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ā¢ Jun 30
š Need reliable test automation for your web application?
I recently set up a complete CI pipeline using Jenkins + Selenium + Java + TestNG + Maven, where Jenkins automatically:
ā
Pulls the latest automation code from Git
ā
Executes end-to-end test suites
ā
Generates detailed HTML reports
ā
Provides quick visibility into test results and failures
I help businesses build and maintain:
š¹ UI Test Automation Frameworks
š¹ CI/CD Integration with Jenkins
š¹ Regression Test Automation
š¹ Performance Testing with JMeter & k6
š¹ Custom QA Automation Solutions
If you're looking to reduce manual testing efforts and improve release confidence, let's connect.
#QAAutomation #SDET #Selenium #Jenkins #TestAutomation #Java #TestNG #Maven #CI #SoftwareTesting #PerformanceTesting #WebAutomation
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
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I built a local Claude Code app that creates a full case study from just one website domain.
One link in.
Then it analyzes the website, understands the business, writes the case study, creates mockups, prepares visuals, and generates a video with transitions.
No manual research.
No copying content.
No starting from blank.
Just one domain ā complete case study package.
This is where AI becomes really useful:
not for random prompts, but for complete automated workflows.
If you run an agency and want a system like this for your own workflow, feel free to contact me:
ā¢ Jul 1
After using AI extensively for the last 1-2 years, I've noticed an interesting limitation.
When I ask AI to generate 10 test cases for a scenario, usually only 3-4 are highly relevant. The remaining test cases are often generic, duplicated, or based on assumptions that don't match the actual business scenario.
The problem isn't just accuracyāit's also cost(Extra Money, Water, Electricity etc).
Even the irrelevant output consumes tokens, which means:
ā¢ More tokens used
ā¢ Higher API costs
ā¢ More time spent reviewing and filtering responses
I don't think the solution is to stop using AI. Instead, we need to use it more efficiently.
A few things that have helped me:
ā
Provide complete business context and acceptance criteria.
ā
Mention constraints and assumptions explicitly.
ā
Ask for only "Top 5 high-priority test cases" instead of asking for everything.
ā
Generate test cases iteratively rather than in one big prompt.
ā
Ask AI to first identify missing information before generating the answer.
ā
Use AI as an assistant, not as a replacement for domain knowledge.
AI is incredibly powerful, but better prompting and better context are still the keys to saving both tokens and money.
Has anyone else experienced the same thing while using AI for testing or development?
Have you tried testing a feedback loop with specific domain tweaks? Curious if it improved relevance!
[Score: 97/100 | 100% Attendance] Ready to Deploy Next-Gen AI & Automation Globally š
Building powerful AI models is one thing. Integrating them into seamless, autonomous enterprise workflows is where the real value lies.
I am thrilled to share that I have officially graduated from the Ruangguru Engineering Academy+ AI Engineering Bootcamp (Batch 11) with a Certificate of Excellence (Grade A, Score: 97) and a 100% attendance record! š
Throughout this rigorous program, I specialized in bridging the gap between core AI development and enterprise automation. My technical toolkit now includes:
āļø AI Automation & Agents: Engineering autonomous Agentic AI systems and orchestrating complex production workflows using n8n.
š§ Generative AI: Designing robust RAG (Retrieval-Augmented Generation) architectures, fine-tuning LLMs, and implementing advanced NLP solutions.
šļø Core Deep Learning: Training and deploying Computer Vision and Deep Learning models powered by PyTorch and Python.
From building foundational ML algorithms to creating production-ready, AI-driven automated workflows, I am fully equipped to deliver high-impact AI engineering to global teams.
š To International Tech Leaders & Recruiters: I am actively looking for global/remote roles as an AI Engineer / Automation Engineer. If you are looking for an engineer who brings top-tier execution and reliability, letās connect or reach out via DM!
A huge thank you to my mentors and peers at Ruangguru and Skill Academy Pro for this incredible journey.
#AIEngineering #AgenticAI #n8n #AutomationWorkflow #LLM #RAG #PyTorch #DeepLearning #ComputerVision #Python #GlobalTalent #TechHiring
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