headroom/docs/headroom-decision-log.md

Headroom - Complete Decision Log & Conversation Archive

Version: 1.0
Date: February 17, 2026
Participants: Santhosh J (Project Owner), AI Assistant (Design Partner)
Purpose: Comprehensive record of all discussions, decisions, considerations, and deferrals

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Table of Contents

1. Project Genesis
2. Requirements Discovery
3. Technical Stack Decisions
4. Architecture Decisions
5. Quality & Testing Decisions
6. Deferred Features
7. Rejected Options
8. Open Questions
9. Timeline

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Project Genesis

The Problem

Context:

• Managing team of 10-15 developers
• Handling 10-12 concurrent projects in various phases
• Currently using spreadsheets → "a nightmare"

Pain Points Identified:

1. Capacity calculation chaos: Manual calculations across holidays, PTO, weekends
2. No validation: Easy to over-allocate people or projects
3. Visibility gap: Hard to answer "Who has headroom for new work?"
4. Billing errors:
   • Over-allocation → Overcharge clients → Escalations
   • Under-allocation → Undercharge → Revenue loss
5. No audit trail: Changes are invisible
6. Actual vs Planned tracking: Difficult to compare what was planned vs what actually happened

The Vision

Product Name: Headroom

• Why this name? It's the word managers actually say ("do we have headroom for this?"), immediately signals capacity planning, and captures the over/under allocation anxiety central to the tool.
• Close runner-up: Margin (protecting margin through accurate forecasting)

Core Value:

Know exactly who has headroom for new work, prevent billing errors, forecast revenue, track planned vs actual hours.

Personas

Four distinct user types identified:

Persona	Primary Need
Superuser	System setup, configuration, admin controls
Managers	Resource planning, allocation, team oversight
Developers	View allocations, log hours, understand workload
Top Brass	Executive reports, forecasts, budget visibility

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Requirements Discovery

The Monthly Cycle

Key Insight: The workflow is organized around monthly capacity planning cycles, not continuous allocation.

Monthly Cycle:
1. Capacity Planning → Who's available, how much?
2. Project Setup → What work needs to be done?
3. Resource Allocation → Who does what?
4. Actuals Tracking → What actually happened?

Capacity Planning Requirements

Inputs:

• Team member list (name, role, hourly rate)
• Calendar data (holidays, weekends)
• Individual PTO requests
• Daily availability: 0 (unavailable), 0.5 (half day), 1.0 (full day)

Critical Clarification:

• Initial assumption: "10 hrs for Dev" meant role-based allocation
• Actual requirement: Person-specific allocation ("10 hrs for Santhosh")
• Availability is per-person, per-day, not role-based

Outputs Needed:

1. Individual capacity (person-days per month)
2. Team capacity summary (total available person-days)
3. Possible revenue (if fully utilized)

Project Management Requirements

Project Lifecycle:

NA/Support → Initial → Gathering Estimates → Estimate Pending Approval
                ↓
        Estimate Rework ←───────┘
                ↓
        Estimate Approved → Funded → Scheduled → In-Progress
                ↓
        Ready for Prod → Done
                ↓
        [Optional: On-Hold, Cancelled]

Key Attributes:

• Approved Estimate: Total billable hours approved by client
• Forecasted Effort: How those hours split across months
• Project Type: Project (billable) vs Support (ongoing ops)

Validation Requirement:

• Over-forecast: Allocated hours > Approved estimate → RED FLAG (will overcharge)
• Under-forecast: Allocated hours < Approved estimate → YELLOW FLAG (will undercharge)
• Clarification: "Under-forecast is NOT OK. This money is my salary! Always try to be 100%."

Resource Allocation Requirements

The "Matrix" Concept:

For month M:
┌────────────────────────────────────────┐
│ Project  │ Dev A │ Dev B │ Dev C │ Ext │
├──────────┼───────┼───────┼───────┼─────┤
│ Proj X   │  40h  │  20h  │   0   │ 10h │
│ Proj Y   │  20h  │  40h  │  30h  │  0  │
└────────────────────────────────────────┘

"Untracked Resource" Requirement:

• Purpose: Accommodate hours for external team members (e.g., DevOps from another team)
• Billing: NOT tracked for revenue (like a joker in a deck of cards)
• Use case: "We might bill another team, but not track their specific person"

Validation Rules:

• Sum of project allocations should equal approved estimate (tolerance: ±5%)
• Cannot allocate more than person's monthly capacity (warning, not hard block)
• Visual indicators: GREEN (100%), YELLOW (<100%), RED (>100%)

Actuals Tracking Requirements

Data Entry:

• Frequency: Monthly aggregate, but can be updated incrementally (weekly)
• Method: Manual entry (no time-tracking tool integration for MVP)

Calculations:

• Running utilization: (Allocated hours YTD) / (Capacity YTD) × 100%
• Overall utilization: (Allocated hours this month) / (Capacity this month) × 100%

Display Requirement:

• Show utilization % alongside capacity view

Reporting Requirements

Core Reports:

1. Forecast Summary (multi-period)
2. Utilization Summary
3. Cost Summary

Critical Requirement:

All reports must be highly customizable with filters (team, person, project, status, date range, type)

Additional Requirements:

• Master data / taxonomy for configurable items (roles, statuses, types)
• Support for multi-tenancy (deferred to post-MVP)

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Technical Stack Decisions

Backend: Why Laravel?

Question Raised: "I chose Laravel because of my PHP background. Debate me if that is not a good choice."

Consideration:

• Alternative: SvelteKit full-stack (single framework)
• Alternative: Next.js + Node.js

Decision: Laravel

• Rationale:
  • You have PHP background (lower learning curve)
  • Laravel is mature, robust for API development
  • Rich ecosystem (Scribe for API docs, Pest for testing, Pint for linting)
  • PostgreSQL support is excellent
  • Redis integration is first-class

No pushback from AI: Laravel is a solid choice for this use case.

Frontend: The Great Debate

Initial Question: "May be Laravel + Svelte? Or Sveltekit itself?"

Options Presented:

1. Laravel + Blade Templates (rejected: less interactive)
2. Laravel + Vue.js (recommended by AI: stay in Laravel ecosystem)
3. Laravel API + SvelteKit (separate) ← CHOSEN
4. Laravel API + React (rejected: more learning curve)

Decision: Laravel API + SvelteKit (separate projects)

• Your choice: "Sveltekit it is!"
• AI concern: "Adds deployment complexity for MVP"
• Your response: "I will choose this."
• Outcome: Two separate containers, clean separation

Why SvelteKit?

• Modern, reactive
• Great for data-heavy dashboards
• Smaller bundle sizes than React/Vue
• You're willing to learn it

Database: PostgreSQL from Day 1

Question: "SQLite for local, PostgreSQL for production?"

Decision: PostgreSQL from the start

• Rationale:
  • Avoid migration pain later
  • Production-grade features (JSON operators, full-text search)
  • Better for reporting queries
  • Volume-mounted in Docker (portability maintained)

Caching: Redis from Day 1

Initial Recommendation: "Start without caching, add in Phase 2 if slow"

Your Response: "Query caching and Response caching on Redis from Day 1. No need to sweat on refactoring it everywhere."

Decision: Redis caching from day 1

• Rationale: Prevents technical debt
• Scope: Query caching + Response caching
• Implementation: Laravel cache facade, automatic invalidation

Authentication: JWT

Question: "Session-based or Token-based (JWT)?"

AI Recommendation: "Session-based is easier for same-origin setup"

Your Choice: "I will go with JWT."

Rationale:

• Token-based authentication
• Suitable for SPA frontend
• Easier to add mobile app later (if needed)

UI Component Library

Options Presented:

• Shadcn/ui (headless, customizable)
• DaisyUI (Tailwind-based, fast) ← CHOSEN
• Svelte Material UI (full-featured)
• Build custom with Tailwind

Decision: DaisyUI

• Rationale: Faster to build dashboards, opinionated but fast
• Your response: "Daisy it is."

Charts & Visualization

Options Presented:

• Recharts ← CHOSEN (AI recommendation)
• Chart.js
• Plotly
• Apache ECharts

Decision: Recharts

• Rationale: Good balance of power and simplicity
• Your response: "Agreed"

Tables & Data Grid

Options Presented:

• TanStack Table (React Table) ← CHOSEN
• Svelte DataTable
• Build custom

Decision: TanStack Table

• AI note: "I am not familiar with this, but I will go with your recommendation."
• Rationale: Industry standard, powerful filtering/sorting, works with Svelte

Forms & Validation

Options Presented:

• SvelteKit Form Actions + Superforms
• Direct API calls

Additional Question: "How about something like Superform or Zod?"

Decision: Superforms + Zod + SvelteKit Form Actions

• Rationale:
  • Type-safe validation (Zod)
  • Form state management (Superforms)
  • Server-side handling (SvelteKit native)
  • Single source of truth for validation

API Documentation

Question Raised: "How about SwaggerUI documentation for APIs?"

Decision: Laravel Scribe (auto-generates SwaggerUI)

• Implementation: composer require knuckleswtf/scribe
• Output: /api/documentation endpoint with OpenAPI spec
• Lift: ~1 hour setup
• Inclusion: From day 1

Testing Stack

Backend:

• PHPUnit (unit tests)
• Pest (feature tests)

Frontend:

• Vitest (unit tests)
• Playwright (E2E tests)

Decision: Include all from day 1

Version Strategy

Question: Which versions to use?

Decision: Use latest versions across the stack

• Laravel 12 (latest major version)
• PHP 8.4 (compatible with Laravel 12)
• All other dependencies: Use :latest tags (PostgreSQL, Redis, Node, npm packages)

Rationale:

• Stay current with latest features and security patches
• Avoid version lock-in from the start
• Docker :latest tags ensure fresh installs get newest versions

---

Architecture Decisions

Containerization

Requirement: "From get go, everything must be containerised."

Additional Constraint: "Do not add any proxy manager (NPM, Caddy, or Traefik). My environment already runs an NPM."

Decision: Docker Compose with 4 containers

1. Frontend: SvelteKit (port 5173)
2. Backend: Laravel (port 3000)
3. Database: PostgreSQL (port 5432)
4. Cache: Redis (port 6379)

Reverse Proxy:

• Use existing Nginx Proxy Manager
• NPM routes /api/* → Laravel
• NPM routes /* → SvelteKit

Multi-Tenancy

Question: "Should we build multi-tenant from day 1?"

AI Recommendation: "Start single-tenant. Add tenant_id column when needed."

Your Response: "AGREED"

Rationale: Reduces complexity, easy to add later

Environment Configuration

Question: ".env files or Docker secrets?"

AI Recommendation: ".env files for local, Docker secrets in prod"

Your Response: ".env everywhere"

Decision: .env files in all environments

• Simpler configuration management
• Consistent across local/prod

Development Environment

Question: "Docker Compose for local dev, or native setup?"

AI Recommendation: "Docker Compose from the start. Ensures prod parity."

Your Response: "100% agree. If possible, we should have at least the local dev avoid building after every change (may be code mounted)"

Decision: Docker Compose with code-mounted volumes

• Hot reload for both frontend and backend
• Avoid rebuilding containers on every change
• Volume mounts: ./frontend:/app, ./backend:/var/www

Real-Time Updates

Question: "Do you need live updates (WebSockets), or is polling OK?"

AI Recommendation: "Start with polling. Add WebSockets if needed."

Your Response: "I dont think we need to sweat on it. Go with a basic implementation. Polling is good enough."

Decision: Polling (defer WebSockets to Phase 2)

State Management (Frontend)

Question: "Svelte stores for UI state, or always fetch from API?"

AI Recommendation: "Use Svelte stores for UI state (filters, modals), API queries for data."

Your Response: "Agreed."

Decision: Minimal Svelte stores (UI state only)

Report Exports

Question: "Will users need PDF/CSV exports?"

AI Recommendation: "Start with on-screen reports, add exports in phase 2."

Your Initial Response: "Good to have at this time."

AI Clarification: "Should exports be in MVP scope, or phase 2?"

Final Decision: Phase 2

• Rationale: Keeps MVP scope tight, adds 4 hours of work
• Interactive dashboard is primary value

Caching Strategy

Question Raised by You: "Should we talk about a caching layer?"

Options Discussed:

1. Database Query Caching
2. API Response Caching
3. Full-page caching

AI Recommendation: "Start without caching, add Redis in Phase 2 if slow"

Your Response: "Query caching and Response caching on Redis from Day 1. No need to sweat on refactoring it everywhere."

Decision: Redis caching from day 1

• Query caching (expensive calculations)
• Response caching (GET endpoints)
• Automatic cache invalidation on mutations
• TTL: 1 hour (allocations), 15 min (reports), 24 hours (master data)

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Quality & Testing Decisions

Project-Level Standing Instructions

Your 5 Points (to be encoded in OpenSpec config.yml):

1. Every change must have unit tests, E2E test, regression tests (whether prompted or not)
2. Changes must end with code review for style, standard, security
3. Verification (/opsx-verify) must trigger checking of uncovered code (code not tested)
4. Commits must be granular (one fix = one commit)
5. Tests run in a progressive loop:
   • Test → Create issue in repo → Fix → Retest + Regression test
   • Loop until all issues fixed

AI Question: "Is this for ALL tests, or specifically for E2E/integration tests?"

Your Clarification: "I agree. Let us go for a kill only in E2E and Integration."

AI Concern: "This workflow can slow velocity. For MVP, start with 'every test must pass before merge' and defer granular issue-loop to phase 2?"

Your Response: "Agreed"

Final Decision:

• MVP: All tests must pass, granular commits, code review
• Phase 2: Issue-driven test loop for E2E/integration failures

Code Coverage Threshold

AI Question: "What code coverage % for /opsx-verify?"

Your Response: "Let us call it >70%"

Decision: >70% code coverage required

• Checked in /opsx-verify
• Blocks merge if below threshold

Data Validation Rules

AI Question: "Should we document validation rules in OpenSpec?"

Your Response: "OpenSpec document must have all required data. I believe we need it there for verification and regression tests. Thoughts?"

AI Agreement: "Absolutely. Rules inform API implementation, test cases, and verification."

Decision: Create validation-rules.md in OpenSpec changes

• These rules drive Laravel validation
• Inform test case generation
• Used in /opsx-verify

RBAC (Role-Based Access Control)

AI Question: "Can a Manager see only their projects, or all projects?"

Your Clarification: "Can see all projects. But not allocate to other team's members."

Decision: RBAC Matrix defined

Persona	Can See	Can Modify
Superuser	All	All
Manager	All projects (read-only for others')	Own projects, own team allocations
Developer	Own allocations, assigned projects	Own actuals only
Top Brass	All reports	Nothing (read-only)

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Deferred Features

Phase 2 Deferrals

Feature	Reason for Deferral	Estimated Lift
Notifications (WebSocket)	Allocations are monthly, not time-critical	~6 hours
PDF/CSV Exports	On-screen reports sufficient for MVP	~4 hours
Background Jobs	No heavy processing in MVP, Laravel Queue ready	~2 hours
Audit Logging	No compliance requirement for MVP	~3 hours
Advanced Caching (pre-calculated reports)	Start with on-demand queries	~4 hours
API Versioning (/api/v1/)	Not needed until breaking changes	~2 hours
Issue-driven test loop	Slower velocity for MVP	~8 hours

Notifications Deep-Dive

AI Presented 3 Options:

Option A: Include WebSocket + 1 notification PoC (~6 hours)

• Pros: Real-time updates, framework ready
• Cons: Adds complexity, delays other features by ~1 day

Option B: Skip notifications entirely for MVP

• Pros: Keeps scope tight, faster MVP
• Cons: Users must refresh to see changes
• Debt accrual: Low (easy to add later)

Option C: Polling-based notifications (~2 hours)

• SvelteKit polls every 30s
• Pros: Simple, users see changes quickly
• Cons: Not true real-time, more server load

AI Recommendation: Option B (skip for MVP)

Your Question: "Wont it become a technical debt? How big the lift will be to at least set up the wiring for notifications (websocket setup and one notification implemented as a proof of concept?)"

AI Response: "6 hours total lift. Not worth it for MVP - allocations are monthly, not time-critical."

Your Decision: "Ok. Option B."

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Rejected Options

Options Considered but Not Chosen

Option	Why Rejected
Laravel + Blade Templates	Less interactive UI, harder to build dashboards
Laravel + Vue.js	You preferred learning Svelte over Vue
Next.js + Node.js	You have PHP background, prefer Laravel
SQLite for local dev	Avoid migration pain, PostgreSQL from start
Session-based auth	JWT chosen for future mobile support
Multi-tenancy from day 1	Adds complexity, defer to post-MVP
WebSocket notifications in MVP	Not time-critical, 6 hours of work
PDF/CSV exports in MVP	On-screen reports sufficient initially
GraphQL	REST is simpler for MVP
Chart.js / Plotly / ECharts	Recharts chosen (good balance)
Shadcn/ui / Svelte Material UI	DaisyUI chosen (faster development)
Custom-built table component	TanStack Table chosen (industry standard)

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Open Questions (Resolved)

1. Over/Under Forecast Context

Initial Confusion: "Is over/under forecast about allocation vs approved estimate, or allocation vs capacity?"

Your Clarification: "In the project's context, yes. it is allocation vs approved. (For the future phases, there will be over/under forecast for resources - that will be based on individual's allocation vs their capacity. May be we can keep that aside for now.)"

Example Correction:

• AI Example: "Month 1 allocation: 80hrs → Under-forecast (OK)"
• Your Correction: "Not OK. Because this money is my salary! We always try to be on par - 100%. If it is under-forecast, call that out."

Resolution: Both over and under-forecast are flagged. Under is YELLOW, Over is RED.

2. Availability Model

Initial Confusion: "Is availability 1.0 = 8 hours/day, or is it a percentage?"

Your Clarification: "Hours per day must be configurable per project. 1 means, 100% of a productive day. .5 means half of that and so on. I dont want to make it too granular thats why I had stops on 1, .5 and 0. Then there are H - holidays and O- weekend offs."

Resolution: Availability is 0, 0.5, or 1.0 (not percentage). 0 = unavailable or PTO.

3. Untracked Resource Purpose

Initial Confusion: "Is this for contractors, or overhead?"

Your Clarification: "We might have some time allocated for DevOps team which is not part of my team but might out bill to another team. For that purpose."

Resolution: Untracked resource is for external team time (not billed in this system).

4. Team Structure

Initial Confusion: "Does 'Team' mean sub-teams?"

Your Clarification: "Yes. Read that as 'Role'."

Resolution: Team = Role (e.g., Frontend, Backend, QA, PM, Architect).

5. Manager Permissions

Initial Confusion: "Can a Manager allocate to projects outside their team?"

Your Clarification: "Can see. But not allocate to other team's members."

Resolution: Managers see all projects (read-only for others'), but can only allocate their own team members.

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Timeline

Conversation Flow

February 17, 2026:

1. Initial Problem Statement (09:00-09:30)

   • You described the spreadsheet nightmare
   • Identified 4 personas
   • Outlined capacity planning → allocation → actuals flow

2. Requirements Deep-Dive (09:30-11:00)

   • Clarified capacity planning details (availability model)
   • Defined project lifecycle states
   • Detailed allocation matrix requirements
   • Discussed reporting needs

3. Technical Stack Discussion (11:00-12:00)

   • Debated Laravel vs alternatives → Laravel chosen
   • Frontend: Vue vs Svelte → SvelteKit chosen
   • Database: SQLite vs PostgreSQL → PostgreSQL chosen
   • Authentication: Session vs JWT → JWT chosen

4. Architecture Decisions (12:00-13:00)

   • Containerization approach (Docker Compose)
   • Multi-tenancy deferral
   • Caching strategy (Redis from day 1)
   • Real-time updates (polling, defer WebSockets)

5. Quality Standards (13:00-13:30)

   • Testing requirements (>70% coverage)
   • Code review process
   • Commit standards (granular)
   • Issue-driven test loop (defer to Phase 2)

6. Frontend Libraries (13:30-14:00)

   • UI components: DaisyUI chosen
   • Charts: Recharts chosen
   • Tables: TanStack Table chosen
   • Forms: Superforms + Zod chosen

7. Final Verification (14:00-14:30)

   • Reviewed complete architecture
   • Confirmed no missing pieces
   • Decided on API documentation (Scribe)
   • Named the project: Headroom

8. Documentation Request (14:30-15:00)

   • Request for comprehensive documentation
   • Mermaid diagrams
   • Word document for hardcopy

Key Turning Points

Moment 1: Naming the Project

• You chose "Headroom" over "Margin"
• This crystallized the product's identity

Moment 2: SvelteKit Decision

• Despite AI recommending Laravel + Vue (easier)
• You chose SvelteKit (more learning, cleaner separation)
• This showed willingness to learn for better architecture

Moment 3: Redis from Day 1

• AI recommended deferring caching
• You insisted on Redis from day 1 (avoid refactoring debt)
• This showed pragmatic technical judgment

Moment 4: "This money is my salary!"

• Clarified that under-forecast is NOT acceptable
• Both over and under-forecast must be flagged
• This revealed the business criticality of accurate allocation

Moment 5: "One last check before we lock in"

• You paused before committing to the stack
• Requested comprehensive review
• This showed careful, deliberate decision-making

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Considerations & Trade-offs

Decision Matrix

Decision	Benefit	Cost	Rationale
SvelteKit (separate)	Clean separation, modern framework	Deployment complexity, learning curve	Better long-term architecture
Redis from day 1	No refactoring debt later	Slightly more upfront setup	Prevents future pain
JWT over sessions	Mobile-ready, stateless	More complex than sessions	Future-proofing
PostgreSQL from day 1	No migration later	Heavier than SQLite	Production-grade from start
Defer notifications	Faster MVP	Users must refresh	Not time-critical for monthly planning
Defer exports	Tighter scope	No PDF/CSV initially	On-screen reports are primary value
TanStack Table	Powerful, standard	Learning curve (you're unfamiliar)	Industry best practice
DaisyUI	Fast development	Opinionated	Speed > customization for MVP

Risk Assessment

Low Risk:

• Laravel choice (you have PHP background)
• PostgreSQL choice (mature, well-supported)
• Redis choice (simple, well-integrated with Laravel)

Medium Risk:

• SvelteKit choice (learning curve, but modern and well-documented)
• TanStack Table (unfamiliar to you, but powerful)
• Two-container deployment (more moving parts, but cleaner)

Mitigated Risks:

• Over-complexity: Deferred features to Phase 2 (notifications, exports, multi-tenancy)
• Performance: Redis caching from day 1
• Testing debt: >70% coverage enforced from day 1

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Success Metrics (Defined)

MVP Success Criteria

Functional Completeness:

• ✅ Users can define team capacity
• ✅ Users can create projects with approved estimates
• ✅ Users can allocate resources month-by-month
• ✅ Users can log actual hours
• ✅ System validates allocations (over/under warnings)
• ✅ Users can view 5 core reports
• ✅ RBAC enforced (4 personas)

Quality Metrics:

• ✅ All tests passing (unit + E2E)
• ✅ Code coverage >70%
• ✅ Zero linting errors
• ✅ API documentation auto-generated

Usability Metrics (Post-Launch):

• Manager can complete monthly allocation in <30 minutes (vs 2+ hours in spreadsheet)
• Zero billing errors in first 3 months (over/under caught before invoicing)
• 90% of team members log actuals weekly

AI Rationale: "Fair but not too lenient. Manager time savings is measurable. Billing error prevention is critical. Adoption (90%) is achievable but requires discipline."

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Appendix: Conversation Highlights

Most Insightful Moments

On Under-Forecasting:

"Not OK. Because this money is my salary! We always try to be on par - 100%. If it is under-forecast, call that out."

On Naming:

"Headroom. It's the word managers actually say ('do we have headroom for this?'), it immediately signals capacity planning, and it's memorable without being try-hard."

On Caching:

"Query caching and Response caching on Redis from Day 1. No need to sweat on refactoring it everywhere."

On Quality:

"I know this will be a time taking process. But I believe it will be worth it."

On Final Review:

"Now this is the part I am most scared about. If I say yes, we need to stick to this rule book. Did I forget anything?"

Your Leadership Style

Observations from conversation:

• Pragmatic: Willing to defer features to keep scope tight
• Quality-focused: Insisted on testing, code review, coverage from day 1
• Deliberate: Paused multiple times to verify decisions before committing
• Learning-oriented: Chose SvelteKit despite unfamiliarity, trusted AI recommendations on unfamiliar tools (TanStack Table)
• Business-minded: Constantly connected technical decisions to business impact (billing accuracy, manager time savings)

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Next Steps (Post-Documentation)

Immediate Actions

1. Review Documentation

   • Read Project Charter
   • Review Architecture Document
   • Verify Decision Log captures everything

2. Formalize in OpenSpec

   • Create first change: /opsx-new headroom-foundation
   • Document proposal, specs, design, tasks
   • Begin implementation

3. Project Setup

   • Initialize Laravel project
   • Initialize SvelteKit project
   • Create Docker Compose setup
   • Configure PostgreSQL + Redis

4. First Sprint (Week 1)

   • Database schema design
   • Docker Compose working
   • JWT authentication
   • Basic CRUD for team members

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Document Control:

• Owner: Santhosh J
• Type: Conversation Archive & Decision Log
• Purpose: Comprehensive record for future reference
• Intended Audience: Santhosh J, Associate
• Format: Markdown (for git), Word (for hardcopy)

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"This is my magnum opus project as of date." — Santhosh J, February 17, 2026

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End of Decision Log