Most people remember Apollo 11 as a triumph of astronauts. That is understandable as the astronauts were the visible heroes of the mission. Their names entered history books, their faces appeared on magazine covers, and their achievements became symbols of technical excellence. But Apollo 11 did not succeed simply because NASA found the perfect astronauts. … Continued
System integration testing (SIT) exists because cross-system releases break at the handoffs, not inside a single ticket. Postman’s 2024 report shows how volatile those handoffs can be: 56% of API changes succeed with minimal issues, yet 5% experience failure rates above 25%. In most enterprises, those handoffs are APIs plus identity. When they change unpredictably, … Continued
If your agile retrospectives surface the same blockers, sprint after sprint, the meeting is collecting signals without changing the system. A successful agile retrospective reduces delivery variance in the next sprint by removing one concrete source of churn that pulls the team off committed work. Culture and resistance can block that kind of change, even … Continued
Many AI efforts stall in the same place. Teams cannot find the truth about how their systems work fast enough to change them safely. Hours disappear into rebuilding context that should be easy to find, so a simple system question turns into Slack archaeology and a repo hunt. Atlassian’s 2025 State of DevEx report found … Continued
Many offshore investments in software delivery started as a rational bet on labor arbitrage. Some organizations expanded that bet into captive centers, long-term vendors, and operating footprints that create switching costs. The math has shifted. In one study, distributed work items took about 2.5 times as long as co-located work. In a controlled experiment, developers … Continued
Across software organizations, the promise of AI is straightforward: accelerate delivery without sacrificing quality. The challenge lies in figuring out how to harness that speed safely. Recent studies show developers completing certain tasks about 50% faster, with some coding work finished in half the time. Other research shows experienced engineers losing close to 20% of … Continued
Stack Overflow’s 2025 Developer Survey shows that 84% of developers use or plan to use AI tools, yet nearly half do not trust the accuracy and lose time debugging the output. In other words, AI in software engineering has moved from pilot experiments to everyday delivery. The shift brings power and risk. Adoption is outpacing … Continued
AI tools for coding already show up in most engineering teams. Surveys report that nearly 80% of developers use or plan to use these tools in their daily work. Yet adoption doesn’t always equal trust. Many developers find themselves not trusting the output and still debugging AI-generated code that was supposed to save them time. … Continued
How generative AI works as a “probability machine” Artificial intelligence, and particularly generative AI (GenAI), has captured the imagination of leaders everywhere. As we look for ways to embrace GenAI, it’s important to understand the fundamentals; the underlying technology and software principles powering generative AI don’t operate like traditional software. What do I mean by … Continued
Practical Questions to Ask Before Starting a Generative AI Project It’s been over a year and half since OpenAI made their LLM (Large Language Model) generally available to the public, introducing the world to an exciting new technology that was leaps and bounds above anything anyone had seen in the space so far. A tidal … Continued
