This week on Software Sundays, KD breaks down why American workers are becoming more productive, what is actually driving those gains, and why the biggest impact from artificial intelligence may still be several years away.

We start with the relationship between productivity, quality, cloud computing, remote work, and the tools that have changed how modern teams operate. KD explains why businesses will continue expecting employees and engineers to produce more with fewer resources—and what builders must do to remain competitive.

Then, we examine the growing pressure on Big Tech to justify massive AI investments. KD discusses the disconnect between Wall Street’s expectations, current model capabilities, data-center restrictions, rising infrastructure costs, and the long-term value companies must eventually prove.

We also explore Anthropic’s discussion of AI-assisted code migrations and what the Bun migration reveals about the future of software engineering. AI can help teams write and transform code faster, but experienced engineers are still responsible for planning, testing, business alignment, risk management, and delivering outcomes that stakeholders can trust.

In this episode’s Q&A, KD explains why developers should keep their branches current, when to involve IT or cybersecurity, how to determine whether a certification is worth pursuing, three practical ways to reduce cloud spending, and why planned breaks are essential for maintaining high-quality work.

We close with a reminder to remain teachable, build strong relationships with people you can learn from, and invest in the skills that allow you to move faster without sacrificing quality.

Chapters:

00:00 Introduction to the series and today's focus on tech and community

00:27 US labor productivity has been increasing for six years

00:58 Defining productivity: output over input

01:54 The importance of quality alongside productivity

02:53 Technological changes enabling productivity gains

04:09 AI's current role in productivity and future potential

06:29 The build-out phase of AI technology and its implications

07:55 The competitive landscape and continuous improvement

08:49 Mastering tools to increase efficiency

09:33 Investor expectations vs. actual AI capabilities

11:53 Regulation and its impact on AI development

13:07 The long-term value of AI investments

16:11 Efficiency in cloud resource management and FinOps

17:38 Code migration projects and engineering leadership

20:00 The irreplaceable role of human engineers

21:38 Leading with AI: decision-making and trust

22:58 Developing skills for increased productivity

23:55 Join BLI University for hands-on learning

24:59 Weekly engineering tip: keep branches current

27:27 The importance of early testing and pushing code

29:39 When to consult cybersecurity and IT

32:36 Using approved repositories and managing supply chain risks

35:37 Balancing security and innovation in development

36:00 The value of certifications and continuous learning

38:21 The role of certifications in career advancement

40:20 Reducing cloud costs through resource management

44:15 Using cloud provider tools for cost estimation

46:44 The importance of scheduled breaks and self-care

51:06 Building relationships and mentorship in tech

52:57 Final thoughts and upcoming plans

Join BLI University: https://discord.gg/jpJHGq6kgS

Connect with Build Learn Impact:

Instagram → https://www.instagram.com/build.learn.impact
Substack → https://buildlearnimpact.substack.com

Connect with Kevin Dowdy:

Instagram → https://www.instagram.com/mrkevindowdy
LinkedIn → https://www.linkedin.com/in/kevinldowdy
Substack → https://substack.com/@kevinldowdy
GitHub → https://github.com/kevindowdy

DISCLAIMER: This is not professional advice. The views are my own and the people quoted. Consult your own advisers for legal, business or tax decisions based upon information from this episode.

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