Quality Engineer
Breaking software before users have to.
Agentic AI Builder
Teaching AI agents to investigate, not just execute.
Community Builder
Writing and speaking on QA and applied AI.
2019 β Started as a manual tester
β Learned to break things before users could
β
2021 β Moved into automation
β Selenium, Pytest, CI pipelines
β
2023 β Started asking "why," not just "what failed"
β Root-cause diagnostics over pass/fail reports
β
2024 β Started writing prompts, not just test cases
β Prompt engineering for structured, testable AI output
β
2025 β Evaluating LLMs, not just web applications
β Testing model behaviour, reasoning, and failure modes
β
2026 β Now: teaching AI agents to investigate
β Agentic testing, autonomous root-cause analysis
flowchart LR
A(["Signal detected<br/>failure / anomaly / crash"]) --> B["Agent ingests context:<br/>logs Β· stack trace Β· DOM snapshot"]
B --> C["Form hypothesis on root cause"]
C --> D["Reproduce in sandbox"]
D --> E{"Hypothesis confirmed?"}
E -- No --> F["Discard & generate<br/>new hypothesis"]
F --> C
E -- Yes --> G["Classify root cause<br/>flaky Β· regression Β· env Β· code"]
G --> H{"Confidence high enough?"}
H -- No --> I["Flag for human review"]
I --> J(["Engineer investigates"])
H -- Yes --> K["Auto-generate report:<br/>cause Β· evidence Β· suggested fix"]
K --> L(["Handed off to dev queue"])
style A fill:#1B6E92,color:#fff
style F fill:#0F6E56,color:#fff
style I fill:#D85A30,color:#fff
style K fill:#2E9E7A,color:#fff
style L fill:#2E9E7A,color:#fff
The loop behind my Agentic Testing Framework project β an AI agent doing the root-cause investigation on its own, escalating to a human only when it isn't confident.
$ pytest --cov=beinghumantester --cov-report=term
Automation & Testing
Python ββββββββββββββββββββ 96%
Selenium ββββββββββββββββββββ 92%
Playwright ββββββββββββββββββββ 85%
Pytest ββββββββββββββββββββ 88%
AI & Backend
FastAPI ββββββββββββββββββββ 70%
PyTorch ββββββββββββββββββββ 60%
OpenAI / LLMs ββββββββββββββββββββ 80%
MCP ββββββββββββββββββββ 65%
DevOps & CI/CD
Docker ββββββββββββββββββββ 75%
Jenkins ββββββββββββββββββββ 65%
GitHub Actions ββββββββββββββββββββ 80%
Git ββββββββββββββββββββ 98%
------------------------------------------------
TOTAL 80% PASSED
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