We live in the zeitgeist of artificial intelligence — where software can be built faster and cheaper than ever before. AI has leveled the playing field, turning anyone with an idea into a potential creator. But in a world where speed and cost are no longer the constraints, what will truly separate the winners from the rest? The classic development trade off — good, fast, or cheap — has long forced teams to pick two at the expense of the third. AI is changing this by enabling development that is both fast and cheap. The pressing question becomes: can AI help us achieve software that is also good ? From idea to prototype, AI empowers teams to deliver solutions quickly, affordably, and with surprisingly high quality. Moving from prototype to Minimum Viable Product (MVP), it’s still possible to maintain the trifecta of Good, Fast and Cheap. However, when aiming for production-ready applications, the stakes rise. Reliability, security, maintainability, and scalability beco...
On the morning of August 1, 2012, Knight Capital - then one of the biggest market maker on Wall Street - deployed new code to its high-speed trading system—but one of eight production servers never got the update. That lone machine started running an old, dormant module called “Power Peg,” flooding the market with errant trades. In just 45 minutes, Knight amassed nearly $7 billion in accidental positions and lost $460 million. It was one of the most expensive software failures in Wall Street history—driven by a rushed deployment, missing checks, legacy code left behind, and no clear plan to roll back. This is the story of how a routine release turned into a company-ending event—and what leaders today can learn from it. Founded in 1995, the Knight Capital Group was the largest market maker in US equities. Knight’s electronic trading group covered more than 19000 securities and it’s high frequency trading algorithms processed a daily trading volume of $20 billions which was 15% of ...