Draft
Refine preview into a diagnostic mirror
The local SME preview should feel like a useful business artifact, not an agency pitch. Next step: define trust-stack proof artifacts.
Lab notebook
Visible thinking, structured enough for future experiments.
Notes are static placeholders for now. They show how experiment evidence, decisions, and operating constraints should be organized before any live systems are added.
1. Notes
Current memos and decision fragments.
Draft
Active
Keep the lab umbrella reusable
Experiments must share data shape, gates, artifacts, and approval rules so future ideas can plug into the same operating system.
Principle
No automation until the manual signal is clean
The system should collect evidence before turning any workflow into outreach, tracking, or external automation.
2. Experiment Registry
Structured data driving the homepage cards.
01 Research
Local SME Digital Preview
Hypothesis
Personalized digital-presence previews will create written replies and price interest from execution-weak but digitally ambitious local premium SMEs.
02 Modeling
Beauty Audit Funnel
Hypothesis
A lightweight audit and preview funnel can drive reply rates and open a paid diagnostic offer without paid ads.
03 Research
AI Growth Systems
Hypothesis
Repeatable AI and automation workflows can reduce CAC and manual ops for small teams without increasing headcount.
3. Artifact Index
Static evidence objects waiting for real data.
CSV ->
Lead Funnel Dataset
Early outreach and reply data, structured for learning.
JSON ->
Experiment Registry
All experiments, hypotheses, status, and next gates.
MD ->
Decision Log
Immutable record of decisions and reasoning.
MD ->
Audit Mockup Structure
Preview architecture, sections, and scoring model.
MD ->
Outreach Rules
No outreach without Gary-Go. Ethical and compliant always.