business
Hosted by Fexingo · business · EN
Lucas and Luna examine the discipline of software testing as a strategic function, not a checkbox. Each episode focuses on a specific testing practice — from unit test coverage metrics and integration test design patterns to the economics of test automation ROI and the psychology of flaky test triage. They walk through real-world case studies: how Stripe reduced regression defects by 40% with contract testing, the trade-offs between Selenium and Cypress for e-commerce checkouts, and why Google's test size taxonomy (small/medium/large) forces better architectural decisions. Lucas explains the math behind mutation testing scores and the diminishing returns of 100% code coverage; Luna challenges him on how to sell testing budgets to skeptical product managers and when manual exploratory testing still outperforms automation. They also explore testing philosophies — shift-left vs. shift-right, risk-based testing prioritization, and the role of AI in generating test oracles. The listener lea
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Signup to Generate a PitchLucas and Luna examine the discipline of software testing as a strategic function, not a checkbox. Each episode focuses on a specific testing practice, from unit test coverage metrics and integration test design patterns to the economics of test automation ROI and the psychology of flaky test triage.
Software Testing with Fexingo: QA, Automation, and Reliable Software Engineering is hosted by Fexingo. The show has published 223 episodes to date.
Recent episodes include "How GitHub Copilot Transformed Developer Quality" (1 November 2026, 12 minutes), "How Netflix Prevented Its Recommendation Engine From Collapsing" (31 October 2026, 10 minutes), and "How Microsoft Prevented Cloud Collapse" (29 October 2026, 10 minutes).
Software Testing with Fexingo: QA, Automation, and Reliable Software Engineering publishes roughly daily, with episodes averaging 11 minutes across 223 episodes.
Booking probability for Software Testing with Fexingo: QA, Automation, and Reliable Software Engineering is 36%, and the host is rated Selective on guests. Software Testing with Fexingo: QA, Automation, and Reliable Software Engineering requires a Pod Score of 80 or higher. Software Testing with Fexingo: QA, Automation, and Reliable Software Engineering's contact route on record: verified email.
The strongest fits for Software Testing with Fexingo: QA, Automation, and Reliable Software Engineering are IT Services & Software Development. Software Testing with Fexingo: QA, Automation, and Reliable Software Engineering has a business audience.
Fexingo hosts Software Testing with Fexingo: QA, Automation, and Reliable Software Engineering, a business podcast with 223 episodes published.
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Episode #226
We examine how AI coding assistants have shifted software testing from a gatekeeping function to a continuous quality signal. By analyzing specific metrics from recent engineering reports, we explore how teams are...
Episode #225
In October 2026, we look at how Netflix engineered its recommendation system to handle unprecedented scale without breaking. This episode explores the specific architectural decisions that turned a fragile data pipeline...
Episode #224
In October 2026, we look at how Microsoft shifted from traditional QA to a rigorous chaos engineering model within Azure. Lucas and Luna explore the specific incident that forced this change, the implementation of...
Episode #223
Flaky tests — automated checks that pass sometimes and fail others — are a silent tax on engineering velocity, costing teams hours of wasted debugging time every week. In this episode, we examine how a major e-commerce...
Episode #222
Airbnb faced a unique dilemma in 2023. Their platform connected millions of hosts and guests, but their testing infrastructure was built for a simpler world. As they scaled globally, traditional QA methods began to...
Episode #221
As we navigate October 25, 2026, the software testing landscape is undergoing a seismic shift driven by generative AI. This episode explores how leading engineering teams are moving beyond traditional automation to...
Episode #220
Most engineering teams treat code reviews as a quality gate, but they are actually the primary mechanism for risk mitigation and knowledge transfer. In this episode of Software Testing with Fexingo, we examine how...
Episode #219
In this episode of Software Testing with Fexingo, we dive into the specific mechanics behind how Netflix transformed chaos engineering from a risky experimental protocol into a disciplined, team-owned reliability...
Episode #218
Software teams are moving away from risky code freezes and toward feature flags as their primary safety net. This episode explores how major tech companies use toggle-based deployments to isolate failures, enable...
Episode #217
Figma faced a classic engineering paradox: their design tool was so complex that every code change risked breaking user workflows, yet they couldn't afford to slow down development. This episode explores how they moved...
Episode #216
Lucas and Luna explore how Spotify transformed its engineering quality by shifting from rigid QA gates to developer-owned testing. They examine the specific metrics behind this cultural change, why traditional test...
Episode #215
We talk about how automated testing suites create a false sense of security by optimizing for code coverage rather than actual user risk. Lucas and Luna examine why teams that hit ninety-five percent test coverage still...
Episode #214
Most engineering teams treat bugs as individual failures, leading to blame games and hidden costs. This episode examines the 'no-blame postmortem' model pioneered by Netflix and adopted by high-performing teams like...
Episode #213
Most engineering teams treat testing as a gatekeeper rather than an enabler, creating delays that slow down deployment cycles and frustrate developers. In this episode of Software Testing with Fexingo, Lucas and Luna...
Episode #212
We talk about how chaos engineering moves beyond simple uptime checks to test the resilience of distributed systems under stress. We examine how Netflix pioneered this approach and why modern teams need to inject...
Episode #211
We examine the unexpected rise of AI-assisted code quality in modern engineering teams, focusing on how tools like GitHub Copilot are shifting QA responsibilities. By looking at specific data from October 2026, we...
Episode #210
Most engineering teams treat continuous integration pipelines as a gatekeeping mechanism, a necessary evil to check code before it hits production. But what if the pipeline itself is the primary environment where...
Episode #209
Lucas and Luna dig into the hidden cost of slow, brittle test suites that stall deployment pipelines. They examine how a mid-sized fintech startup reduced its build time from forty-five minutes to under five by killing...
Episode #208
This week we look at how design-to-code handoffs break when engineering teams treat visual prototypes as final specifications. We examine a specific case where a major e-commerce platform nearly lost mobile conversion...
Episode #207
We explore the paradox of manual testing in modern software engineering, using a specific case from a mid-sized fintech startup that lost eighteen months to human error. Lucas and Luna break down why automation alone...
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