Thanos Diacakis, Software Delivery Coach & Fractional CTO
Childhood curiosity with technology’s “buttons and knobs”Problem-solving as creative satisfaction
Podcast
Overview
Ever wonder how technology leaders adapt between nimble startups and tech giants, or what it truly takes to ship software that matters? In this insightful TBCY episode (S7 E062), Ashutosh Garg sits down with Thanos Diacakis—software delivery coach, fractional CTO, patent-holder, and independent consultant—to unpack 25+ years of lessons from the front lines of engineering and startup life.
Below you’ll find key topics explored in the episode, organized by timestamp, complete with guiding questions to help you navigate the most relevant insights for your journey.
00:00:36- What sparked Thanos’s passion for software, and what fuels it after two decades?
Childhood curiosity with technology’s “buttons and knobs”Problem-solving as creative satisfactionEvolving from coding to debugging teams and processes00:02:12- How are startups and tech giants different, and what mindset shifts are needed?
Resource constraints vs. abundanceWearing multiple hats in startups vs. specialization at scaleScaling via speed in startups; scaling via collaboration in big companiesThe challenge of consensus-building in larger organizations00:03:54- What are the most common engineering bottlenecks in early-stage startups?
Tech debt: shortcuts, their dangers, and the balance between speed vs. future painThe concept of good versus company-killing shortcutsThe importance of returning to pay down technical debt00:05:38- How can founders recognize when engineering processes are holding them back?
Focusing on output (shipping value), not just input (featuring checklists)Diagnosing bottlenecks across process, culture, and technologyThe essential step-back: defining success, then aligning processes00:07:27- What framework does Thanos use to align tech strategy with business outcomes?
Bridging business and engineering expectationsKey mental models: beyond simply adding engineersFour-stage process:Iteration: speed to deploy (idea to production in days)Quality: Observability and confidence in live systemsComplexity: Managing growth (procedural, architectural, and cultural)Planning: True predictability emerges only after mastering the prior stages00:12:51- What qualities matter when scaling engineering teams now (including AI impacts)?
Generalist engineers over language-specific specialistsEmphasis on learning, adaptability, and problem-solvingCustomer-first mentality, not tech-for-tech’s-sakeOpenness to AI as an accelerating tool—but balanced with understanding its limitations00:15:48- When should startups invest in infrastructure versus performance optimizations?
Infrastructure investment pays off early—multiplies dev productivityPerformance comes after product-market fit; avoid premature optimizationLessons from Twitter: reliability can lag if your product gets traction00:17:31- How should startups approach the classic build vs. buy dilemma?
“Buy” first, unless the last 10–20% of features are business-criticalConduct real tests before committing to in-house buildsLearn more about Thanos Diacakis: Linkedin
If you learned new insights about Startups vs. Giants: At startups, you’re scrappy—doing a bit of everything. At tech giants (like Uber), you leverage collaboration, expertise, and process, and share them with friends!
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Profile
Childhood curiosity with technology’s “buttons and knobs”Problem-solving as creative satisfactionEvolving from coding to debugging teams and processes
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