additions and changes continuing

PRODUCT-DEV-OS.md

@@ -2,7 +2,15 @@
 
 ## Overview
 
-This is a template that will be copied when a new product is to be created.  This template is to be used when an AI is involved because this document helps provide executable structure that an AI can understand to create the product and manage its production.  A change to the product would mean changing the executable structure, not the actual code or the product itself, because AI is the production layer and uses the executable structure layer to produce.  This template guides how to create the product, how to produce it, and improve it.  This process is not just for software products, but also for physical products, because increasingly, AI will assume control of physical production of products via automated test and assembly lines.
+This is a template that will be copied when a new product is to be created.  
+
+This template is to be used when an AI is involved because this document helps provide executable structure that an AI can understand to create the product and manage its production.  
+
+A change to the product would mean changing the executable structure, not the actual code or the product itself, because AI is the product development and production layer and uses the executable structure layer to produce.  
+
+This template guides how to create the product, how to produce it, and improve it.  This process is not just for software products, but also for physical products, because increasingly, AI will assume control of physical production of products via automated test and assembly lines.
+
+I organize the layers according to the 8 core functional areas of a business, [as defined here](https://eddiesoehnel.com/startup-roadmap/).
 
 ### Tools:
 
@@ -18,8 +26,8 @@ The most valuable stack is:
 
 ### 3-layer system
 
-1. Knowledge layer (specs/)   → what the system is supposed to do. The truth via highly structured executable knowledge that AI can understand.
+1. Knowledge layer (specs/)   → what the system is supposed to do. The truth via highly structured executable knowledge that AI can understand. Structure leads to intelligence.  Smarter AI models help, but if poorly structured, then failure.  Well structure knowledger layers can succeed even with average models. 
-2. Product layer (srv/) → takes the knowledge layer and executes it:  develop code, develop the product, produce the product.
+2. Product layer (tasks/ and srv/) → takes the knowledge layer and executes it:  develop code, develop the product, produce the product.
 3. Data layer (data/) → what the system observes, stores, and learns from based on production. The data validates reality, that leads to iterate above to improve.
 
 ### Structure For Git Repo
@@ -32,57 +40,60 @@ The most valuable stack is:
 - Use consistent headings
 - Keep sections predictable.  If every file has a predictable structure, AI navigation improves dramatically.
 
-### repo/
+#### repo/
 
 - README.md \ high level overview of project
 - CHANGELOG.md \
 - VERSION.md \ 
 - PROJECTRULESPROCESSES.md \ agent and human rules/processes
 
-### specs/
+##### specs/
 
 *The executable structure layer, organized by main function and in order*
 
-- agents.md \ Functionas more like a router, telling AI where to find stuff. And general rules.
+- agents.md \ Functionas more like a router, telling AI where to find stuff. General rules. Set up clear path where AI agents orchestrate other AI agents
-- build-plan.md \- sequences, tasks, modules, dependencies, components
 - decisions.md \ why we did what we did, why we chose A over B, etc.  Architecture Decision Records (ADR). provide context, decision, risks, consequences. Document using the [decision layer and biases layer](https://docs.google.com/document/d/1VjtP-jPn-wOpE8z5QSVOdk-pPxneyuDDM6z_a9OIpYY/edit?tab=t.0)
 - personas.md \ As AI may run sub-agents, this document defines the  personas for those sub-agents.
 
-#### 1_strategy_s
+###### 1_strategy_s
 
 - vision/concept validation/strategy/mission/goals/marketing/sales/distribution/goals/target customer/constraints/success metrics/.md \ use the **B2C framework**.
 
-#### 2_systems_s
+###### 2_systems_s
 
 - api-spec.md \- AI capabilities, focus for this project.
 - architecture.md \- infrastructure, platforms, code bases, tech stack, engineering design, environment \ the [long-term tech stack is here](https://docs.google.com/document/d/1BtcV4Lpv4E8vf5jMHcYmzw__U8ZN0ZCx0-1KTo0Z-1U/edit?tab=t.0)
 - data-model.md \- how the data flows through the product, where it ends up, how it is , structure, relationships, rules governing it, where stored
 - environments.md - multiple environments that exist - dev, staging, production
 - system.md \ map of how the knowledge layer connects to the code, how data flows, how AI should reason about the repo
+- ####### config/
+- - .env files, API's, feature flags, for both dev and production
  
-#### 3_product_development_s
+###### 3_product_development_s
 
 - user-flows/screen states/actions.md
 
-#### 4_finance_s
+###### 4_finance_s
 
-#### 5_production_logistics_s
+###### 5_production_logistics_s
 
-#### 6_marketing_s
+###### 6_marketing_s
 
-#### 7_sales-distribution_s
+###### 7_sales-distribution_s
 
-#### 8_support_s
+###### 8_support_s
  
-### tasks
+##### tasks
 
-*Task items by document with dates*
+*task/project items in separate documents* 
 
-### srv/
+date_build-plan.md \ sequences, tasks, modules, dependencies, components
+
+##### srv/
 
 *The production/execution layer for AI to execute on. Code is created in files.  Code is well documented and explains why the code exists, what it does, maintenance tips, gotchas if any.*
 
-#### digital 
+###### digital 
 
 *digital/software-based products/services*
 
@@ -94,55 +105,49 @@ The most valuable stack is:
 - utils/
 - routes/
 
-#### physical
+###### physical
 
 *physical-based products/services*
 
-### data/
+##### data-ops/
 
 *Data that is already a part of the system (ie.: CRM customer data) or which gets produced from the system. repo/ topline and docs/ are strategy, systems and product development are src/, data is all other functions, pulled from **B2C Framework**
 
-#### 1_strategy_d
+###### 1_strategy_d
 
 
-#### 2_systems_d
+###### 2_systems_d
 
 - json-db/
 - schemas/
 - runtime-exports/
- 
-#### 3_product_development_d
-
-
-#### 4_finance_d
-
-
-#### 5_production-logistics_d
-
-
-#### 6_marketing_d
-
-
-#### 7_sales-distribution_d
-
-
-#### 8_support_d
-
-### tests/
-
-*Run time feedback*
-- acceptance-tests.md \
-- qa-checklists.md \
-- dev-tests/
-
-### ops/
-
 - deployment.md \
 - monitoring.md \
 - maintenance.md \
 - backup.md \
 - security.md \
+ 
+###### 3_product_development_d
 
-### config/
 
-.env files, API's, feature flags, for both dev and production
+###### 4_finance_d
+
+
+###### 5_production-logistics_d
+
+
+###### 6_marketing_d
+
+
+###### 7_sales-distribution_d
+
+
+###### 8_support_d
+
+
+##### tests/
+
+*Run time feedback*
+- acceptance-tests.md \
+- qa-checklists.md \
+- dev-tests/

specs/build-plan.md

@@ -1 +0,0 @@
-sequences, tasks, modules, dependencies, components

specs/personas.md

@@ -1,6 +1,6 @@
 # Description
 
-As AI may run sub-agents, this document defines the  personas for those sub-agents.
+As AI may run sub-agents, this document defines the  personas for those sub-agents. Set up clear path where AI agents orchestrate other AI agents. This is where it is done. 
 
 # Sub-Agent Personas
 

tasks/_build-plan.md

@@ -0,0 +1,14 @@
+What specifically must be true when this is done? Define in terms of metrics (revenue, costs, use metrics, etc), user flows, user delight, the feeling achieved when this outcome is realized, what it allows, where it can lead, how it leverages.  
+
+What are the non-negotiables? (safety, cost, time, inputs)
+
+Sequences, tasks, modules, dependencies, components
+
+Vague input → mediocre AI output
+Precise constraints → high-quality execution
+
+Think in terms of outcomes - what you want to see when all is done.
+
+Break that outcome into components, dependencies, unknowns. You are converting the outcome, or problem, or rask or idea into machine-operable structure. 
+
+Turn messy reality of achieving outcomes into machine-readable objects, which are the documents and how they are structured throughout the Product Dev OS framework