#execution-method

#execution-method

In the fintech industry we can link latency directly to profit and money. If I have lower latency than the competition, I can get to the better deals, I can make the better deals.

I got a degree from Douglas College in programming and business management. I understood the business side more and was better at that than at being a coder.

Operational Excellence practices alone don't guarantee success; implementation quality, organizational culture, leadership commitment, and strategic alignment determine competitive outcomes. Banks implementing identical operational improvement methodologies like Lean and Six Sigma achieve vastly different results due to factors beyond the practices themselves. Success depends on how thoroughly organizations embed these approaches into their culture, the quality of implementation execution, leadership commitment to continuous improvement, and alignment with overall business strategy.

You must be a TalkNats Subscriber to access this content. Subscribers have access to exclusive content on the TalkNats website and can engage in discussions with other Nats fans. First two weeks are free and then you will be billed $3.99/month. Cancel anytime. Secure payments using Stripe. If you are already a subscriber, simply log in using the form below.

Well, our guest today argues that the best way is by moving to a more project-driven model of work, up and down the organization from the corporate level to individual teams. He wants us to both ruthlessly prioritize as well as stay fluid so that we're identifying strategic goals, assembling teams to go after them, evaluating as we go, and then either continuing, shifting, or disbanding based on our outcomes.

To find the typical example, just observe an average stand-up meeting. The ones who talk more get all the attention. In her article, software engineer Priyanka Jain tells the story of two colleagues assigned the same task. One posted updates, asked questions, and collaborated loudly. The other stayed silent and shipped clean code. Both delivered. Yet only one was praised as a "great team player."

Your AI pilot showed 94% accuracy improvements. The LLM is yielding solid results. You're getting defunded anyway. The reason? You solved a problem AI can solve. Your budget-holder needed you to solve theirs. Companies launch AI pilots that produce results, then stall at scale. The team's diagnosis: "They don't get it." What's really going on: These projects never earned budget-holder buy-in.

"I've never felt this much behind as a programmer. The profession is being dramatically refactored as the bits contributed by the programmer are increasingly sparse and between. I have a sense that I could be 10X more powerful if I just properly string together what has become available over the last ~year and a failure to claim the boost feels decidedly like skill issue."