Issued on 05 Aug 2026 by
Basware
| Achievement Type | Certification |
enablement@basware.com
Basware is how the world's best finance teams gain complete control of every invoice, every time. Powered by the world's most sophisticated invoice-centric AI — trained on over 2.5 billion invoices — and trusted by 6,500+ customers globally including DHL, Heineken, and Sony. Recognized as a Leader in the Gartner® Magic Quadrant™ for AP Applications, Basware is pioneering the next era of finance.
Core (both learning paths) -Generate test cases with AI from real product requirements and critically evaluate the output: gaps, incorrect assumptions, missing domain context -Execute AI-driven browser tests using Playwright CLI and agent skills -Write and maintain SKILL.md files that encode QA knowledge and guide AI output in repeatable, project-specific ways -Articulate where AI adds value and where domain expertise cannot be substituted -Apply AGENTS.md, SKILL.md, and iterative prompting as a transferable framework for integrating AI into new work beyond the training
Test Automation learning path -Design and implement a greenfield UI test automation suite from scratch with AI, using pytest or Robot Framework and Selenium page objects -Author AGENTS.md convention files that measurably improve AI code generation quality -Contribute AI-assisted improvements to a production test codebase: new coverage, flakiness fixes, modernization, or framework migration -Apply best practices (class-based tests, fixtures, parametrize, page objects, error handling) with AI guided by authored skills
Test Planning learning path -Analyse system logs with AI to identify anomalies, correlate events, and form failure hypotheses -Triage defects with AI: assess severity, hypothesize root causes, and spot where AI analysis diverges from domain knowledge -Run a structured exploratory testing session and compare AI-suggested scenarios against manual findings -Generate an AI-assisted test plan for a real feature and improve it with domain knowledge, annotating what AI missed and why -Design cross-team E2E test scenarios covering happy paths, failure modes, and integration risks across multiple systems -Perform an AI-supported regression analysis: extract defect patterns from historical data, cross-reference release changes, and build a prioritized test list with explicit defect history traceability