What predicts a good day?
Here's 90 days of daily energy (1–10) plus sleep, HRV, RHR, training, and a 1-line meal note. Rank the inputs by how well they predicted my best 10 days vs. my worst 10 days.
AI for energy
You already know which days feel awful. AI helps you find out why — and what you can change.
What we’re actually working with
Energy is the subjective experience of recovery, glucose, sleep, hormones, and stress all at once. It's the most useful signal you can capture in 5 seconds a day.
Why doing this without a method fails
Most people describe their energy as 'random'. It almost never is. The pattern is there in the data you already collect.
The 3-Layer treatment
How the method handles energy
Layer 01
Research
Read what the literature actually says about the strongest modifiable inputs to subjective energy (sleep, training, light exposure, meals, social stress).
Layer 02
Ledger
Combine 90 days of a 1-line daily energy score with sleep, HRV, training, meals, and screen time. Let AI rank the inputs by predictive power.
Layer 03
Protocol
Test the top-ranked input over 4 weeks with a clean comparison. Decide whether to keep, drop, or refine it.
Three prompts you can use today
Paste any of these into the AI chat tool you already use. No setup.
Crash pattern
I crash around 3pm most days. Here's my morning routine, breakfast, lunch, training, and energy score for 30 days. Find the inputs that protect against the crash and the ones that worsen it.
Light and energy
Design a 4-week test of morning light exposure (10–20 min within an hour of waking). Use my current energy score as the baseline and define what a meaningful improvement looks like.
Common questions
Isn't 'energy' too subjective to analyse?+
On its own, yes. Combined with objective data, a daily 1–10 score becomes one of the most useful signals you can collect.
Do I need a wearable?+
Helpful, not required. A simple notebook with sleep duration, training, and an energy score works.
What if nothing predicts my energy?+
Then the answer is usually missing variables (light, hydration, social stress, hormones). AI can help you find them.
More on energy
Everything we’ve published that touches this topic — refreshed automatically as new entries ship.
From the blog
What ChatGPT is good and bad at for mental health support — an honest framework.
An honest framework for using ChatGPT for mental health support: what it is genuinely good at, where it is dangerous, and a four-line script to keep a thread safe. Not therapy. Not nothing.
Giving up one more nutrition tracking app.
Most people quit nutrition apps not because they lack discipline, but because the app asked the wrong question. Here is what to keep, what to delete, and the one document that replaces all of them.
The outreach engine that replaces cold pitching.
Replace Friday afternoon cold pitching with one back-office board where drafts, contacts and follow-ups live in the same row. The recipe — and the playbook PDF.
GLP-1 without the brand app
GLP-1 medications shift weight, glucose, energy, and side effects together. Use AI to keep one honest ledger across all four — without the brand app.
Personal longevity analytics, without the dashboard
What longevity analytics really tracks, the four signals that compound, and why the right interface is a long-context AI — not another dashboard.
The dual-lab interpretation pyramid
Stop choosing between conventional and functional medicine ranges. Read your labs through three lenses in order: clinical, functional, personal. The pyramid that prevents both panic and complacency.
Case studies
Enhanced Nutritional Insight for Individual Wellness
An individual leverages automated data flows to refine dietary choices and improve well-being.
Automated Health Data Flow for a Busy Executive
A streamlined system for health data collection and analysis improved decision-making for a demanding schedule.
Activity Trend Recognition for Personalized Energy Management
An individual leverages automated data synthesis and pattern identification to inform daily routine adjustments for sustained energy.
The reader who deleted the fifth nutrition app and kept the noticing
A busy parent stopped re-downloading food trackers, swapped them for a one-page ledger and a Sunday read with a free chat tool — and finally saw the pattern the apps had been hiding for two years.
Computer Vision Unlocks Deeper Nutrient Insights
A practitioner refines dietary recommendations by leveraging image analysis to quantify food intake with greater precision.
AI as a Mirror: Illuminating the Shape of Daily Habits for Better Sleep
A continuous glucose sensor and a reasoning chat tool revealed a 41-year-old’s specific sleep disruptors.
Glossary
AI Health Stack
A personal, tool-agnostic system that uses three free general-purpose AI chat tools as one coordinated health intelligence layer.
Protocol Layer (Layer 03)
The conversational planning layer. Translates research + patterns into a livable plan.
Evidence Hierarchy
A simple ranking (RCT > meta-analysis > observational > expert opinion > anecdote) used inside every AI prompt in the stack.
Personal AI
AI used by an individual for their own thinking — not as a product they pay for, but as a method they own.
Sunday Integration Hub
The weekly 20-minute ritual where the three layers merge — patterns meet evidence, evidence meets a plan.
Related topics
AI for Training Load
Use AI to read your weekly training data and your recovery markers together — and stop wrecking yourself by accident.
AI for Stress
Your HRV, sleep, and resting HR already record your stress. AI helps you read them — and design a response that actually fits your life.
AI for Longevity
Skip the guru subscriptions. Use AI to read the longevity literature, your own labs and data, and build a focused protocol that fits your life.
AI for Weight
Daily weight is mostly noise. AI helps you read the trend across months, separate water from fat, and stop reacting to the wrong signal.
Start with 10 free days.
The free 10-day email challenge teaches the same method on whatever data you already collect. No credit card.