docs: import qa workflow knowledge from grilling session

raw/002-session-with-gpt.txt

@@ -0,0 +1,214 @@
+QA Workflow Assessment (Version 0.1)
+1. Profile
+
+Official Job Title
+
+QA Engineer
+
+Experience
+
+Approximately 1 year
+
+Primary Projects
+
+Yara (main project)
+TamasLink (Call Center)
+Other projects (Balan, Beno, Karjo, etc.) on a periodic basis
+
+Reporting
+
+Work requests come directly from both the CEO and CTO.
+2. Nature of the Role
+
+Although the official title is QA Engineer, the actual responsibilities extend far beyond traditional software testing.
+
+The role combines responsibilities from multiple disciplines:
+
+QA Engineer
+Requirement Analyst
+Product Analyst
+Technical Writer
+Bug Investigator
+API Tester
+Database Inspector
+3. Requirement Intake
+
+Requirements do not follow a standardized process.
+
+Typical characteristics:
+
+Received from different stakeholders.
+Usually communicated verbally or as short informal messages.
+Often consist of only one sentence or a rough idea.
+Frequently marked as urgent.
+Sometimes conflict with existing business workflows.
+Require additional clarification before implementation.
+4. Requirement Analysis Process
+
+For clear requirements:
+
+Receive Request
+        ↓
+Open Jira
+        ↓
+Navigate the current flow
+        ↓
+Capture screenshots
+        ↓
+Document the requirement
+        ↓
+Use ChatGPT with a predefined Jira template
+        ↓
+Review
+        ↓
+Publish Jira Task
+
+For ambiguous or larger requirements:
+
+Receive Request
+        ↓
+Analyze current workflow
+        ↓
+Discuss with Frontend / Backend
+        ↓
+Reach verbal agreement
+        ↓
+Create Jira Task
+5. Investigation Workflow
+
+When validating features or investigating bugs, the workflow typically involves several tools.
+
+UI
+        ↓
+Browser DevTools
+        ↓
+Network Requests
+        ↓
+Swagger
+        ↓
+MongoDB
+        ↓
+Root Cause Analysis
+6. Current Toolset
+
+Daily tools include:
+
+Jira
+Swagger
+MongoDB
+Browser DevTools
+Bruno
+Postman
+JMeter
+Paint (UI annotation)
+
+The repositories of the backend and frontend applications are also consulted when necessary, although code-reading skills are still at a beginner level.
+
+7. Current Pain Points
+A. API Complexity
+
+The biggest time consumer is API investigation.
+
+Reasons include:
+
+Large number of APIs
+Difficulty remembering rarely used APIs
+Finding the correct endpoint
+Understanding API sequences within a business flow
+Authentication before testing
+Preparing request bodies
+Switching between multiple tools
+B. Authentication Overhead
+
+Many test sessions require repeating the authentication process.
+
+Typical sequence:
+
+Open Swagger
+        ↓
+Captcha API
+        ↓
+Login API
+        ↓
+Receive Token
+        ↓
+Authorize
+        ↓
+Start Testing
+
+This workflow may be repeated multiple times every day.
+
+C. Stateful Business Flows
+
+The application is heavily state-driven.
+
+Many APIs cannot be tested independently because business entities must first reach a specific state.
+
+Example:
+
+Create Case
+      ↓
+Upload Documents
+      ↓
+Expert Review
+      ↓
+Approval
+      ↓
+Payment
+
+This creates dependencies between APIs and significantly increases investigation time.
+
+D. Test Data Preparation
+
+MongoDB is frequently used to:
+
+Inspect business entities
+Verify system state
+Modify test data when necessary
+E. Context Switching
+
+Knowledge is fragmented across multiple systems:
+
+Jira
+Swagger
+DevTools
+MongoDB
+Bruno
+Backend code
+Frontend code
+Product knowledge
+
+A single investigation often requires moving repeatedly between these tools.
+
+8. Current AI Usage
+
+ChatGPT is already integrated into the workflow.
+
+Current use cases include:
+
+Converting raw requirements into structured Jira tickets
+Improving wording
+Organizing documentation
+9. Observations
+
+Based on the current information, the main bottlenecks do not appear to be writing Jira tickets.
+
+Instead, the primary bottlenecks are:
+
+Reconstructing business context.
+Finding the correct APIs.
+Navigating complex API chains.
+Preparing valid test data.
+Repeating authentication and setup tasks.
+Frequent context switching across tools.
+10. Initial Improvement Opportunities
+
+Without changing the product itself, several areas appear promising for future optimization:
+
+Standardized Bruno/Postman collections organized by business flows.
+Better use of environments and variables to reduce repetitive authentication work.
+Documentation of business flow → API mappings.
+Reusable test data and state preparation procedures.
+AI-assisted API discovery and workflow navigation.
+AI-assisted root cause analysis support.
+A centralized QA knowledge base to preserve project knowledge across time and projects.