I wrote a practical example of applying the introduccion of a method that is mentioned here.
I’m developing an app that helps define and show correlations between personal missions, visions, objectives, routines and moments. And I want to study its scope with a focus on people who need more substantial improvements: young people in rehabilitation.
I would like to help analyzing the potential flaws in this method and perhaps finding potential coworker.
Step 1: Define Your Extreme Missions
What goals do you have?
Get clean from drugs
Finish high school
Repair relationship with mom
Write your objective with more benefits: User: “Getting clean from drugs—because everything else depends on it. Evidence: Every time I use, I mess up school and hurt my mom. When I was clean for 2 months, I got better grades and we talked more.”
Write your most difficult objective: User: “Getting clean from drugs—I’ve tried 3 times and failed. Evidence: I always relapse when stressed, and withdrawal makes me feel terrible for weeks.”
Establishing Reference Points:
Most Benefits Goal: Getting clean from drugs = 100% benefit reference
Most Difficult Goal: Getting clean from drugs = 100% difficulty reference
Step 2: Analyze Each Extreme Mission
Deep Analysis of Goal: “Getting Clean from Drugs” (Reference: 100% benefit, 100% difficulty)
1. Internal vs External Change Analysis
For your most difficult goal (getting clean), do you need more internal or environment change? Evidence?
User: “Both, but probably more environmental. Evidence: I can stay clean when I’m away from my usual friends and places, but when I go back to my neighborhood, I relapse within days. Also, I have no clean friends to hang out with.”
Follow-up: What percentage internal vs external? Evidence?
User: “Maybe 40% internal, 60% external. Evidence: Internal—I need to learn coping skills for stress and cravings. External—I need new friends, new places to spend time, maybe even move neighborhoods. My dealer lives two blocks away.”
2. Scope Analysis: Operational vs Emotional
For getting clean, do you need more elemental or emotional dedication? Evidence?
User: “Definitely emotional. Evidence: I know what to do physically—go to meetings, avoid triggers, take care of my body. But emotionally I feel empty without drugs, and I use them to numb pain from my dad leaving when I was 12.”
3. Scope Analysis: Emotional vs Informational
For getting clean, do you need more emotional or informational support? Evidence?
User: “More emotional. Evidence: I already know drugs are bad, I know the risks, I’ve read about addiction. But when I feel depressed or anxious, all that knowledge goes out the window. I need to learn how to feel my emotions without running away.”
4. Scope Analysis: Informational vs Social
For getting clean, do you need more informational or social support? Evidence?
User: “Social. Evidence: I have plenty of information about recovery—I’ve been to treatment twice. But I don’t have anyone to call when I’m craving. All my friends use drugs. I need people who understand what I’m going through.”
Analysis Results:
Impact Score: 100% (Much higher than reference goal)
Benefit: Extremely high (health, relationships, future opportunities)
Risk: High (withdrawal, social isolation, identity crisis)
Evidence: “When clean, everything improves. When using, everything falls apart.”
Entusiastic/Funny 30% (pleasurable activities to replace)
Researcher/Analyst 2% (requires long-term planning for recovery)
Strategist/Tactician 3% (day-to-day and keyMetas coping skills needed)
Empatetic/Altruistic 10% (Maybe trousseau to people can help me distract myself)
Negociator/Cooperator 15% (wants to help others, group, therapist in recovery eventually)
Implementation Hierarchy Integration:
Level 1: These percentages establish base latent value vectors for extreme goals ✅
Level 2: Minor goals will inherit proportional values from these base calculations 🔄
Level 3: Daily routines/tasks will correlate with specific latent values (e.g., “Go to NA meeting” connects with 65% Collaboration value) 📋
Level 4: “Life Possibilities Graph” will track how these latent values fluctuate over time for predictive insights 🔮
Step 3: Impact—Compare Other Goals Using References
Now that we have established “Getting clean from drugs” as 100% benefit and 100% difficulty, let’s compare other goals:
Goal: “Finish High School”
Compared to getting clean (100% benefit), how much benefit does finishing school provide? Evidence?
User: “Maybe 60% benefit. Evidence: School is important for jobs, but if I’m still using drugs, I’ll mess up anyway. When I was clean, school felt manageable and meaningful. When using, I don’t care about graduation.”
Compared to getting clean (100% difficulty), how difficult is finishing school? Evidence?
User: “About 40% difficulty. Evidence: I can do the work when I show up, and teachers want to help me. The hard part is just attending regularly and not giving up when I feel behind.”
Analysis Results:
Benefit: 60% (relative to getting clean)
Difficulty: 40% (relative to getting clean)
Benefit/Difficulty Ratio: 1.5 (better ratio than getting clean)
Goal: “Repair Relationship with Mom”
Compared to getting clean (100% benefit), how much benefit does repairing relationship with mom provide? Evidence?
User: “70% benefit. Evidence: Having her support would help with everything—she could help with school, give me a safe place to stay, and she believes in me. But I can’t truly repair it while I’m still lying about drug use.”
Compared to getting clean (100% difficulty), how difficult is repairing relationship with mom? Evidence?
User: “30% difficulty. Evidence: She still loves me and wants to help. I just need to be honest, consistent, and show her I’m changing. The hard part is earning back trust, but she’s already willing to talk.”
Analysis Results:
Benefit: 70% (relative to getting clean)
Difficulty: 30% (relative to getting clean)
Benefit/Difficulty Ratio: 2.3 (much better ratio than getting clean)
Step 4: Strategic Insights—All Goals Combined
Goal Comparison Matrix:
Goal
Benefit %
Difficulty %
Ratio
Strategic Insight
Get Clean
100%
100%
1.0
Highest impact but hardest—requires environmental change
Repair Mom Relationship
70%
30%
2.3
Best ratio—focus here first for momentum
Finish School
60%
40%
1.5
Medium priority—easier when other goals progress
Recommended Strategy Based on Analysis:
START with “Repair Mom Relationship” (highest benefit/difficulty ratio)
Provides support system needed for getting clean
Builds confidence and momentum
Evidence: “Having her support would help with everything”
Use mom’s support to tackle “Getting Clean”
Address 60% external factors first (environment, social support)
Mom can provide safe environment and accountability
Evidence: “she could give me a safe place to stay”
“Finish School” becomes easier when the other two progress
Evidence: “When I was clean, school felt manageable and meaningful”
Key Insight from Comparative Analysis:
The user initially thought getting clean was the foundation for everything else, but the benefit/difficulty analysis reveals that repairing the relationship with mom might be the actual foundation—it has the best ratio and provides the environmental support needed to get clean successfully.
Evidence-Based Probability Estimate:
Success Probability: 35% (higher than past attempts due to environmental focus)
Previous attempts failed because: Too much focus on willpower (internal) and not enough on changing environment and social connections.
Why this approach might work better: Addresses the 60% external factors that were previously ignored.
Comparison Questions for Validation:
Does this analysis match your lived experience? User: “Yes—I always focused on trying to be stronger inside, but never changed my environment. That’s why I kept failing.”
What would increase your probability of success? User: “Having clean friends and moving away from my neighborhood. Maybe getting a job in a different part of town.”
What’s your biggest fear about recovery? User: “Being lonely and boring. All my fun memories involve drugs. I don’t know who I am without them.”
Dynamic strategy adjustment based on accumulated evidence
Example: Detect stress patterns that predict relapse probability
Results
Automatically calculates latent values based on user responses (as we see “Employee” 26.1% is the highest for this goal “work with her”)
Shows specific proportions for each latent value needed for the goal (Altruistic 11.7%, Strategic 4.1%, etc.)
Have the “Life Possibilities Chart” for temporal progress tracking
Analysis Hierarchy:
Level 1: Extreme Goals (yet implemented)
Establish references 100% benefit/difficulty
Generate base latent value vectors
Internal/external division for each goal
Level 2: Smaller Goals (next step)
Compare as % of goals extreme
Heredan proportions of latent values of the target goals
Automatic calculation of benefit/difficulty ratio
Level 3: Routines & Tasks (future implementation)
Daily/weekly micro-tracking
Correlation with latent values of higher goals
Automatic detection of factors that most help/hinder
Level 4: Predictive Analysis (final objective)
Identification of patrons in “Life Possibilities”
Suggestions based on detected extreme factors
Dynamic adjustment of strategies according to accumulated evidence
And thus, rebuild personas to adapt them to the world of overwhelming information.
Conclusions
With that introduction, I’d like to find people interested in setting personal goals and analyzing moments using information theory and know if I can use it as a good first step to create a personal planner for users to define goals using information theory, which I’m currently calling: keyMetas.
What I’ve done so far:
A moment analysis apk that analyze moments that I’m adapting to analyze goals.
Latent value model with its informational and evolutionary basis
Scientific study model
A printed paper model (with a design cooworker)
A graphic design thesis at the University of La Plata to disseminate the method. (of a cooworker)
A postgraduate degree in neuroscience, with a thesis defense that received top marks in motivation and satisfaction human factors.
I’ve been applying an evolution of this method to myself for eleven years in sheets.
Four year study of information systems to develops this method.
With this foundation, we could create scabilizemodels to prioritize:
Visions,
missions,
values,
goals,
routines,
priority factors at a given moment.
Next steps:
Launch apk on Play Store
A new model printed in paper.
Clinical tests and supervision
Each part of the project will be sent separately: latent value model (informational and evolutionary basis), scientific study model, open-source app on GitHub with theoretical framework and scoring formulas.
If we can educate AIs, why not apply that education to people? - A Simulation with Claude
I wrote a practical example of applying the introduccion of a method that is mentioned here.
I’m developing an app that helps define and show correlations between personal missions, visions, objectives, routines and moments. And I want to study its scope with a focus on people who need more substantial improvements: young people in rehabilitation.
I would like to help analyzing the potential flaws in this method and perhaps finding potential coworker.
Step 1: Define Your Extreme Missions
What goals do you have?
Get clean from drugs
Finish high school
Repair relationship with mom
Write your objective with more benefits: User: “Getting clean from drugs—because everything else depends on it. Evidence: Every time I use, I mess up school and hurt my mom. When I was clean for 2 months, I got better grades and we talked more.”
Write your most difficult objective: User: “Getting clean from drugs—I’ve tried 3 times and failed. Evidence: I always relapse when stressed, and withdrawal makes me feel terrible for weeks.”
Establishing Reference Points:
Most Benefits Goal: Getting clean from drugs = 100% benefit reference
Most Difficult Goal: Getting clean from drugs = 100% difficulty reference
Step 2: Analyze Each Extreme Mission
Deep Analysis of Goal: “Getting Clean from Drugs” (Reference: 100% benefit, 100% difficulty)
1. Internal vs External Change Analysis
For your most difficult goal (getting clean), do you need more internal or environment change? Evidence?
User: “Both, but probably more environmental. Evidence: I can stay clean when I’m away from my usual friends and places, but when I go back to my neighborhood, I relapse within days. Also, I have no clean friends to hang out with.”
Follow-up: What percentage internal vs external? Evidence?
User: “Maybe 40% internal, 60% external. Evidence: Internal—I need to learn coping skills for stress and cravings. External—I need new friends, new places to spend time, maybe even move neighborhoods. My dealer lives two blocks away.”
2. Scope Analysis: Operational vs Emotional
For getting clean, do you need more elemental or emotional dedication? Evidence?
User: “Definitely emotional. Evidence: I know what to do physically—go to meetings, avoid triggers, take care of my body. But emotionally I feel empty without drugs, and I use them to numb pain from my dad leaving when I was 12.”
3. Scope Analysis: Emotional vs Informational
For getting clean, do you need more emotional or informational support? Evidence?
User: “More emotional. Evidence: I already know drugs are bad, I know the risks, I’ve read about addiction. But when I feel depressed or anxious, all that knowledge goes out the window. I need to learn how to feel my emotions without running away.”
4. Scope Analysis: Informational vs Social
For getting clean, do you need more informational or social support? Evidence?
User: “Social. Evidence: I have plenty of information about recovery—I’ve been to treatment twice. But I don’t have anyone to call when I’m craving. All my friends use drugs. I need people who understand what I’m going through.”
Analysis Results:
Impact Score: 100% (Much higher than reference goal)
Benefit: Extremely high (health, relationships, future opportunities)
Risk: High (withdrawal, social isolation, identity crisis)
Evidence: “When clean, everything improves. When using, everything falls apart.”
Direction: 40% Internal / 60% External
Internal needs: Coping skills, emotional regulation, trauma processing
External needs: Environment change, new social network, support systems
Evidence: Environmental triggers are stronger than internal willpower
Scope Breakdown:
Elemental: 20% (Physical detox, basic health needs)
Emotional: 50% (Trauma work, learning to feel emotions, identity work)
Informational: 5% (Already has knowledge about addiction/recovery)
Social: 25% (New friend group, support meetings, family repair)
Latent Values Inferred (Specific Proportions for This Goal):
Grateful/Guardian
8% (Food and supplements that can help with anxiety and stress)
Non-attached/Determined
12% (physical exercises that can help)
Self-Aware/Versatile
20% (Meditation, mindfulness)
Entusiastic/Funny
30% (pleasurable activities to replace)
Researcher/Analyst
2% (requires long-term planning for recovery)
Strategist/Tactician
3% (day-to-day and keyMetas coping skills needed)
Empatetic/Altruistic
10% (Maybe trousseau to people can help me distract myself)
Negociator/Cooperator
15% (wants to help others, group, therapist in recovery eventually)
Implementation Hierarchy Integration:
Level 1: These percentages establish base latent value vectors for extreme goals ✅
Level 2: Minor goals will inherit proportional values from these base calculations 🔄
Level 3: Daily routines/tasks will correlate with specific latent values (e.g., “Go to NA meeting” connects with 65% Collaboration value) 📋
Level 4: “Life Possibilities Graph” will track how these latent values fluctuate over time for predictive insights 🔮
Step 3: Impact—Compare Other Goals Using References
Now that we have established “Getting clean from drugs” as 100% benefit and 100% difficulty, let’s compare other goals:
Goal: “Finish High School”
Compared to getting clean (100% benefit), how much benefit does finishing school provide? Evidence?
User: “Maybe 60% benefit. Evidence: School is important for jobs, but if I’m still using drugs, I’ll mess up anyway. When I was clean, school felt manageable and meaningful. When using, I don’t care about graduation.”
Compared to getting clean (100% difficulty), how difficult is finishing school? Evidence?
User: “About 40% difficulty. Evidence: I can do the work when I show up, and teachers want to help me. The hard part is just attending regularly and not giving up when I feel behind.”
Analysis Results:
Benefit: 60% (relative to getting clean)
Difficulty: 40% (relative to getting clean)
Benefit/Difficulty Ratio: 1.5 (better ratio than getting clean)
Goal: “Repair Relationship with Mom”
Compared to getting clean (100% benefit), how much benefit does repairing relationship with mom provide? Evidence?
User: “70% benefit. Evidence: Having her support would help with everything—she could help with school, give me a safe place to stay, and she believes in me. But I can’t truly repair it while I’m still lying about drug use.”
Compared to getting clean (100% difficulty), how difficult is repairing relationship with mom? Evidence?
User: “30% difficulty. Evidence: She still loves me and wants to help. I just need to be honest, consistent, and show her I’m changing. The hard part is earning back trust, but she’s already willing to talk.”
Analysis Results:
Benefit: 70% (relative to getting clean)
Difficulty: 30% (relative to getting clean)
Benefit/Difficulty Ratio: 2.3 (much better ratio than getting clean)
Step 4: Strategic Insights—All Goals Combined
Goal Comparison Matrix:
Recommended Strategy Based on Analysis:
START with “Repair Mom Relationship” (highest benefit/difficulty ratio)
Provides support system needed for getting clean
Builds confidence and momentum
Evidence: “Having her support would help with everything”
Use mom’s support to tackle “Getting Clean”
Address 60% external factors first (environment, social support)
Mom can provide safe environment and accountability
Evidence: “she could give me a safe place to stay”
“Finish School” becomes easier when the other two progress
Evidence: “When I was clean, school felt manageable and meaningful”
Key Insight from Comparative Analysis:
The user initially thought getting clean was the foundation for everything else, but the benefit/difficulty analysis reveals that repairing the relationship with mom might be the actual foundation—it has the best ratio and provides the environmental support needed to get clean successfully.
Evidence-Based Probability Estimate:
Success Probability: 35% (higher than past attempts due to environmental focus)
Previous attempts failed because: Too much focus on willpower (internal) and not enough on changing environment and social connections.
Why this approach might work better: Addresses the 60% external factors that were previously ignored.
Comparison Questions for Validation:
Does this analysis match your lived experience? User: “Yes—I always focused on trying to be stronger inside, but never changed my environment. That’s why I kept failing.”
What would increase your probability of success? User: “Having clean friends and moving away from my neighborhood. Maybe getting a job in a different part of town.”
What’s your biggest fear about recovery? User: “Being lonely and boring. All my fun memories involve drugs. I don’t know who I am without them.”
KeyMetas System Architecture
Core Implementation Levels:
Level 1: Extreme Goals ✅ (Current Implementation)
Establish 100% benefit/difficulty reference points
Generate base latent value vectors with specific proportions
Calculate internal/external intervention ratios
Example: “Getting clean” produces Collaboration 65%, Autonomy 95%, etc.
Level 2: Minor Goals 🔄 (Next Development Phase)
Compare as percentages relative to extreme goals
Inherit proportional latent values from parent goals
Auto-calculate benefit/difficulty ratios
Example: “Finish school” inherits modified proportions from “Getting clean”
Level 3: Routines & Tasks 📋 (Future Implementation)
Daily/weekly micro-tracking connected to goal hierarchy
Correlate specific activities with latent values
Auto-detect factors that most help/hinder progress
Example: “Attend therapy” correlates with Connection/Love 85% value
Level 4: Predictive Analysis 🔮 (Advanced Features)
“Life Possibilities Graph” pattern recognition
Identify extreme factors in historical tracking
Dynamic strategy adjustment based on accumulated evidence
Example: Detect stress patterns that predict relapse probability
Results
Automatically calculates latent values based on user responses (as we see “Employee” 26.1% is the highest for this goal “work with her”)
Shows specific proportions for each latent value needed for the goal (Altruistic 11.7%, Strategic 4.1%, etc.)
Have the “Life Possibilities Chart” for temporal progress tracking
Analysis Hierarchy:
Level 1: Extreme Goals (yet implemented)
Establish references 100% benefit/difficulty
Generate base latent value vectors
Internal/external division for each goal
Level 2: Smaller Goals (next step)
Compare as % of goals extreme
Heredan proportions of latent values of the target goals
Automatic calculation of benefit/difficulty ratio
Level 3: Routines & Tasks (future implementation)
Daily/weekly micro-tracking
Correlation with latent values of higher goals
Automatic detection of factors that most help/hinder
Level 4: Predictive Analysis (final objective)
Identification of patrons in “Life Possibilities”
Suggestions based on detected extreme factors
Dynamic adjustment of strategies according to accumulated evidence
And thus, rebuild personas to adapt them to the world of overwhelming information.
Conclusions
With that introduction, I’d like to find people interested in setting personal goals and analyzing moments using information theory and know if I can use it as a good first step to create a personal planner for users to define goals using information theory, which I’m currently calling: keyMetas.
What I’ve done so far:
A moment analysis apk that analyze moments that I’m adapting to analyze goals.
Latent value model with its informational and evolutionary basis
Scientific study model
A printed paper model (with a design cooworker)
A graphic design thesis at the University of La Plata to disseminate the method. (of a cooworker)
A postgraduate degree in neuroscience, with a thesis defense that received top marks in motivation and satisfaction human factors.
I’ve been applying an evolution of this method to myself for eleven years in sheets.
Four year study of information systems to develops this method.
With this foundation, we could create scabilizemodels to prioritize:
Visions,
missions,
values,
goals,
routines,
priority factors at a given moment.
Next steps:
Launch apk on Play Store
A new model printed in paper.
Clinical tests and supervision
Each part of the project will be sent separately: latent value model (informational and evolutionary basis), scientific study model, open-source app on GitHub with theoretical framework and scoring formulas.