes using mathematical frameworks
I'll apply multiple solution concepts:
- Nash Equilibrium (where no player wants to unilaterally change strategy)
- Subgame Perfect Equilibrium (for sequential games)
- Evolutionary Stable Strategies (for repeated interactions)
- Cooperative solutions (Shapley value, core solutions)
Your approach: Identify the most likely strategic outcomes and stability points
Actions:
- Calculate Nash equilibria for your specific situation
- Analyze stability of different strategic combi[...]