LLM Reflections and Suggestions

Source: This page is based on docs/REFLECTIONS/LLM_REFLECTIONS.md

Last Updated: January 1, 2026

This document captures valuable insights, observations, and suggestions from LLM interactions regarding the project architecture and design.

Architecture Observations

High-Level Observations

Clear Separation of Concerns ("Define, Execute, Store"): The architecture is cleanly divided into three distinct but interconnected domains.
- Define (Workflow Builder): This is the "template" layer where the process structure, logic, content, and roles are defined.
- Execute (Sessions): This is the "runtime" layer, a live instance of the template, tracking real-time state and user progression.
- Store (Sheets): This is the "data" layer, capturing all user-generated data in a structured, reusable format.
Data-Binding is the Core of the System: The entire architecture hinges on the concept of binding an interactive element (Block) to a specific data location (Sheet + Column). This is the critical link that makes the system so powerful.
State-Driven, Declarative UI: Both the Session and Builder experiences rely on a pattern of fetching a complete server state and then calculating a derived view model on the client. This approach is robust, as the UI is always a direct reflection of the data.
Designed for Extensibility: The detailed guide on "How to Add a New Block" demonstrates that the system was built with modularity in mind. The process is well-defined and touches all three pillars.
Consistent and Modern Tech Stack: React Query for server state, Zustand for client state, React Flow for graphs, and AG-Grid for tables. This consistency simplifies development.

High-Level Suggestions

Introduce Workflow Versioning: The current Draft/Published model is a great start. Versioning (e.g., v1, v2) would allow you to edit a new draft while the previous version remains published and active.
Explore Bi-Directional Data Flow with Sheets: Currently, the data flow is primarily one-way: Sessions write data to Sheets. Consider creating mechanisms for Sheets to influence Sessions (triggers, dynamic updates).
Abstract the Data Binding Interface: As the system grows, you might find blocks with more complex data needs. Abstracting the data binding configuration could make it easier to build advanced blocks.
Create a Centralized Component Library/Storybook: Formally documenting reusable components would improve developer velocity, promote UI consistency, and serve as living documentation.

Impact and Philosophy of Eddy

The Practical & Business Impact

Democratization of Application Development: Empowering non-technical "domain experts" to build the tools they need. They understand the process intricacies better than anyone.
Transforming Tacit Knowledge into Explicit Assets: Eddy forces the codification of knowledge. The act of building a workflow transforms a fuzzy, implicit process into a tangible, version-controlled, and executable asset.
Creation of High-Integrity "Process Datasets": Because every input block is strictly bound to a sheet column, Eddy doesn't just manage a process; it generates a perfect dataset about the process as a natural byproduct.
Radical Transparency and Accountability: The Session Graph acts as a "map" for work. For any given session, anyone involved can see exactly where it is, who is responsible, and what comes next.

The Philosophical Implications

The Codification of Procedure and Trust: At its core, a business process is a set of agreements on how work should flow. Eddy takes these human agreements and translates them into a formal, logical system.
Redefining the "Expert": A tool like Eddy suggests a shift where the primary expert is the person with deep domain knowledge, not necessarily a developer. The value lies in knowing the process, not in knowing JavaScript.
Data as the Natural "Exhaust" of Work: The "Define, Execute, Store" model implies a philosophical shift. Data is the direct, unavoidable result of performing the work itself, not a separate chore done after the fact.
Shifting Cognitive Load from Orchestration to Execution: For a participant in a session, the system handles the complexity of "what's next?" and "who do I send this to?" This frees the human to focus entirely on the task at hand.

Strategic Feature Ideas

Building on the "Define, Execute, Store" model, the most powerful supporting features will be those that act as connective tissue between the pillars.

1. Governance & Scalability: The Component Library

Concept: A library of reusable workflow "components" (sub-workflows, common page patterns, pre-configured blocks) that can be shared across workflows.

Why it matters: As organizations build more workflows, they'll discover common patterns. A component library would:

Promote consistency across processes
Speed up workflow creation
Enable governance (approved components only)
Facilitate best practice sharing

2. Intelligence & Analytics: The Process Intelligence Hub

Concept: A dedicated analytics layer that provides insights into workflow performance, bottlenecks, and outcomes.

Why it matters: The data generated by sessions is incredibly valuable. Process intelligence would:

Identify bottlenecks automatically
Track cycle times and completion rates
Correlate outcomes with process paths
Enable data-driven process improvement

3. Connectivity & Integration: The Automation Engine

Concept: A system for triggering external actions based on workflow events, and for starting workflows based on external triggers.

Why it matters: Workflows don't exist in isolation. Integration would:

Connect Eddy to existing tools (Slack, email, CRM)
Enable automation of routine tasks
Create feedback loops with other systems
Extend Eddy's reach beyond its UI

4. Collaboration & Communication: Secure Guest Portals

Concept: A way to invite external users (clients, vendors) to participate in specific workflows without granting full workspace access.

Why it matters: Many processes involve external parties. Guest portals would:

Enable secure collaboration with outsiders
Maintain data isolation and security
Simplify onboarding for one-time participants
Expand Eddy's use cases significantly

Comparative Analysis: Eddy vs. Adjacent Tools

The Core Differentiator: Process as the Primary Entity

Most tools treat data as the primary entity, with process as an afterthought. Eddy inverts this: process is the primary entity, and data is the structured output.

Eddy vs. Airtable

Airtable: Database-first. You create tables, then figure out how to collect data.

Eddy: Process-first. You design the workflow, and the database is automatically structured to match.

Eddy's advantage: Better for complex, multi-step processes with roles and conditional logic.

Eddy vs. Notion

Notion: Document-first. Flexible but unstructured. Process is manual.

Eddy: Structured process with enforced rules and automatic progression.

Eddy's advantage: Ensures consistency, provides accountability, generates clean data.

Eddy vs. Google Forms

Google Forms: Single-step data collection. No process, no roles, no logic.

Eddy: Multi-step workflows with roles, conditional branching, and rich interactions.

Eddy's advantage: Can handle complex processes that Google Forms can't touch.

Eddy vs. Jira

Jira: Task-tracking focused. Process is implicit in ticket states.

Eddy: Explicit process modeling with visual graphs and enforced rules.

Eddy's advantage: More flexible, visual, and accessible to non-technical users.

The Long-Term Value of the 'Process Graph'

The workflow graph is not just a UI convenience. It's a formal representation of organizational knowledge.

Over time, an organization's collection of workflow graphs becomes:

A process library - Documentation of how things actually work
An onboarding tool - New employees can see processes visually
An improvement engine - Analytics reveal optimization opportunities
An institutional memory - Processes survive employee turnover
A compliance asset - Auditable record of procedures

This is the "fourth pillar" - Process Intelligence. The system evolves from just executing processes to understanding and improving them.

Security, Compliance, and Trust

As Eddy handles more critical processes, security and compliance become paramount.

Key Considerations

Audit Trails: Every action should be logged. Who did what, when, and why.
Version Control: Workflows should be versioned. Changes should be tracked and reversible.
Access Control: Fine-grained permissions. Who can view, edit, execute, and administer.
Data Retention: Policies for how long data is kept and when it's deleted.
Compliance Certifications: SOC 2, GDPR, HIPAA depending on target markets.
Encryption: At rest and in transit. For sensitive data fields.

Final Reflections: The Soul of the Machine

The Human-Computer Symbiosis

Eddy represents a form of human-computer symbiosis where:

Humans provide judgment, creativity, and domain expertise
Computers provide consistency, memory, and orchestration

The computer doesn't replace the human; it amplifies their capabilities by handling the "meta-work" of process management.

The Conceptual Gravity of the Core Model

The "Define, Execute, Store" model is powerful because it's:

Simple: Three concepts, clearly separated
Complete: Covers the entire lifecycle
Extensible: New features naturally fit into one of the three pillars
Intuitive: Maps to how people think about work

This conceptual clarity is a strategic asset. It makes the system easier to explain, easier to build on, and easier to use.

Eddy is a Game Engine

The game engine metaphor explained

What is Eddy?

Core concepts and philosophy

LLM Reflections

Eddy is a Game Engine

What is Eddy?

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