Podcasts about tech debt

It’s been a while. Episode 46 came out in late January of 2025 and I’m recording this now in mid-December, so it’s been about 10 or 11 months. When I last left off, we were in the middle of season 4, and I was telling you about all the things I was learning as I was writing my book, Swimming in Tech Debt. Well, I’m happy to say that I finally finished Swimming in Tech Debt, and it came out in September of 2025, a couple of months ago. And then the print book came out about a month and a half or so later, and I’ve learned so much about the book publishing process that I want to share with you. Write Useful Books [affiliate] The Useful Authors community Transcript

Swarupa Mahambrey, Vice President of Software Engineering at The College Board, breaks down what tech debt really looks like in a mission critical environment, and how an engineering mindset can prevent it from quietly choking delivery. She shares a practical operating model for paying down debt without stopping the roadmap, and the cultural habits that make it stick.You will hear how College Board carved out durable space for engineering excellence, how they use testing and automation to protect reliability at scale, and how to make the trade offs between features, simplicity, and user experience without slowing the team to a crawl.Key Takeaways• Tech debt behaves like financial debt, delay the payment and the interest compounds until even simple changes become painful• A permanent allocation of capacity can work, dedicating 20 percent of every sprint to tech debt can reduce support load and improve delivery• Shipping more features can slow you down, simplifying workflows and validating with real usage can increase velocity and reduce tickets• Resilience is not about avoiding every failure, it is about designing for graceful degradation so spikes and outages become small blips instead of crises• Automation is not “extra,” it is part of the definition of done, including unit tests as acceptance criteria and clear code coverage expectationsTimestamped Highlights• 00:00 Why tech debt is a mindset problem, not just a backlog problem• 01:00 Tech debt explained with a real example, what happens when a proof of concept becomes production• 03:45 The feature trap, how “powerful” workflows can overwhelm users and explode maintenance costs• 11:03 Engineering Tuesday, one day a week to strengthen foundations, not ship features• 14:39 Stability vs resilience, designing systems that bend instead of shatter• 20:06 Testing and automation at scale, unit tests as a requirement and code coverage guardrailsA line worth keeping“If we don't intentionally carve out space for engineering excellence, the urgent will always crowd out the important.”Practical moves you can steal• Protect a fixed slice of capacity for tech debt, make it part of the operating model, not a one time cleanup• Treat automation as acceptance criteria, no test, no merge, no release• Use pilots and targeted releases to learn early, then iterate based on metrics and real user behavior• Design for graceful degradation with retries, fallback paths, and clear failure visibilityCall to actionIf this episode helped you think differently about tech debt and engineering culture, follow The Tech Trek, leave a quick rating, and share it with one engineer who is fighting fires right now.

BONUS: Swimming in Tech Debt — Practical Techniques to Keep Your Team from Drowning in Its Codebase In this fascinating conversation, veteran software engineer and author Lou Franco shares hard-won lessons from decades at startups, Trello, and Atlassian. We explore his book "Swimming in Tech Debt," diving deep into the 8 Questions framework for evaluating tech debt decisions, personal practices that compound over time, team-level strategies for systematic improvement, and leadership approaches that balance velocity with sustainability. Lou reveals why tech debt is often the result of success, how to navigate the spectrum between ignoring debt and rewriting too much, and practical techniques individuals, teams, and leaders can use starting today. The Exit Interview That Changed Everything "We didn't go slower by paying tech debt. We went actually faster, because we were constantly in that code, and now we didn't have to run into problems." — Lou Franco   Lou's understanding of tech debt crystallized during an exit interview at Atalasoft, a small startup where he'd spent years. An engineer leaving the company confronted him: "You guys don't care about tech debt." Lou had been focused on shipping features, believing that paying tech debt would slow them down. But this engineer told a different story — when they finally fixed their terrible build and installation system, they actually sped up. They were constantly touching that code, and removing the friction made everything easier. This moment revealed a fundamental truth: tech debt isn't just about code quality or engineering pride. It's about velocity, momentum, and the ability to move fast sustainably. Lou carried this lesson through his career at Trello (where he learned the dangers of rewriting too much) and Atlassian (where he saw enterprise-scale tech debt management). These experiences became the foundation for "Swimming in Tech Debt." Tech Debt Is the Result of Success "Tech debt is often the result of success. Unsuccessful projects don't have tech debt." — Lou Franco   This reframes the entire conversation about tech debt. Failed products don't accumulate debt — they disappear before it matters. Tech debt emerges when your code survives long enough to outlive its original assumptions, when your user base grows beyond initial expectations, when your team scales faster than your architecture anticipated. At Atalasoft, they built for 10 users and got 100. At Trello, mobile usage exploded beyond their web-first assumptions. Success creates tech debt by changing the context in which code operates. This means tech debt conversations should happen at different intensities depending on where you are in the product lifecycle. Early startups pursuing product-market fit should minimize tech debt investments — move fast, learn, potentially throw away the code. Growth-stage companies need balanced approaches. Mature products benefit significantly from tech debt investments because operational efficiency compounds over years. Understanding this lifecycle perspective helps teams make appropriate decisions rather than applying one-size-fits-all rules. The 8 Questions Framework for Tech Debt Decisions "Those 8 questions guide you to what you should do. If it's risky, has regressions, and you don't even know if it's gonna work, this is when you're gonna do a project spike." — Lou Franco   Lou introduces a systematic framework for evaluating whether to pay tech debt, inspired by Bob Moesta's push-pull forces from product management. The 8 questions create a complete picture:   Visibility — Will people outside the team understand what we're doing? Alignment — Does this match our engineering values and target architecture? Resistance — How hard is this code to work with right now? Volatility — How often do we touch this code? Regression Risk — What's the chance we'll introduce new problems? Project Size — How big is this to fix? Estimate Risk — How uncertain are we about the effort required? Outcome Uncertainty — How confident are we the fix will actually improve things?   High volatility and high resistance with low regression risk? Pay the debt now. High regression risk with no tests? Write tests first, then reassess. Uncertain outcomes on a big project? Do a spike or proof of concept. The framework prevents both extremes — ignoring costly debt and undertaking risky rewrites without proper preparation. Personal Practices That Compound Daily "When I sit down at my desk, the first thing I do is I pay a little tech debt. I'm looking at code, I'm about to change it, do I even understand it? Am I having some kind of resistance to it? Put in a little helpful comment, maybe a little refactoring." — Lou Franco   Lou shares personal habits that create compounding improvements over time. Start each coding session by paying a small amount of tech debt in the area you're about to work — add a clarifying comment, extract a confusing variable, improve a function name. This warms you up, reduces friction for your actual work, and leaves the code slightly better than you found it. The clean-as-you-go philosophy means tech debt never accumulates faster than you can manage it. But Lou's most powerful practice comes at the end of each session: mutation testing by hand. Before finishing for the day, deliberately break something — change a plus to minus, a less-than to less-than-or-equal. See if tests catch it. Often they don't, revealing gaps in test coverage. The key insight: don't fix it immediately. Leave that failing test as the bridge to tomorrow's coding session. It connects today's momentum to tomorrow's work, ensuring you always start with context and purpose rather than cold-starting each day. Mutation Testing: Breaking Things on Purpose "Before I'm done working on a coding session, I break something on purpose. I'll change a plus to a minus, a less than to a less than equals, and see if tests break. A lot of times tests don't break. Now you've found a problem in your test." — Lou Franco   Manual mutation testing — deliberately breaking code to verify tests catch the break — reveals a critical gap in most test suites. You can have 100% code coverage and still have untested behavior. A line of code that's executed during tests isn't necessarily tested — the test might not actually verify what that line does. By changing operators, flipping booleans, or altering constants, you discover whether your tests protect against actual logic errors or just exercise code paths. Lou recommends doing this manually as part of your daily practice, but automated tools exist for systematic discovery: Stryker (for JavaScript, C#, Scala) and MutMut (for Python) can mutate your entire codebase and report which mutations survive uncaught. This isn't just about test quality — it's about understanding what your code actually does and building confidence that changes won't introduce subtle bugs. Team-Level Practices: Budgets, Backlogs, and Target Architecture "Create a target architecture document — where would we be if we started over today? Every PR is an opportunity to move slightly toward that target." — Lou Franco   At the team level, Lou advocates for three interconnected practices. First, create a target architecture document that describes where you'd be if starting fresh today — not a detailed design, but architectural patterns, technology choices, and structural principles that represent current best practices. This isn't a rewrite plan; it's a North Star. Every pull request becomes an opportunity to move incrementally toward that target when touching relevant code. Second, establish a budget split between PM-led feature work and engineering-led tech debt work — perhaps 80/20 or whatever ratio fits your product lifecycle stage. This creates predictable capacity for tech debt without requiring constant negotiation. Third, hold quarterly tech debt backlog meetings separate from sprint planning. Treat this backlog like PMs treat product discovery — explore options, estimate impacts, prioritize based on the 8 Questions framework. Some items fit in sprints; others require dedicated engineers for a quarter or two. This systematic approach prevents tech debt from being perpetually deprioritized while avoiding the opposite extreme of engineers disappearing into six-month "improvement" projects with no visible progress. The Atlassian Five-Alarm Fire "The Atlassian CTO's 'five-alarm fire' — stopping all feature development to focus on reliability. I reduced sync errors by 75% during that initiative." — Lou Franco   Lou shares a powerful example of leadership-driven tech debt management at scale. The Atlassian CTO called a "five-alarm fire" — halting all feature development across the company to focus exclusively on reliability and tech debt. This wasn't panic; it was strategic recognition that accumulated debt threatened the business. Lou worked on reducing sync errors, achieving a 75% reduction during this focused period. The initiative demonstrated several leadership principles: willingness to make hard calls that stop revenue-generating feature work, clear communication of why reliability matters strategically, trust that teams will use the time wisely, and commitment to see it through despite pressure to resume features. This level of intervention is rare and shouldn't be frequent, but it shows what's possible when leadership truly prioritizes tech debt. More commonly, leaders should express product lifecycle constraints (startup urgency vs. mature product stability), give teams autonomy to find appropriate projects within those constraints, and require accountability through visible metrics and dashboards that show progress. The Rewrite Trap: Why Big Rewrites Usually Fail "A system that took 10 years to write has implicit knowledge that can't be replicated in 6 months. I'm mostly gonna advocate for piecemeal migrations along the way, reducing the size of the problem over time." — Lou Franco   Lou lived through Trello's iOS navigation rewrite — a classic example of throwing away working code to start fresh, only to discover all the edge cases, implicit behaviors, and user expectations baked into the "old" system. A codebase that evolved over several years contains implicit knowledge — user workflows, edge case handling, performance optimizations, and subtle behaviors that users rely on even if they never explicitly requested them. Attempting to rewrite this in six months inevitably misses critical details. Lou strongly advocates for piecemeal migrations instead. The Trello "Decaffeinate Project" exemplifies this approach — migrating from CoffeeScript to TypeScript incrementally, with public dashboards showing the percentage remaining, interoperable technologies allowing gradual transition, and the ability to pause or reverse if needed. Keep both systems running in parallel during migrations. Use runtime observability to verify new code behaves identically to old code. Reduce the problem size steadily over months rather than attempting big-bang replacements. The only exception: sometimes keeping parallel systems requires scaffolding that creates its own complexity, so evaluate whether piecemeal migration is actually simpler or if you're better off living with the current system. Making Tech Debt Visible Through Dashboards "Put up a dashboard, showing it happen. Make invisible internal improvements visible through metrics engineering leadership understands." — Lou Franco   One of tech debt's biggest challenges is invisibility — non-technical stakeholders can't see the improvement from refactoring or test coverage. Lou learned to make tech debt work visible through dashboards and metrics. The Decaffeinate Project tracked percentage of CoffeeScript files remaining, providing a clear progress indicator anyone could understand. When reducing sync errors, Lou created dashboards showing error rates declining over time. These visualizations serve multiple purposes: they demonstrate value to leadership, create accountability for engineering teams, build momentum as progress becomes visible, and help teams celebrate wins that would otherwise go unnoticed. The key is choosing metrics that matter to the business — error rates, page load times, deployment frequency, mean time to recovery — rather than pure code quality metrics like cyclomatic complexity that don't translate outside engineering. Connect tech debt work to customer experience, reliability, or developer productivity in ways leadership can see and value. Onboarding as a Tech Debt Opportunity "Unit testing is a really great way to learn a system. It's like an executable specification that's helping you prove that you understand the system." — Lou Franco   Lou identifies onboarding as an underutilized opportunity for tech debt reduction. When new engineers join, they need to learn the codebase. Rather than just reading code or shadowing, Lou suggests having them write unit tests in areas they're learning. This serves dual purposes: tests are executable specifications that prove understanding of system behavior, and they create safety nets in areas that likely lack coverage (otherwise, why would new engineers be confused by the code?). The new engineer gets hands-on learning, the team gets better test coverage, and everyone wins. This practice also surfaces confusing code — if new engineers struggle to understand what to test, that's a signal the code needs clarifying comments, better naming, or refactoring. Make onboarding a systematic tech debt reduction opportunity rather than passive knowledge transfer. Leadership's Role: Constraints, Autonomy, and Accountability "Leadership needs to express the constraints. Tell the team what you're feeling about tech debt at a high level, and what you think generally is the appropriate amount of time to be spent on it. Then give them autonomy." — Lou Franco   Lou distills leadership's role in tech debt management to three elements. First, express constraints — communicate where you believe the product is in its lifecycle (early startup, rapid growth, mature cash cow) and what that means for tech debt tolerance. Are we pursuing product-market fit where code might be thrown away? Are we scaling a proven product where reliability matters? Are we maintaining a stable system where operational efficiency pays dividends? These constraints help teams make appropriate trade-offs. Second, give autonomy — once constraints are clear, trust teams to identify specific tech debt projects that fit those constraints. Engineers understand the codebase's pain points better than leaders do. Third, require accountability — teams must make their work visible through dashboards, metrics, and regular updates. Autonomy without accountability becomes invisible engineering projects that might not deliver value. Accountability without autonomy becomes micromanagement that wastes engineering judgment. The balance creates space for teams to make smart decisions while keeping leadership informed and confident in the investment. AI and the Future of Tech Debt "I really do AI-assisted software engineering. And by that, I mean I 100% review every single line of that code. I write the tests, and all the code is as I would have written it, it's just a lot faster. Developers are still responsible for it. Read the code." — Lou Franco   Lou has a chapter about AI in his book, addressing the elephant in the room: will AI-generated code create massive tech debt? His answer is nuanced. AI can accelerate development tremendously if used correctly — Lou uses it extensively but reviews every single line, writes all tests himself, and ensures the code matches what he would have written manually. The problem emerges with "vibe coders" — non-developers using AI to generate code they don't understand, creating unmaintainable messes that become someone else's problem. Developers remain responsible for all code, regardless of how it's generated. This means you must read and understand AI-generated code, not blindly accept it. Lou also raises supply chain security concerns — dependencies can contain malicious code, and AI might introduce vulnerabilities developers miss. His recommendation: stay six months behind on dependency updates, let others discover the problems first, and consider separate sandboxed development machines to limit security exposure. AI is a powerful tool, but it doesn't eliminate the need for engineering judgment, testing discipline, or code review practices. The Style Guide Beyond Formatting "Have a style guide that goes beyond formatting to include target architecture. This is the kind of code we want to write going forward." — Lou Franco   Lou advocates for style guides that extend beyond tabs-versus-spaces formatting rules to include architectural guidance. Document patterns you want to move toward: how should components be structured, what state management approaches do we prefer, how should we handle errors, what testing patterns should we follow? This creates a shared understanding of the target architecture without requiring a massive design document. When reviewing pull requests, teams can reference the style guide to explain why certain approaches align with where the codebase is headed versus perpetuating old patterns. This makes tech debt conversations less personal and more objective — it's not about criticizing someone's code, it's about aligning with team standards and strategic direction. The style guide becomes a living document that evolves as the team learns and technology changes, capturing collective wisdom about what good code looks like in your specific context. Recommended Resources Some of the resources mentioned in this episode include:  Steve Blank's Four Steps To Epiphany The podcast episode with Bernie Maloney where we discuss the critical difference between "enterprise" and "startup". And Geoffrey Moore's Crossing the Chasm, and Dealing with Darwin.   About Lou Franco   Lou Franco is a veteran software engineer and author of Swimming in Tech Debt. With decades of experience at startups, as well as Trello, and Atlassian, he's seen both sides of debt—as coder and leader. Today, he advises teams on engineering practices, helping them turn messy codebases into momentum.   You can link with Lou Franco on LinkedIn and learn more at LouFranco.com.

AI Assisted Coding: Swimming in AI - Managing Tech Debt in the Age of AI-Assisted Coding In this special episode, Lou Franco, veteran software engineer and author of "Swimming in Tech Debt," shares his practical approach to AI-assisted coding that produces the same amount of tech debt as traditional development—by reading every line of code. He explains the critical difference between vibecoding and AI-assisted coding, why commit-by-commit thinking matters, and how to reinvest productivity gains into code quality. Vibecoding vs. AI-Assisted Coding: Reading Code Matters "I read all the code that it outputs, so I need smaller steps of changes."   Lou draws a clear distinction between vibecoding and his approach to AI-assisted coding. Vibecoding, in his definition, means not reading the code at all—just prompting, checking outputs, and prompting again. His method is fundamentally different: he reads every line of generated code before committing it. This isn't just about catching bugs; it's about maintaining architectural control and accountability. As Lou emphasizes, "A computer can't be held accountable, so a computer can never make decisions. A human always has to make decisions." This philosophy shapes his entire workflow—AI generates code quickly, but humans make the final call on what enters the repository. The distinction matters because it determines whether you're managing tech debt proactively or discovering it later when changes become difficult. The Moment of Shift: Staying in the Zone "It kept me in the zone. It saved so much time! Never having to look up what a function's arguments were... it just saved so much time."   Lou's AI coding journey began in late 2022 with GitHub Copilot's free trial. He bought a subscription immediately after the trial ended because of one transformative benefit: staying in the flow state. The autocomplete functionality eliminated constant context switching to documentation, Stack Overflow searches, and function signature lookups. This wasn't about replacing thinking—it was about removing friction from implementation. Lou could maintain focus on the problem he was solving rather than getting derailed by syntax details. This experience shaped his understanding that AI's value lies in removing obstacles to productivity, not in replacing the developer's judgment about architecture and design. Thinking in Commits: The Right Size for AI Work "I think of prompts commit-by-commit. That's the size of the work I'm trying to do in a prompt."   Lou's workflow centers on a simple principle: size your prompts to match what should be a single commit. This constraint provides multiple benefits. First, it keeps changes small enough to review thoroughly—if a commit is too big to review properly, the prompt was too ambitious. Second, it creates a clear commit history that tells a story about how the code evolved. Third, it enables easy rollback if something goes wrong. This commit-sized thinking mirrors good development practices that existed long before AI—small, focused changes that each accomplish one clear purpose. Lou uses inline prompting in Cursor (Command-K) for these localized changes because it keeps context tight: "Right here, don't go look at the rest of my files... Everything you need is right here. The context is right here... And it's fast." The Tech Debt Question: Same Code, Same Debt "Based on the way I've defined how I did it, it's exactly the same amount of tech debt that I would have done on my own... I'm faster and can make more code, but I invest some of that savings back into cleaning things up."   As the author of "Swimming in Tech Debt," Lou brings unique perspective to whether AI coding creates more technical debt. His answer: not if you're reading and reviewing everything. When you maintain the same quality standards—code review, architectural oversight, refactoring—you generate the same amount of debt as manual coding. The difference is speed. Lou gets productivity gains from AI, and he consciously reinvests a portion of those gains back into code quality through refactoring. This creates a virtuous cycle: faster development enables more time for cleanup, which maintains a codebase that's easier for both humans and AI to work with. The key insight is that tech debt isn't caused by AI—it's caused by skipping quality practices regardless of how code is generated. When Vibecoding Creates Debt: AI Resistance as a Symptom "When you start asking the AI to do things, and it can't do them, or it undoes other things while it's doing them... you're experiencing the tech debt a different way. You're trying to make changes that are on your roadmap, and you're getting resistance from making those changes."   Lou identifies a fascinating pattern: tech debt from vibecoding (without code review) manifests as "AI resistance"—difficulty getting AI to make the changes you want. Instead of compile errors or brittle tests signaling problems, you experience AI struggling to understand your codebase, undoing changes while making new ones, or producing code with repetition and tight coupling. These are classic tech debt symptoms, just detected differently. The debt accumulates through architecture violations, lack of separation of concerns, and code that's hard to modify. Lou's point is profound: whether you notice debt through test failures or through AI confusion, the underlying problem is the same—code that's difficult to change. The solution remains consistent: maintain quality practices including code review, even when AI makes generation fast. Can AI Fix Tech Debt? Yes, With Guidance "You should have some acceptance criteria on the code... guide the LLM as to the level of code quality you want."   Lou is optimistic but realistic about AI's ability to address existing tech debt. AI can definitely help with refactoring and adding tests—but only with human guidance on quality standards. You must specify what "good code" looks like: acceptance criteria, architectural patterns, quality thresholds. Sometimes copy/paste is faster than having AI regenerate code. Very convoluted codebases challenge both humans and AI, so some remediation should happen before bringing AI into the picture. The key is recognizing that AI amplifies your approach—if you have strong quality standards and communicate them clearly, AI accelerates improvement. If you lack quality standards, AI will generate code just as problematic as what already exists. Reinvesting Productivity Gains in Quality "I'm getting so much productivity out of it, that investing a little bit of that productivity back into refactoring is extremely good for another kind of productivity."   Lou describes a critical strategy: don't consume all productivity gains as increased feature velocity. Reinvest some acceleration back into code quality through refactoring. This mirrors the refactor step in test-driven development—after getting code working, clean it up before moving on. AI makes this more attractive because the productivity gains are substantial. If AI makes you 30% faster at implementation, using 10% of that gain on refactoring still leaves you 20% ahead while maintaining quality. Lou explicitly budgets this reinvestment, treating quality maintenance as a first-class activity rather than something that happens "when there's time." This discipline prevents the debt accumulation that makes future work progressively harder. The 100x Code Concern: Accountability Remains Human "Directionally, I think you're probably right... this thing is moving fast, we don't know. But I'm gonna always want to read it and approve it."   When discussing concerns about AI generating 100x more code (and potentially 100x more tech debt), Lou acknowledges the risk while maintaining his position: he'll always read and approve code before it enters the repository. This isn't about slowing down unnecessarily—it's about maintaining accountability. Humans must make the decisions because only humans can be held accountable for those decisions. Lou sees potential for AI to improve by training on repository evolution rather than just end-state code, learning from commit history how codebases develop. But regardless of AI improvements, the human review step remains essential. The goal isn't to eliminate human involvement; it's to shift human focus from typing to thinking, reviewing, and making architectural decisions. Practical Workflow: Inline Prompting and Small Changes "Right here, don't go look at the rest of my files... Everything you need is right here. The context is right here... And it's fast."   Lou's preferred tool is Cursor with inline prompting (Command-K), which allows him to work on specific code sections with tight context. This approach is fast because it limits what AI considers, reducing both latency and irrelevant changes. The workflow resembles pair programming: Lou knows what he wants, points AI at the specific location, AI generates the implementation, and Lou reviews before accepting. He also uses Claude Code for full codebase awareness when needed, but the inline approach dominates his daily work. The key principle is matching tool choice to context needs—use inline prompting for localized changes, full codebase tools when you need broader understanding. This thoughtful tool selection keeps development efficient while maintaining control. Resources and Community Lou recommends Steve Yegge's upcoming book on vibecoding. His website, LouFranco.com, provides additional resources.    About Lou Franco   Lou Franco is a veteran software engineer and author of Swimming in Tech Debt. With decades of experience at startups, as well as Trello, and Atlassian, he's seen both sides of debt—as coder and leader. Today, he advises teams on engineering practices, helping them turn messy codebases into momentum.   You can link with Lou Franco on LinkedIn and visit his website at LouFranco.com.

Jessica Swank, Chief People Officer at Box, joined us on The Modern People Leader. We talked about building an "org brain", preparing managers to lead teams of humans plus agents, avoiding agent sprawl and tech debt, and why every people leader needs to start experimenting with AI personally to stay ahead.----  Downloadable PDF with top takeaways: https://modernpeopleleader.kit.com/episode269Sponsor Links:

(06:06) Brought to you by JellyfishAI tools alone won't transform your engineering org. Jellyfish provides insights into AI tool adoption, cost, and delivery impact – so you can make better investment decisions and build teams that use AI effectively. See for yourself at jellyfish.co/platform/ai-impact.Why do organizations constantly complain about having too much technical debt? Because they're solving the wrong problem.In this episode, Dr. Andrew Brown, author of “Taming Your Dragon: Addressing Your Technical Debt,” reveals a profound insight: technical debt isn't fundamentally a technical problem. It's a trade-off problem rooted in human bias, organizational systems, and economic incentives. Through his innovative “Technical Debt Onion Model,” Andrew shows how decisions about code quality happen across five interconnected layers, from individual cognitive biases to wicked problem dynamics.Andrew explains why the financial debt analogy is dangerously misleading and, more importantly, how others can rack up debt you'll eventually pay for. Drawing from behavioral economics, systems thinking, and organizational theory, he reveals why our emotions, not logic, drive most technical decisions, and how to work with this reality rather than against it.Key topics discussed:Why technical debt is a trade-off problem, not technicalHow emotions override logic in critical decisionsThe Technical Debt Onion Model framework explainedPrincipal-agent problems sabotaging your codebaseExternalities: who pays for shortcuts taken today?Why burning down debt is already too lateUlysses contracts for managing future obligationsSystems thinking applied to software developmentWicked problems: why different teams see different solutionsAI's impact on technical debt creationTimestamps:(00:00:00) Trailer & Intro(00:02:24) Career Turning Points(00:06:06) The Importance of Skilling Up in Tech(00:06:49) The Definition of Technical Debt(00:09:08) The Broken Analogy of Technical Debt as a Financial Debt(00:09:58) The Role of Human Bias and Organization Issues in Technical Debt(00:12:41) Tech Debt is a Trade-off Problem(00:13:07) Building a Healthier Relationship with Technical Debt(00:15:15) The Technical Debt Onion Model(00:18:17) The Onion Model: Trade-Off Layer(00:25:10) The Ulysses Contract for Managing Technical Debt(00:33:03) The Onion Model: Systems Layer(00:36:32) The Onion Model: Economics/Game-Theory Layer(00:41:50) The Onion Model: Wicked Problem Layer(00:48:10) How Organizations Can Start Managing Technical Debt Better(00:52:03) The Al Impact on Technical Debt(00:56:16) 3 Tech Lead Wisdom_____Andrew Brown's BioAndrew Richard Brown has worked in software since 1999, starting as an SAP programmer fixing Y2K bugs. He realized the biggest problems in software development were human, not technical, and has since helped teams improve performance by addressing these issues.Andrew coaches organizations on software development and quality engineering, focusing on technical debt, risk in complex systems, and project underestimation. He investigates how cognitive biases drive software problems and applies behavioral science techniques to solve them. His research has produced counterintuitive insights and fresh approaches. He regularly speaks at international conferences and runs a growing YouTube channel on these topics.Follow Andrew:LinkedIn – linkedin.com/in/andrew-brown-4b38062YouTube – @behaviouralsoftwareclub705Email – brownsensei@hotmail.com Taming Your Dragon – https://www.amazon.com/Taming-Your-Dragon-Addressing-Technical/dp/B0CV4TTP32/Like this episode?Show notes & transcript: techleadjournal.dev/episodes/239.Follow @techleadjournal on LinkedIn, Twitter, and Instagram.Buy me a coffee or become a patron.

On this episode, I cover questions about enterprise security issues relating to the recent heist at the Louvre, another example of technical debt at an organization costing millions, zero day vulnerabilities patched by QNAP and more! Reference Links: https://www.rorymon.com/blog/tech-debt-questions-for-louvre-config-man-update-cadence-to-change-win11-market-share-on-the-rise/

Pega provides the leading AI-powered platform for enterprise transformation. The world's most influential organizations trust Pega's technology to reimagine how work gets done by automating workflows, personalizing customer experiences, and modernizing legacy systems. Since 1983, Pega's scalable, flexible architecture has fueled continuous innovation, helping clients accelerate their path to the autonomous enterprise. Learn more at Pega.comWhat if the most valuable use of AI in the enterprise is actually the often overlooked yet incredibly costly work of untangling decades of legacy code and process documents? Agility requires the ability to adapt and evolve, but for many enterprises, that ability is trapped inside decades of legacy systems and byzantine processes. What if the same AI that's creating the new could also be the key to understanding and modernizing the old? Today, we're going to talk about moving beyond the hype we're so used to hearing about AI and into the practical, high-impact world of agentic AI. We'll explore how this approach can help large organizations finally tackle their technical debt, not by ripping and replacing, but by understanding and redesigning from the inside out, fostering a new level of collaboration between business and IT along the way. To help me discuss this topic, I'd like to welcome, Don Schuerman, CTO at Pega. About Don Schuerman As CTO and Vice President of Marketing & Technology Strategy at Pegasystems, I see my role as being a "Chief Translation Officer" – bridging the gap between cutting-edge technology and real-world business value. With 25 years of experience in orchestration and AI technology, I'm passionate about translating complex technical concepts into meaningful solutions that drive digital transformation for global organizations.My approach to technology leadership has been shaped by an unexpected source: 20 years of improv comedy at ImprovBoston's Mainstage. The skills I honed there – active listening, storytelling, and thinking on my feet – now help me connect with both technical teams and business leaders. It's where I also met my wife, proving that sometimes the best partnerships form when you say "yes, and..."At Pega, I lead the intersection of technology and go-to-market strategy across our enterprise AI decisioning and workflow automation platform. My focus is two-fold: translating the power of technology into tangible value for our Fortune 500 clients, while ensuring our technology roadmap reflects the evolving needs of these organizations. I believe that inclusivity is a key ingredient of innovation and am honored to service as Executive Sponsor of the Pride@Pega Employee Resource Group. Don Schuerman on LinkedIn: https://www.linkedin.com/in/donschuerman/ Resources Pega: https://www.pega.com Pega provides the leading AI-powered platform for enterprise transformation. The world's most influential organizations trust Pega's technology to reimagine how work gets done by automating workflows, personalizing customer experiences, and modernizing legacy systems. Since 1983, Pega's scalable, flexible architecture has fueled continuous innovation, helping clients accelerate their path to the autonomous enterprise. Catch the future of e-commerce at eTail Palm Springs, Feb 23-26 in Palm Springs, CA. Go here for more details: https://etailwest.wbresearch.com/ Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregkihlstromDon't miss a thing: get the latest episodes, sign up for our newsletter and more: https://www.theagilebrand.showCheck out The Agile Brand Guide website with articles, insights, and Martechipedia, the wiki for marketing technology: https://www.agilebrandguide.com The Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. https://www.missinglink.company

Pega provides the leading AI-powered platform for enterprise transformation. The world's most influential organizations trust Pega's technology to reimagine how work gets done by automating workflows, personalizing customer experiences, and modernizing legacy systems. Since 1983, Pega's scalable, flexible architecture has fueled continuous innovation, helping clients accelerate their path to the autonomous enterprise. Learn more at Pega.comWhat if the most valuable use of AI in the enterprise is actually the often overlooked yet incredibly costly work of untangling decades of legacy code and process documents? Agility requires the ability to adapt and evolve, but for many enterprises, that ability is trapped inside decades of legacy systems and byzantine processes. What if the same AI that's creating the new could also be the key to understanding and modernizing the old? Today, we're going to talk about moving beyond the hype we're so used to hearing about AI and into the practical, high-impact world of agentic AI. We'll explore how this approach can help large organizations finally tackle their technical debt, not by ripping and replacing, but by understanding and redesigning from the inside out, fostering a new level of collaboration between business and IT along the way. To help me discuss this topic, I'd like to welcome, Don Schuerman, CTO at Pega. About Don Schuerman As CTO and Vice President of Marketing & Technology Strategy at Pegasystems, I see my role as being a "Chief Translation Officer" – bridging the gap between cutting-edge technology and real-world business value. With 25 years of experience in orchestration and AI technology, I'm passionate about translating complex technical concepts into meaningful solutions that drive digital transformation for global organizations.My approach to technology leadership has been shaped by an unexpected source: 20 years of improv comedy at ImprovBoston's Mainstage. The skills I honed there – active listening, storytelling, and thinking on my feet – now help me connect with both technical teams and business leaders. It's where I also met my wife, proving that sometimes the best partnerships form when you say "yes, and..."At Pega, I lead the intersection of technology and go-to-market strategy across our enterprise AI decisioning and workflow automation platform. My focus is two-fold: translating the power of technology into tangible value for our Fortune 500 clients, while ensuring our technology roadmap reflects the evolving needs of these organizations. I believe that inclusivity is a key ingredient of innovation and am honored to service as Executive Sponsor of the Pride@Pega Employee Resource Group. Don Schuerman on LinkedIn: https://www.linkedin.com/in/donschuerman/ Resources Pega: https://www.pega.com Pega provides the leading AI-powered platform for enterprise transformation. The world's most influential organizations trust Pega's technology to reimagine how work gets done by automating workflows, personalizing customer experiences, and modernizing legacy systems. Since 1983, Pega's scalable, flexible architecture has fueled continuous innovation, helping clients accelerate their path to the autonomous enterprise. Catch the future of e-commerce at eTail Palm Springs, Feb 23-26 in Palm Springs, CA. Go here for more details: https://etailwest.wbresearch.com/ Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregkihlstromDon't miss a thing: get the latest episodes, sign up for our newsletter and more: https://www.theagilebrand.showCheck out The Agile Brand Guide website with articles, insights, and Martechipedia, the wiki for marketing technology: https://www.agilebrandguide.com The Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. https://www.missinglink.company

If Caleb Hammer hosted a show for CIOs, this would be the episode.

"L'importance ne réside plus uniquement dans l'écriture de code, mais dans la capacité à exprimer des concepts systèmes et à conceptualiser les solutions." Episode in English // Premier épisode en anglais d'If This Then DevThe D.E.V. of the week is Marcel Weekes, VP of Engineering at Figma.Marcel shares what it means to lead a global engineering team while keeping collaboration, creativity, and quality at the core. We discuss how Figma bridges designers, developers, and AI &mdash and how this unique culture shapes the way software gets built.From managing tech debt at scale to integrating AI-driven code generation, Marcel reflects on how roles are evolving, why feedback is an art form, and what agility really means when your product is collaboration itself.A sincere and grounded conversation on leadership, complexity, and the human side of engineering.Chapters00:00:53 : Introduction: the Figma mindset00:03:17 : Inside Figma's 700-engineer team00:08:33 : Productivity, collaboration, and trust00:11:42 : The VP Engineering's role in keeping teams connected00:16:16 : The art of feedback00:22:02 : Managing tech debt at scale00:27:30 : Code generation tools and developer satisfaction00:34:05 : How AI is changing software development00:41:25 : The evolving role of developers with AI00:45:54 : Final thoughts and cultural recommendationsMarcel's recommandationAtlanta (serie TV) **Restez compliant !** Cet épisode est soutenu par Vanta, la plateforme de Trust Management qui aide les entreprises à automatiser leur sécurité et leur conformité. Avec Vanta, se mettre en conformité avec des standards comme SOC 2, ISO 27001 ou HIPAA devient plus rapide, plus simple, et surtout durable. Plus de 10 000 entreprises dans le monde utilisent déjà Vanta pour transformer leurs obligations de sécurité en véritable moteur de croissance.

In this conversation, Marc Binkley and Vassilis Douros reflect on their conversation with Ben Allison, exploring various aspects of media planning and marketing strategies. They focus on the importance of understanding the media diet pyramid, navigating the attention economy, and integrating organic social media into marketing efforts. They discuss the challenges posed by tech debt and the need for cohesive planning, especially as Q4 approaches.Enjoy the show:Our Guest:Ben Allison - EVP Media @ VaynerMediahttps://www.linkedin.com/in/benjamin-allison-7331a646/https://vaynermedia.com/Follow Our Updates⁠⁠LinkedIn: https://www.linkedin.com/company/sleeping-barber/https://www.sleepingbarber.caGet in touch with our hosts:Marc Binkley: ⁠⁠https://www.linkedin.com/in/marcbinkley/Vassilis Douros: https://www.linkedin.com/in/vassilisdouros/Takeaways:The media diet pyramid helps visualize media channels.Walled gardens are essential for audience reach.Retail media and linear streaming should be integrated.Attention economy requires a principled media approach.Search is more about shelf space than direct advertising.SEO remains a complex and opaque field.Organic social can provide insights into audience attention.Marketing teams must collaborate for cohesive strategies.Tech debt can drain marketing budgets.Understanding attention versus impressions is crucial.Chapters:00:00 - Introduction to the Post Pod02:39 - Media Diet Pyramid and Its Implications05:21 - Navigating the Attention Economy07:56 - The Role of Search and SEO10:13 - Organic Social and Marketing Integration12:38 - Tech Debt and Marketing Challenges

In this episode, eXp founder and CEO Glenn Sanford joins us for a raw, unfiltered conversation about his journey. Glenn shares the origin story of eXp, revealing how the 2008 crash forced him to craft a new business model from a "blank sheet of paper." He discusses the challenges of building a brand, surviving a hostile takeover, and why focusing on agent experience over a P&L is the only path to lasting success. Connect with Glenn on - LinkedIn. Learn more about eXp World Holding on - Instagram - LinkedIn - X - Facebook or online at expworldholdings.com. Follow these links for SUCCESS Magazine - Instagram - Facebook - TikTok - LinkedIn - Pinterest - X and online at success.com.   Subscribe to Real Estate Insiders Unfiltered on YouTube! https://www.youtube.com/@RealEstateInsidersUnfiltered?sub_confirmation=1   To learn more about becoming a sponsor of the show send us an email: jessica@inman.com You asked for it. We delivered. Check out our new merch! https://merch.realestateinsidersunfiltered.com/   Follow Real Estate Insiders Unfiltered Podcast on Instagram - YouTube - Facebook - TikTok. Visit us online at realestateinsidersunfiltered.com.   Link to Facebook Page: https://www.facebook.com/RealEstateInsidersUnfiltered Link to Instagram Page: https://www.instagram.com/realestateinsiderspod/ Link to YouTube Page: https://www.youtube.com/@RealEstateInsidersUnfiltered Link to TikTok Page: https://www.tiktok.com/@realestateinsiderspod Link to website: https://realestateinsidersunfiltered.com This podcast is produced by Two Brothers Creative. https://twobrotherscreative.com/contact/  

People talk quite a lot about things like 'shift left" that make it sound as if it is a new concept -- sold at your finer consultancies -- to build things properly in the first place. After two decades of incident response, smoke jumping and Tech Debt burndowns, I think it's time to talk about the way teams can build security not just into the product but into the company culture by examining some basic realities of the product development process. This is not just for tech companies; it's for any firm with a process by which they turn ideas into money. Because for all the SDLC tools, all the configuration platforms, the code scanners, and the security and code testing doodads out there, nothing in my experience works as well as starting with the basics: including security and legal experts as well as the people who manage the internal services that will be your upstream and downstream dependencies at the ideation stage. The amount of weapons-grade stupid, the mountain ranges of tech debt, and the broken business promises that this simple plan can avoid make it hard to believe that it's so rare to find these practices in mainstream companies. In this talk, I will describe the most common side effects of failing to do this, how those side effects manifest into cultural roadblocks, silos, and sadness, and most important: how you can break the cycle, slash through the Gordian knot of despair and missed deadlines, and return to cranking out product like a start up. About the speaker: Nick Selby is the founder of EPSD, Inc., and he has more than 20 years of experience advising organizations in highly targeted industries. Previously, he led professional services at Evertas and served as Interim Executive Director of the Cryptoasset Intelligence Sharing and Analysis Center. His executive roles have also included stints at Trail of Bits and Paxos Trust Company. He managed cyber incident response at TRM Partners and N4Struct, and in 2005 founded the information security practice at 451 Research (now S&P Global Intelligence), where he served as Vice President of Research Operations until 2009. As Director of Cyber Intelligence and Investigations at the NYPD (2018-2020), Selby led cybercrime investigations for America's largest police department. Selby serves on the Board of Directors of the non-profit National Child Protection Task Force and the advisory board of Sightline Security. While retired from law enforcement, he continues to serve as a reserve detective for a Dallas-Fort Worth area police agency, where he investigates crimes against children and the cyber aspects of real-world crimes.

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.

Today, we're talking to Fredrik Carlegren, VP & Head of Marketing & Communications, and Yeshai Bouskila, Executive Director Retail Innovation at Toshiba Global Commerce Solutions. We discuss the best ways to manage tech debt, why rigid systems block innovation, and how AI is impacting the technology of frictionless grocery stores. All of this right here, right now, on the Modern CTO Podcast!  To learn more about Toshiba Global Commerce Solutions, check out their website her

Miska's usual jetset life hits a snag when he misses Kress' Subnotica correction. Adam calls in from his cottage to lay down the law on Merge history, while Phil gushes over $500m in capital deployment. Eric details Ubisoft's reality TV show attempt at Succession, and Jen delivers the 411 on Apple's hypercasual attempt. The group pours one out for a very special Candy Crush anniversary.01:58 Gaming News Highlights02:42 Personal Updates05:33 Remembering the Mario Lopez Candy Crush Show07:52 Subnautica and Crafton Legal Drama10:37 App Charge Sponsorship and Insights14:40 Ubisoft Earnings and Family Drama22:44 Battlefield 6 Trailer and Expectations24:57 Call of Duty's Tech Debt and Battlefield's Response26:24 Battlefield 6 Release Date and Editions Leak28:31 Challenges and Risks for Battlefield 638:03 Supervi's Full Launch and Market Challenges40:05 Splitgate 2's Struggles and Relaunch43:09 Wild Gate's Launch and Marketing Issues46:58 Apple's Emoji-Based Puzzle Game49:39 Conclusion and Sign-Off

Today's episode is about technical debt, not as a cautionary tale, but as a lens. We take a closer look at where debt comes from, how it quietly rewires teams, and why paying it off is rarely just a matter of “cleaning up code.” Along the way, we'll examine two real-world stories: one where unaddressed debt led to a $440 million disaster, and another where a company used an infrastructure overhaul to rebuild architectural trust. This is about more than code. It's about momentum, memory, and the systems we inherit.

Many Ecommerce brands believe their customer journey is optimized, but are they leaving significant revenue and trust on the table without even knowing it? From a clunky checkout to hidden technical debt, seemingly small issues can quietly erode profits and customer loyalty.In this episode of Deal Closers, we chat with Sarah Gallagher, CEO and Head of Strategy at Gamma Waves. Sarah has helped major brands like Nike and Airbnb, as well as fast-growing startups, build smarter Ecommerce foundations. She dives into how to create strategic checkout experiences, identify and eliminate hidden tech debt, and build scalable Ecommerce systems that drive growth.You'll learn:Why a "good enough" checkout experience is actually a major revenue leakHow to leverage the checkout process to build trust with new customersPractical strategies for "smarter upsells" that feel valuable, not "icky"What "technical debt" is and how it can silently sabotage your site's performanceA real-world case study of a 37% conversion rate increase by simply cleaning up backend codeWhy AB testing is critically underutilized in Ecommerce and where to startThe growing importance of "circular commerce" and how brands are owning the resale marketHow to get your hands around your data to unlock powerful insightsTimestamps:00:00:00 – The critical importance of understanding your data00:00:30 – Introduction to Sarah Gallagher: The unsung hero of the customer journey00:01:30 – Sarah's journey into digital commerce: From early 2000s to Gamma Waves00:02:00 – Building the first Shaq Ecommerce site and Sony Latin America00:04:00 – The evolving nature of Ecommerce and why customer experience always wins00:05:00 – Why your checkout experience is a major revenue opportunity00:06:00 – Building trust signals at checkout for new customers00:07:00 – Case studies: Optimizing checkout for Flight Club and Supergoop00:08:00 – Using AB testing to uncover hidden opportunities (and biases)00:11:00 – The surprising results of an AB test: Percent vs. Dollar savings00:12:00 – Implementing "smarter upsells" that genuinely add value00:15:00 – Understanding and eliminating technical debt in your Ecommerce site00:17:00 – The 37% conversion rate increase from a simple backend cleanup00:19:00 – Why site audits are often neglected and their hidden value00:20:00 – Long-term strategic planning and the concept of "circular commerce"00:24:00 – The biggest "money leaks" in Ecommerce: Tech debt and lack of AB testing00:25:00 – Where to start with AB testing for maximum impact00:27:00 – What's next for Ecommerce brands: Getting a handle on their data00:29:00 – How AI can help pull insights from clean data00:30:00 – Connecting with Sarah Gallagher and Gamma WavesConnect with Sarah Gallagher:Website: gammawaves.ioLinkedIn: Sarah GallagherDeal Closers is brought to you by WebsiteClosers.com and produced by Walk West. Hosted on Acast. See acast.com/privacy for more information.

Welcome to the podcast featuring Hope Gurion, an esteemed product leadership coach. She is recommended by Marty Cagan in his book, Transformed, has moderated product leadership councils with Phyl Terry's Collaborative Gain, and works with Teresa Torres in training teams on Continuous Discovery Habits. In this episode, Hope delves into her extensive background in product management, sharing insights from over 25 years in the tech industry, her roles as Chief Product Officer, and SVP of Product. She discusses her transition from consulting to coaching, offering valuable guidance on becoming outcome-oriented and enhancing team effectiveness. Hope covers the challenges of finding the right company fit, the nuances between training and coaching, and key strategies for cross-functional collaboration. Tune in for actionable advice on elevating your product management career.00:00 Introduction and Welcome00:39 Hope Gurion's Background01:54 Transition to Coaching03:37 Challenges in Product Leadership04:55 Coaching and Training Approach07:25 Importance of Discovery in Product Management09:47 Balancing Training and Coaching15:57 Selecting the Right Coach18:51 Defining Success in Product Leadership21:33 Peer-Based Coaching vs. One-on-One Coaching28:23 Transformation in Organizations39:57 Podcast Origin Story and Conclusion

In this episode, Amir sits down with Brent Keator, an expert advisor at Primary Venture Partners, to unpack one of the most debated engineering challenges: tech debt versus reengineering. They explore how to define tech debt, when to refactor versus rebuild, the ROI of revisiting old code, and how AI is (and isn't) changing the equation. This is a must-listen for engineering leaders navigating complex technical decisions in fast-moving environments.

In this episode of Autonomous IT, Live!, Landon Miles hosts leads a three-part discussion focused on spring cleaning your IT systems, workflows, and personal well-being. You'll hear candid, practical insights from IT professionals tackling burnout, technical debt, and infrastructure hygiene head-on.This live show originally aired April 16, 2025  

Russ Mikowski, CEO of SurePeople and longtime revenue leader intech, never planned to become a CEO, until he was recruited to transform a 10-year-old company grappling with technical debt, a scattered ICP, and untapped potential. In this episode of Topline Spotlight, Russ opens up about the tough decisions he's made since taking the helm: rebuilding instead of refactoring, saying "no" to legacy customers, and doubling down on a focused go-to-market strategy for SurePeople's innovative psychometric assessment platform, Prism.You're invited! Join the free Topline Slack channel to connect with 600+ revenue leaders, share insights, and keep the conversation going beyond the podcast!Subscribe to the Topline Newsletter to get the latest industry developments and emerging go-to-market trends delivered to your inbox every Thursday.Tune into The Revenue Leadership Podcast with Kyle Norton every Wednesday. Kyle dives deep into the strategies and tactics that drive success for revenue leaders like Jason Lemkins of SaaStr, Stevie Case of Vanta, and Ron Gabrisko of Databricks.Key Moments:(00:00) Introduction to Topline Spotlight(03:00) Understanding SurePeople and Its Mission(05:51) Russ's Journey to CEO and Company History(08:55) Navigating Technical Debt and Product Development(12:01) Defining Ideal Customer Profile (ICP) and Market Focus(14:50) Company Culture and Communication Strategies(17:53) Inspiration and Leadership Philosophy

Spring is in the air, and it's time to give your IT environment the deep clean it deserves! In this episode of Hands-On IT, host Landon Miles shares nine essential spring cleaning tips to help IT pros declutter, optimize, and future-proof their systems. From cleaning workspaces and dusting off hardware to reviewing patch policies, auditing backups, and addressing tech debt, Landon walks you through practical steps that will boost efficiency, enhance security, and set you up for a smoother year ahead. Tune in and learn how a little proactive maintenance today can save you countless hours of reactive troubleshooting tomorrow!Clean Your Desk and WorkspaceDust Off Your Hardware and Check for WearUntangle and Manage CablesReview Patch PoliciesPurge Old Accounts and Review Software ContractsDeclutter Local Systems and StorageAudit and Test Your BackupsReview Digital and Hardware Tech DebtUpdate Your Documentation and Refresh Policies

In this episode, Dave and Jamison answer these questions: Nearly every time certain developers on the team want to address technical debt, they end up just adding more technical debt. Of course, after one round of addressing technical debt, the developers in question believe that yet another round of redesigning and refactoring is in order. This stresses me out for many reasons, as you can imagine, and has led to my productivity dropping to an abysmal rate. I spend a large chunk my time resolving merge conflicts and re-orienting myself in an ever-changing codebase. Do you have any suggestions for me? Hi! I'm a software engineer at a big tech company, and I'm starting to feel siloed in my IC role. I'm getting my work done, but I'm often lost when it comes to the bigger picture. I can't keep up with what our internal customer teams are doing, what they need, or even what my own team's priorities are. I'm feeling siloed, and it's starting to worry me. I know that just being a good IC isn't enough to advance my career here. To get promoted, I need to understand the impact of my work, be aligned with the team and customer goals, and show that I can contribute to the overall success of the company. But how can I do it? How do I stay informed about customer needs and team priorities and position myself for career growth without getting completely overwhelmed? Thank you for your precious advice!

We're bringing back one of our favorite conversations — and for good reason: Noibu is a trusted partner of Mejuri. In this episode, we revisit our insightful chat with Rohit Nathany, Chief Product and Technology Officer at Mejuri, the leading fine jewelry brand redefining ecommerce. Rohit dives into how his team transitioned from a custom tech stack to Shopify, launched a loyalty-driven mobile app, and built a high-performing internal tech culture that fuels fast, focused innovation. Whether you missed it the first time or just want a fresh take, tune in for sharp insights on balancing speed, scale, and strategy in modern ecommerce.

ABOUT FUNMI OLUDAIYEFunmi is a Managing Director and the Head of the Digital Risk Office for Enterprise Partnerships at Goldman Sachs, where she is pioneering a first-of-its-kind global initiative to embed critical business, security, and engineering risk practices within the engineering organization. With nearly 15 years of experience as a software engineer, architect, and engineering manager, she has a proven track record of leading high-performing teams, delivering innovative technology solutions, and championing best practices in developer experience and productivity across large-scale engineering teams. Most recently, she was the Head of Engineering for Consumer Deposits at Marcus by Goldman Sachs, and prior to that, she led the product engineering teams that built and launched the firm's award-winning credit card partnerships with Apple and later, General Motors. Funmi is a passionate advocate for underrepresented groups in the technology industry and is committed to mentoring the next generation of engineering leaders. Her wealth of experience and dedication to driving positive change make her a sought-after speaker and advisor.ABOUT KETAN GUPTAKetan is a seasoned engineering leader with 13+ years in software development, cloud, architecture, product delivery, and organizational leadership. He excels at building high-performing engineering teams and driving strategic initiatives. As an active community builder, he contributes to the Engineering Leaders Community and champions software craftsmanship.ABOUT SASHA HALLSasha Hall is an Engineering Manager at Planitar Inc, makers of iGUIDE. A University of Waterloo graduate with over 5 years of leadership experience at Pegasus Aeronautics and Deep Trekker, Sasha brings valuable insights on decisive leadership, effective communication, and strategic vision in growing organizations. Their career path through underwater robotics at Deep Trekker, aerial drone systems at Pegasus Aeronautics, and spatial mapping technologies at Planitar showcases a passion for innovative hardware and sensing solutions. This diverse technical background, combined with consistent leadership dedication, has equipped Sasha with a unique perspective on navigating today's complex engineering challenges. Build AI Voice Agents with ElevenLabsElevenLabs is the leading Voice AI platform for developers with thousands of ultra-realistic, human-like voices across 32 languages.Developers use ElevenLabs to build life-like, conversational AI voice agents to handle customer support queries, appointment scheduling, and even offer personalized 1-1 tutoring.Get started for free at elevenlabs.io/elc SHOW NOTES:Funmi discusses why successful eng leaders build true partnerships between engineering & business stakeholders (1:58)Navigating the dynamics of engineering & cross-functional team partnerships (3:00)Creating alignment / building relationships through fostering trust & curiosity (4:42)How engaging w/ curiosity is key to building cross-functional relationships (7:21)Funmi's framework to help identify gaps in understanding (8:56)Recognizing knowledge gaps and relying on subject matter experts (10:15)Tips for navigating partnerships with multiple stakeholders (13:14)What's going on with ELC New York & the power of connecting with eng leaders (14:45)Ketan discusses cloud transformation and AI integration (17:08)Considering challenges w/ security, scalability, cost, flexibility & AI in cloud vs. hybrid migrations (18:04)Explaining the impact of technical debt on organizations (20:04)The STIR framework for managing tech debt during cloud migrations (21:17)Translating tech debt into business value w/ STIR (24:17)Separating continuous improvement / performance from tech debt (27:02)Understanding team strengths & bolstering team motivation (29:24)Ketan's experience with ELC London (31:07)Have fun with decision-making (33:29)Sasha discusses optimizing team processes amid company growth & new hires (35:11)Effective decision-making - balancing being decisive & thoughtful (37:36)Examples of balancing quick decision-making w/ thoughtfulness (39:05)How to refactor repetitive tasks to improve efficiency (40:32)Balancing time, risk & impact in decision-making processes (42:06)The value of building a network & finding mentors outside your own company (45:03)Advice for jumping into ELC community events (47:41)This episode wouldn't have been possible without the help of our incredible production team:Patrick Gallagher - Producer & Co-HostJerry Li - Co-HostNoah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/

Wie geht man die Quartals- und Jahresplanung an und balanciert verschiedene Anforderungen?Für viele ist es ein langweiliges und notwendiges Übel. Für andere die beste Zeit des Jahres - Die Quartals- bzw. Jahresplanung. Firmen lieben es zu planen. Firmen lieben es, den Kunden neue Features zu versprechen. Produktmanager können endlich alles in die nächsten 3 Monate einordnen, dann wird das gemacht und die Welt ist wieder in Ordnung.Am Ende des Quartals fragt man sich dann aber: Wieso hat das alles so lange gedauert? Wieso haben wir für Feature X 2 Wochen geplant, aber es wurden 6 Wochen draus? Wieso werden wir bei der Software-Entwicklung langsamer und nicht schneller? Das ist ein bekanntes Bild in vielen Firmen, denn oft findet die Stimme der Software-Entwickler*innen keinen Platz in der Planung.Technical Debt abbauen? Machen wir nächstes Quartal. Was für die eigene Team-Produktivität tun, um manuelle Aufgaben zu automatisieren? Das lohnt sich nicht. Kleine Bugs, sogenannte Papercuts, fixen um die Power-User glücklich zu machen? Zu klein, machen wir nebenher. Software updaten? Das ist Keep The Lights On Arbeit und kann doch Ops machen. So oder so ähnlich trägt es sich alle 3 Monate in Firmen zu.In dieser Episode geben wir euch mal ein paar Leitfragen und ein spezifisches Framework an die Hand, wie man die Software-Entwicklungs-Ressourcen gut über das nächste Quartal balanciert, es genug Features in die Roadmap schaffen, aber auch Zeit für Tech Debt und Produktivitätsverbesserungen bleibt. Dabei klären wir, warum eine gewisse Planung eigentlich so wichtig ist, wer eigentlich immer die ganzen Anforderungen auf den Tisch knallt, was Over-Commitments und Rollovers sind, wie Ubuntu und Github mit Mission Papercut kleine Bugs zu einem großen Projekt gemacht hat aber auch warum eine Quartalsplanung in die Bereiche KTLO, Build New Stuff, Improve Stuff und Productivity eingeteilt werden sollte.Das Thema klingt trocken. Dennoch kann dies euch eine Stimme im Planungsprozess geben, damit ihr endlich mal Zeug aufräumen könnt.Bonus: Ist Jira das neue ERP-System?Unsere aktuellen Werbepartner findest du auf https://engineeringkiosk.dev/partnersDas schnelle Feedback zur Episode:

Kevin Scott is the CTO of Microsoft, where he leads the company's AI and technology strategy at global scale and played a pivotal role in Microsoft's partnership with OpenAI. Prior to Microsoft, Kevin spent six years at Linkedin as SVP of Engineering. Kevin has also enjoyed advisory positions with Pinterest, Box, Code.org and more.  In Today's Episode We Discuss: 04:10 Where is Enduring Value in a World of AI 10:53 Why Scaling Laws are BS 12:26 What is the Bottleneck Today: Data, Compute or Algorithms 15:38: In 10 Years Time: What % of Data Usage will be Synthetic 20:04 How Will AI Agents Evolve Over the Next Five Years 23:34: Deepseek Evalution: Do We Underestimate China 28:34 The Future of Software Development 31:53 The Thing That Most Excites Me in AI is Tech Debt 35:01 Leadership Lessons from Satya Nadella 41:13 Quickfire Round  

On this episode of the Hedge, Eyvonne, Tom, and Russ talk about topics near and dear to every network engineer's heart--documentation, legacy, and tech debt. What should our philosophy of documentation be? What are legacy, end of life, and tech debt, really?

Luca Casanato, member of the Deno core team, delves into the intricacies of debugging applications using Deno and OpenTelemetry. Discover how Deno's native integration with OpenTelemetry enhances application performance monitoring, simplifies instrumentation compared to Node.js, and unlocks new insights for developers! Links https://lcas.dev https://x.com/lcasdev https://github.com/lucacasonato https://mastodon.social/@lcasdev https://www.linkedin.com/in/luca-casonato-15946b156 We want to hear from you! How did you find us? Did you see us on Twitter? In a newsletter? Or maybe we were recommended by a friend? Let us know by sending an email to our producer, Emily, at emily.kochanekketner@logrocket.com (mailto:emily.kochanekketner@logrocket.com), or tweet at us at PodRocketPod (https://twitter.com/PodRocketpod). Follow us. Get free stickers. Follow us on Apple Podcasts, fill out this form (https://podrocket.logrocket.com/get-podrocket-stickers), and we'll send you free PodRocket stickers! What does LogRocket do? LogRocket provides AI-first session replay and analytics that surfaces the UX and technical issues impacting user experiences. Start understand where your users are struggling by trying it for free at [LogRocket.com]. Try LogRocket for free today.(https://logrocket.com/signup/?pdr) Special Guest: Luca Casonato.

Heimir Thor Sverrisson joins Robby to discuss the importance of software architecture in long-term maintainability. With over four decades in the industry, Heimir has witnessed firsthand how poor architectural decisions can set teams up for failure. He shares his experiences mentoring engineers, tackling technical debt, and solving large-scale performance problems—including one bank's misguided attempt to fix system slowness by simply adding more CPUs.Heimir also discusses his work at MojoTech, the value of code reviews in consulting, and his volunteer efforts designing radiation-tolerant software for satellites.Episode Highlights[00:01:12] Why architecture is the foundation of maintainability – Heimir explains why starting with the wrong architecture dooms software projects.[00:02:20] Upfront design vs. agile methodologies – The tension between planning and iterative development.[00:03:33] When architecture becomes the problem – How business pivots can render initial designs obsolete.[00:05:06] The rising demand for rapid software delivery – Why modern projects have less time for deep architectural planning.[00:06:15] Defining technical debt in practical terms – How to clean up code without waiting for permission.[00:09:56] The rewrite that never launched – What happens when a company cancels a multi-million-dollar software project.[00:12:43] How a major bank tackled system slowness the wrong way – Adding CPUs didn't solve their performance problems.[00:15:00] Performance tuning as an ongoing process – Why fixing one bottleneck only reveals the next.[00:22:34] How MojoTech mentors instead of manages – Heimir explains how their consultancy approaches team development.[00:27:54] Building software for space – How AMSAT develops radiation-resistant software for satellites.[00:32:52] Staying relevant after four decades in tech – The power of curiosity in a constantly changing industry.[00:34:26] How AI might (or might not) help maintainable software – Heimir shares his cautious optimism.[00:37:14] Non-technical book recommendation – The Man Who Broke Capitalism and its relevance to the tech industry.Resources & LinksHeimir Thor Sverrisson on LinkedInHeimir's GitHubMojoTechAMSAT – Amateur Radio Satellite OrganizationThe Man Who Broke CapitalismHow to Make Things Faster

Highlights from this week's conversation include:The Return of the Cynical Data Guy (0:14)Risks of SQL Complexity (2:16)Technical Debt in Data (4:34)Data Mesh Critique (6:38)Governance vs. Decentralization (9:55)Never Let a Stakeholder Tell You They Need a Dashboard (12:05)Dashboard vs. Table (13:34)Organizational Dynamics in Data Requests (16:35)AI and Prompt Writing (19:43)Search Techniques and User Behavior (21:20)Discussion on Code Optimization Tools (23:19)Final Thoughts and Takeaways (24:47)The Data Stack Show is a weekly podcast powered by RudderStack, the CDP for developers. Each week we'll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit rudderstack.com.

This is the 7th episode of season four. I started this season in January of 2024. My intent was to document the process of writing a book. But even though this season is over a year long, there have only been 7 episodes, and that's because I took a 9 month break. I want to talk more about what happened during that break, and how I was derailed from my plans, and how I recovered. The Four Disciplines of Execution [affiliate link] On Writing Well [affiliate link] by William Zinsser Swimming in Tech Debt (my book) Help This Book (book sharing platform) Useful Books Community Transcript

“Looking at the development pace of this area, it's just a question of when generative AI will take over larger parts of software engineering. It's a leadership responsibility to ensure your organization is ready for AI and you are taking the right path.” AI is changing EVERYTHING – including the way we build software. Are you READY for it? In this episode, we dive deep into the impact of AI on the future of work, particularly in the software development space. Join me and André Neubauer as we explore: * The evolution of AI: From early code generation to today's advanced Generative AI and Large Language Models (LLMs). * The rise of Agentic AI: How AI agents are collaborating to automate complex tasks and reshape software development workflows. * The impact on organizations: How companies can leverage AI to boost productivity, foster innovation, and navigate the challenges of this new era. * The future of software teams: Will AI replace developers or empower them? Discover why smaller, leaner, high-performing teams might be the way forward. * Leadership in the age of AI: Essential strategies for leaders to successfully integrate AI into their organizations and address the concerns of their teams. Listen out for: (00:02:11) Career Turning Points (00:07:56) Giving a Talk on “The Role of AI in Future Workplaces” (00:10:30) What Drives the AI Advancements (00:18:54) The Levels of AI Advancement (00:25:01) AI in Software Engineering (00:26:53) Concerns on Tech Debt and Issues (00:31:11) Impact of AI to Organizations (00:34:34) Smaller and Leaner Teams (00:37:15) The Rise of Solopreneurship (00:41:32) Getting People Onboard to AI (00:44:40) Leadership Measures for Adopting AI (00:49:34) 3 Tech Lead Wisdom _____ André Neubauer's Bio For nearly two decades, André Neubauer has shaped Tech & Product and its interface with the business in varied settings, from startups to major corporations. His journey began in software engineering and evolved into technical leadership, a role he's passionately undertaken for the past 15 years. As CTO, he's spearheaded transformative projects and strategies, backed by an academic foundation in informatics and business economics. Always at the forefront of modern leadership practices, he's transformed companies into tech powerhouses. Beyond his role as CTO, he actively mentors tech leaders and consults businesses, guiding them through their tech challenges. Follow Andre: * LinkedIn – linkedin.com/in/andreneubauer * Newsletter – devpg.substack.com _____ Our Sponsors Enjoy an exceptional developer experience with JetBrains. Whatever programming language and technology you use, JetBrains IDEs provide the tools you need to go beyond simple code editing and excel as a developer.Check out FREE coding software options and special offers on jetbrains.com/store/#discounts.Make it happen. With code. Manning Publications is a premier publisher of technical books on computer and software development topics for both experienced developers and new learners alike. Manning prides itself on being independently owned and operated, and for paving the way for innovative initiatives, such as early access book content and protection-free PDF formats that are now industry standard.Get a 40% discount for Tech Lead Journal listeners by using the code techlead24 for all products in all formats. Like this episode?Show notes & transcript: techleadjournal.dev/episodes/202.Follow @techleadjournal on LinkedIn, Twitter, and Instagram.Buy me a coffee or become a patron.

Thomas Mulreid is the VP of Sales at Orium and he was Kailin Noivo's latest guest on Ecommerce Toolbox: Expert Perspectives. Thomas shared his journey from finance through the tech world, and eventually landed at Orium, just at the very moment that the pandemic started to reshape how we work. Now, he's an expert in the changes that are reshaping the world of ecommerce: headless and composable commerce. In this conversation, Thomas reflects on how Orium has helped brands to quickly create tailored digital experiences with cutting-edge composable strategies. They also explore the pivotal role of MACH architecture in building the sort of flexible solutions that can adapt as businesses grow. Tune in to hear practical advice and learn how innovation and best practices are shaping the future of online shopping.

Check out the full episode on https://www.techtables.com/podcast/182/frank-sweeney-beth-neeley Featuring: - Frank Sweeney, CIO, Arizona Department of Child Safety - Beth Neeley, CIO, Arizona Department of Education In this episode, you'll learn: - How Frank Sweeney transformed DCS's Guardian system from 2 releases to 46 successful deployments in 10 months - Why the Arizona Department of Education's $9M school finance payment system succeeded through strategic stakeholder collaboration - How the Department of Education achieved unprecedented financial transparency and reduced technology debt by $500,000 - The power of authentic leadership and being present in driving organizational transformation - Why strategic team placement and a culture of gratitude are critical success factors in public sector IT Timestamps: (00:00) Welcome and Introductions (01:41) Frank's transition strategy: People, process, and culture at DCS (04:52) Beth's journey: Leading the Department of Education transformation (09:06) Building a culture of gratitude and breaking down bureaucratic barriers (14:07) Success story: Department of Education's $9M payment system overhaul (18:54) DCS transformation: From Guardian system challenges to 46 deployments (22:42) Leadership insights: EOS framework and strategic team placement (25:37) Key leadership lessons: The power of being present and authentic • Frank Sweeney: https://www.linkedin.com/in/frank-sweeney-iot/ • Beth Neeley: https://www.linkedin.com/in/elizabeth-neeley-687099222/ Whenever you're ready, there are 4 ways you can connect with TechTables: 1.

Evan Doyle says AI makes tech debt more expensive, Hunter Ng researches the ghost job ad phenomenon, Gavin Anderegg analyzes Bluesky in light of its recent success, Martin Tournoij rants against best practices & Evan Schwartz tells us why he thinks binary vector embeddings are so cool.

Evan Doyle says AI makes tech debt more expensive, Hunter Ng researches the ghost job ad phenomenon, Gavin Anderegg analyzes Bluesky in light of its recent success, Martin Tournoij rants against best practices & Evan Schwartz tells us why he thinks binary vector embeddings are so cool.

Evan Doyle says AI makes tech debt more expensive, Hunter Ng researches the ghost job ad phenomenon, Gavin Anderegg analyzes Bluesky in light of its recent success, Martin Tournoij rants against best practices & Evan Schwartz tells us why he thinks binary vector embeddings are so cool.

Join us as we sit down with Jordan Kaye, the Head of Technology at Belvedere Trading, to unpack the true nature of technical debt and its broader implications. In this episode, we delve into the delicate balance between managing tech debt and delivering business value, the impact of evolving technology on past decisions, and practical ways to enhance efficiency without compromising quality.  Discover how to achieve flexibility and velocity in Agile development, the importance of intentional, business-aligned decisions, and the benefits of high team autonomy. Jordan shares his unique perspectives on quantifying and visualizing technical debt, effective project scoping, and conscious management.  Gain valuable insights into navigating the complex landscape of tech debt and technological evolution.  Don't forget to like, subscribe, and share this insightful conversation with your network. Highlights: 01:29 Defining Technical Debt 04:00 Quantifying and Managing Tech Debt 06:23 Tech Debt in Different Departments 09:06 The Evolution of Technology and Tech Debt 13:04 Balancing Business Needs and Engineering Discretion 13:58 The Challenge of Replicating Success 14:15 Conscious Decision-Making in Engineering 15:12 The Pareto Principle in Engineering 15:54 Empowering Teams with Business Understanding 18:09 Flexibility Over Correctness 19:47 The Art of Balancing Quality and Speed 21:23 Avoiding Premature Problem Solving 24:00 Just-in-Time Scoping Guest:

I've seen a TON of horror stories with tech debt and code migrations. It's estimated that 15% to 60% of every dollar in IT spend goes toward tech debt (that's a big range, I know). Regardless, most of this tech debt will not be paid down without a radical change in how we do things. Might AI be the Hail Mary we need to pay down tech debt? I don't see why not... My works:

My wife and I have been thinking about some new audio equipment. We've been a little unhappy with our Bose soundbar because of the software flakiness and sporadic network connectivity issues. In looking around, I saw a Sonos product, but after reading a bit about the company's recent history, I decided to look elsewhere. Sidebar: if any of you have recommendations that aren't high-end $$$$ audio, let me know. Read the rest of Tech Debt Perils

In this podcast episode, the host interviews Brian Young, Director of Engineering at Grindr, about the concepts of scale and tech debt in the tech industry. Brian shares insights from his career at major companies like Wayfair and Amazon, highlighting the unique challenges each faced with scaling their systems. He explains the CAP theorem and its implications on consistency, availability, and partition tolerance within large-scale applications. The conversation also delves into the balance of art and science required in scaling, the significance of 'YAGNI' in software design, and the necessity of revisiting technical debt. Brian discusses how contextual understanding is vital for addressing tech debt and explores new technologies like AI-assisted coding tools, which may aid in managing tech debt in the future. Highlights: 00:47 Understanding Scale in Tech 02:48 Designing for Scale at Amazon 05:20 Scaling Strategies at Grindr 06:31 The Art and Science of Scaling 09:59 Technical Debt: A Necessary Evil? 17:53 The Role of Context in Software Engineering 20:50 Future of Tech Debt and AI Solutions Guest: Brian Young (he/him) is Director of Engineering at Grindr, the number 1 social network for the LGBTQ+ community. With more than 13 million monthly active users in virtually every country, Grindr has become a fundamental part of the LGBTQ+ community since its launch in 2009. The company continues to expand its ecosystem to enable gay, bi, trans, and queer people to connect, express themselves, and discover the world around them. Brian has spent 25 years in the software industry as an engineer and leader and has worked at large companies, including Amazon and Wayfair, and start-ups. Brian has built high-scale / low-latency distributed systems, microservices, backend solutions, web apps, and mobile apps and worked in almost every tech stack from dcom and dll hell to modern cloud-based microservices. LinkedIn: https://www.linkedin.com/in/briankyoung/ ---- Thank you so much for checking out this episode of The Tech Trek. We would appreciate it if you would take a minute to rate and review us on your favorite podcast player. Want to learn more about us? Head over at https://www.elevano.com Have questions or want to cover specific topics with our future guests? Please message me at https://www.linkedin.com/in/amirbormand (Amir Bormand)

BONUS: Mastering Product Management in a Remote World, Insights from Tuple's Head of Product, Eli Goodman NOTE: We want to thank the folks at Tuple.app for being so generous with their stories, and supporting the podcast. Visit tuple.app/scrum and share them if you find the app useful! Remember, sharing is caring!   In this episode, Eli Goodman, Head of Product at Tuple, shares insights from his extensive experience in software development and product management. Having transitioned from engineering management to product leadership, Eli reveals the key strategies Tuple uses to develop its remote pair programming service, which is trusted by companies like Figma and Shopify. Tune in to discover how Tuple handles remote team dynamics, customer-driven development, and balances tech debt with client needs, all while maintaining a customer-centric focus. Introduction to Tuple and Why It's Unique Tuple, a remote pair programming service designed by engineers, solves a pain point that its founders, all pairing enthusiasts, experienced firsthand. They were unsatisfied with generic screen-sharing tools that disrupted the flow of coding collaboration. Tuple's product philosophy is about staying "one inch wide, one mile deep" to ensure the tool stays focused on enhancing the pairing experience without getting in the way. "The details matter. Generic screen-sharing tools just don't cut it for productive pairing." Managing a Remote Team at Tuple Managing a distributed team across the U.S. and Europe comes with its challenges. Eli highlights the importance of alignment and ensuring everyone is on the same page, despite working remotely. He emphasizes the role of Product Owners as "connective tissue" and the power of connecting team members with key initiatives. Through personal conversations, Eli uncovers what motivates his team, allowing him to support them without micromanaging. "What makes you proud? What brings you shame? Understanding these emotions helps uncover what drives our team." Ensuring Effective Communication in a Remote Environment Effective communication is the backbone of remote work, and Eli shares some of the practices that have helped Tuple's team stay aligned and collaborative. From using spontaneous pairing sessions to fostering a culture of checking in, Tuple has created a remote work environment where conversations are naturally sparked, and collaboration is effortless. "We have more space in our schedules for spontaneous pairing, which keeps collaboration flowing." Lessons Learned from Pairing Remotely One of the key insights Eli shares is how Tuple has evolved its remote pairing process. In the past, pairing might have felt like a formal meeting, but now it happens more spontaneously. Tuple's app facilitates this by offering the metaphor of a phone call—engineers can call each other at any time, making collaboration easy, especially when someone is deep into a task and needs quick support. "At Tuple, engineers only have three meetings a week, leaving the rest of the time open for pairing and creative work." Pairing Beyond Programming Tasks While pairing is typically associated with programming, Eli explains how Tuple uses pairing for other activities, like design or planning sessions. This practice has extended beyond coding, fostering a culture where team members collaborate on various tasks that benefit from shared perspectives and live problem-solving. "We've expanded pairing beyond coding, using it for activities like design reviews and project planning." Balancing Customer Feedback with Product Vision Responding to customer feedback is vital, but it can also lead to losing focus. Eli explains how Tuple balances this by capturing as much feedback as possible, using tools like Product Board to keep track of customer requests. However, instead of building every requested feature, Eli focuses on synthesizing broader patterns and emotional triggers that align with Tuple's long-term vision. "Focus on discovery as a product person. Understand the emotional context behind customer feedback—that's what drives great products." Tuple's Ideal Customer and Core Value Tuple's ideal customers are teams that value deep collaboration through pair programming. The platform's most important offering is the ability to make remote pairing seamless and intuitive, something traditional tools fail to deliver. "Tuple is built for teams that believe in the power of collaboration and want a tool that enhances their pairing experience, not disrupts it." Roadmapping: How to Prioritize the Right Work in Product Development Looking ahead, Eli shares Tuple's plans to continue investing in quality and lowering the barriers to remote pairing. One exciting potential direction includes creating a "social layer" within the app to help users feel more connected with their teammates. Another idea is incorporating non-human pairing agents that could assist with specific tasks. "We want to see if we can make it feel like you're right there with your teammates, lowering the barriers to start pairing." Recommended Resources Eli recommends The Mom Test by Rob Fitzpatrick, a must-read for anyone working in product management. The book teaches how to talk to customers in a way that gets honest, useful feedback rather than polite responses that don't help improve the product. "I thought caring about people was enough to talk to customers, but The Mom Test taught me what not to do during customer interviews." About Eli Goodman Eli Goodman has been working on software teams for 17 years. He's been a full-stack developer and engineering manager at both large and small companies, including Etsy and Headspace. A few years ago, Eli transitioned to product management and is now the Head of Product at Tuple, a remote pair programming service used by companies such as Figma, Shopify, and many others in the software industry. You can link with Eli Goodman on LinkedIn, or email Eli at Eli@Tuple.app.

Considerations in paying down tech debt, make Rust work on bare metal, ECDSA side-channel in Yubikeys, trade-offs in deploying SSO quickly, and more! Visit https://www.securityweekly.com/asw for all the latest episodes! Show Notes: https://securityweekly.com/asw-298

Considerations in paying down tech debt, make Rust work on bare metal, ECDSA side-channel in Yubikeys, trade-offs in deploying SSO quickly, and more! Show Notes: https://securityweekly.com/asw-298

Considerations in paying down tech debt, make Rust work on bare metal, ECDSA side-channel in Yubikeys, trade-offs in deploying SSO quickly, and more! Visit https://www.securityweekly.com/asw for all the latest episodes! Show Notes: https://securityweekly.com/asw-298

In this podcast episode, we explore critical technical decisions and the concept of technical debt with Brian Moseley, Co-Founder and CTO of Sixfold. Brian discusses his views on balancing short-term goals with long-term ramifications, including real-life examples from his work. The conversation delves into the use of generative AI in insurance underwriting, the importance of context in decision-making, and the challenge of remote work collaboration. Brian stresses the need for documenting reasoning and decisions to avoid future misunderstandings and highlights the role of whiteboard sessions in accelerating productive outcomes. The episode comprehensively discusses making informed and contextually aware technical choices. Highlights: 01:28 Understanding Technical Debt 02:38 Real-World Examples of Technical Debt 05:47 The Importance of Context in Decision Making 08:38 Asynchronous Communication and Documentation 16:30 Challenges of Remote Collaboration ---- Thank you so much for checking out this episode of The Tech Trek. We would appreciate it if you would take a minute to rate and review us on your favorite podcast player. Want to learn more about us? Head over at https://www.elevano.com Have questions or want to cover specific topics with our future guests? Please message me at https://www.linkedin.com/in/amirbormand (Amir Bormand)

Christian Hammer is a tech optimist and the dynamic CEO of Vala AI, spearheading innovation at the intersection of artificial intelligence and enterprise solutions. With a career spanning decades across global powerhouses like Wayfair, Nike, Appnexus, and Maersk, Christian has consistently been at the forefront of digital transformation, leaving an indelible mark on the tech landscape. In this conversation, we explored his insights into merging artistic creativity with technological innovation, Vala AI's mission to streamline information within businesses, and his optimistic views on future technologies like genetic manipulation and robotics. Key topics include the intersection of art and technology, the future of software development, and the evolution of human-computer interaction. EPISODE LINKS: Christian Hammer LinkedIn: https://www.linkedin.com/in/chammer1/ Christian Hammer Podcast: http://podcast.techtastic.tech/ Christian Hammer Website: https://christianhammer.io/ Christian Hammer Artwork: https://c-hammer.com/ Vala AI: https://vala-ai.com TIMESTAMPS: 00:00:12 Intro and background 00:00:45 Technology and art 00:01:59 The Intersection of Art and Coding 00:05:29 Process of Creating Art vs Coding 00:08:00 Building solutions and value creation 00:09:33 Vala AI Evolution, Tech Debt and Data Dictionary 00:17:31 Vala AI Use Case Scenario 00:20:07 Future of Software Development and AI 00:25:11 Future of Aplication Interaction 00:28:22 Technological Optimism and Future Innovations 00:33:08 Sci-Fi Recommendations 00:34:30 Closing CONNECT: Website: https://hoo.be/elijahmurray YouTube: https://www.youtube.com/@elijahmurray Twitter: https://twitter.com/elijahmurray Instagram: https://www.instagram.com/elijahmurray LinkedIn: https://www.linkedin.com/in/elijahmurray/ Apple Podcasts: https://podcasts.apple.com/us/podcast/the-long-game-w-elijah-murray/ Spotify: https://podcasters.spotify.com/pod/show/elijahmurray RSS: https://anchor.fm/s/3e31c0c/podcast/rss