• 37 minutes 22 seconds
    The excitement and value of quality

    Share Episode         
             
    Sauce Labs CTO Anoop Tripathi addresses the root causes of broken test suites and why teams frequently become numb to intermittent test failures. Anoop shares concrete lessons from his career, detailing how bad practices like embedding fixed sleep routines instead of signal-based waiting ruin test reliability. We discuss the necessity of designing products for testability from day one—such as using pair programming where one developer writes the implementation while the other writes the test suite, or building dedicated test interfaces directly into the application architecture. We also analyze the hidden business costs of poor quality, where engineering debt forces sales teams to spend their time managing upset clients instead of acquiring new revenue.

             

    We explore organizational anti-patterns—such as teams claiming to be 'Agile' with one-year sprint cycles, or shipping debug builds to production because release builds continuously crash, highlighting a pair-programming model where one developer writes the code while another writes the corresponding tests

             

    Finally, we tackle the dangers of chasing vanity metrics, from engineers writing automated assert pass statements to claim fake coverage, to organizations bragging about more code. Anoop distinguishes between output gain and outcome gain, warning that LLMs are creating a massive testing and review crisis by generating 20-page documentation files for minor features.

             
    💡 Notable Links:         
    🎯 Picks:         
    11 September 2026, 12:00 am
  • 1 hour 2 minutes
    How to land a software job in the age of LLMs

    Share Episode         
             
    In this episode, we sit down with Nikhil Mungel, Head of AI R&D at Cribl, to discuss how LLMs have dramatically transformed the tech hiring landscape. The conversation opens with an honest look at the flood of AI-generated, low-quality resumes and remote interview cheating tactics, which have pushed many organizations toward in-person whiteboard interviews or closed-network referrals.

             

    We explore how software development has evolved from character-by-character coding into "judgment work," where an engineer's value relies on holistic decision-making, taste, and business alignment rather than raw syntax memorization. Nikhil emphasizes the importance of an "ownership mindset," urging developers to move beyond acting as mere specification-translators and instead evaluate technical trade-offs through a business-focused lens. We also pull back the curtain on modern technical interviews, highlighting why expressing strong convictions, asking intentional career questions, and proving human reasoning without LLM assistance remain essential for standing out.

             
    💡 Notable Links:         
    🎯 Picks:         
    28 August 2026, 12:00 am
  • 42 minutes 25 seconds
    Why does anyone use Crossplane?

    Share Episode         
             
    Pushkar Gopalakrishna, Senior Staff Software Engineer at Snap, previously Cruise and AWS, joins to explore why engineering organizations pivot away from Terraform and HCL toward Kubernetes-native tools even when they might not be better. We unpack how developer friction, copy-pasted control structures, and misaligned organizational incentives create massive tech debt—often forcing SREs to manually update infrastructure repositories for compliance, resulting in broken pipelines and severe operational friction.

             

    We debate over the mechanics of Crossplane, detailing how its continuous reconciliation loop and Custom Resource Definitions (CRDs) allow teams to express cloud infrastructure as YAML alongside their application manifests at potentially the cost of async validation. Pushkar pulls back the curtain on how Cruise managed infrastructure at scale using a custom internal platform called 'Juno' to bootstrap GCP projects, repositories, and permissions, while leveraging Crossplane for application-level resources. We also dive into the dangers of using CI tools for continuous deployment, detailing a terrifying incident where a pipeline bug accidentally marked three production Kubernetes namespaces for deletion, and how moving to ArgoCD and Argo Rollouts helped prevent future outages for autonomous vehicles.

             

    Finally, we touch on the realities of non-production environment isolation, testing against live APIs, and why platform teams must balance providing a seamless developer experience without stripping away developer accountability.

             
    💡 Notable Links:         
    🎯 Picks:         
    7 August 2026, 12:00 am
  • 41 minutes 58 seconds
    Building Observability for the Innovators

    Share Episode         
             
    Co-Founder of Grafana Labs, Anthony Woods, joins to share his perspective on how open source solutions are thriving despite the deluge of pull requests being thrown at them through their open source repositories.

             

    Most importantly, he outlines how observability is no longer being done by users looking directly at dashboards. The data rarely makes to LLMs or automation, it rarely makes sense even to humans looking at them, without the context. The context is critical component, and having a model that was built on the semantic concepts relevant to your use cases.

             

    And of course we can't stay away from asking on the record the current state of security of open source repositories from a vendor side. Given how their was an inevitable incident with some of the Grafana open source repos, we dig in to figure out how they are dealing with the real world impacts of malware being spread throughout the ecosystem.

             
    💡 Notable Links:         
    🎯 Picks:         
    31 July 2026, 12:00 am
  • 1 hour 9 minutes
    When knowledge is free but the infrastructure isn't

    Share Episode         
             
    As it turns out, the entire artificial intelligence boom is essentially running on Wikipedia's free labor, but while knowledge is free, physical server infrastructure definitely is not. We sit down with Moriel Schottlender, Principal Systems Software Engineer at the Wikimedia Foundation, to dissect how public systems survive an endless onslaught of high-volume AI scrapers and aggressive crawlers. Because 65% of the resource-heavy requests originate from automated bots, we explore how Wikimedia navigates this traffic without blocking legitimate users. We skip the approaches of IP-banning which doesn't work in practice and discuss actual mature architectural strategies, by focusing on the users' needs. From structured database dumps and high-volume enterprise APIs to rate-limiting and CDN caching trade-offs.

             

    It's a mind-bogglingly complex ecosystem ­of open-source, a 25-year-old PHP monolith supporting over 900 distinct site instances across 300 languages and 11 unique projects. It's an immense engineering challenge to modernize infrastructure while serving 250,000 active volunteer editors who build custom workflows via Toolforge—Wikimedia's internal, open-source mini-AWS.

             

    Finally, we have to tackle the philosophical divide between artificial statistical models and human creativity. Because LLMs are trained to predict the statistical mean, they inherently miss the edge cases where real human value, internationalization, and accessibility actually reside. And even if they did, we managed to squeeze out every last bit of AI creativity that early models had until what we are actually left with is the most boring result. We also commiserate over the gratuitous low-quality AI pull requests flooding open-source repositories, drawing parallels to the chaotic Hacktoberfest spam of years past.

             
    💡 Notable Links:         
    🎯 Picks:         
    24 July 2026, 12:00 am
  • 1 hour 28 seconds
    Technically We Have Code Reviews and the LLM Semantic Layer

    Share Episode         
             
    We are joined this week by Mark Hay, CTO and co-founder of TextQL and former lead of Text Classification Infrastructure at Meta, to uncover the hidden complexities behind massive-scale machine learning. Mark explains why the most crucial features for identifying abusive behavior, like drug dealers or scammers on Facebook and Instagram, rarely rely on the content itself but instead analyze the underlying behavioral graphs, such as abnormal friend requests or messaging patterns.

             

    Of course we review the adversarial nature of spam detection, where bad actors constantly evolve from simple regex evasion to embedding messages inside images or even utilizing pure symbolic communication, like comparing different sized cucumber emojis to evade text filters. That requires diving into the evolution of database querying and the rise of the semantic layer. Mark unpacks why relying on raw LLMs to write complex SQL is a recipe for hallucinations, and how implementing a "correct by construction" semantic layer guarantees structurally sound queries by restricting outputs to a strictly defined configuration. However, this rigid structure fundamentally stifles the creative flexibility of LLMs.

             

    Lastly, we can't avoid exploring the tension between these approaches and how new tools aim to bridge the gap by dynamically balancing raw SQL generation with structured ontological constraints, providing rapid time-to-value for analytical workflows. Finally, we discuss the controversial philosophical shift occurring within software engineering, particularly the tension between the "Don't Repeat Yourself" principle and "Locality of Behavior".

             
    💡 Notable Links:         
    🎯 Picks:         
    10 July 2026, 12:00 am
  • 54 minutes 36 seconds
    Who Needs Testers Anyway?

    Share Episode         
             

    26 June 2026, 12:00 am
  • 52 minutes 52 seconds
    You Wouldn't Implement A Database

    Share Episode         
             
    We talk with Ragic CEO Jeff Kuo about Semantic Web origins, dodging DDoS attacks, and the absolute horror of a database that randomly deletes its own files. He revisits how a 25-year-old master's thesis on the Semantic Web evolved into a massive spreadsheet-driven database builder. It's the one better Airtable alternative.

             

    Rather than forcing non-technical users into complex two-layer SQL architectures, Ragic utilizes a highly flexible, graph-based data model. Achieving this performance meant abandoning traditional ORMs to build a custom graph indexing engine on top of Berkeley DB, a key-value store. This custom implementation came with brutal growing pains, including a terrifying bug that would randomly delete the wrong data files. To survive, Ragic's team shares with us just exactly how they had to hijack the internal implementation to avoid these sorts of problems.

             

    When we get down to it, we review how they dealt with critical DDoS against their cloud providers, how they performed a cloud migration in just one weekend, and how they manage thousands of tenants on shared infrastructure.

             
    💡 Notable Links:         
    🎯 Picks:         
    19 June 2026, 12:00 am
  • 49 minutes 55 seconds
    What If Tools Are Not Expensive To Build

    Share Episode         
             
    Developers spend more than 50% of their time reading code, making it the single largest expense in software engineering. Despite this massive cost, the industry rarely discusses or optimizes how we read code. So we've brought in Tudor Girba, CEO at Feenk to help us rethink, just how software engineering should be done. Instead of relying on manual reading and generic text editors, teams must shift toward building deterministic, contextual tools to directly extract information and answer questions about their systems.

             

    The suggested solution? Contextual and composable micro-tools writen by everyone focused on exposing just the right information at the right time. This creates the opportunity for structural interrogation of your solution.

             

    And how many tools should we? We'll if one example of tool is testing, and 50% or more of your code can be tests, imagine what percentage of your software should be actually production related!

             

    Most importantly, generic tools fall short, but where can we find how to build the right tools, listen in to find out....

             
    💡 Notable Links:         
    🎯 Picks:         
    12 June 2026, 12:00 am
  • 1 hour 5 minutes
    DR: Staying resilient in the cloud

    Share Episode         
             
    Welcome back to another hopefully, relief from architectural existential dread. This week, we've pulled in Seth Eliot from Arpio, (Ar-Pi-O, RPO, get it?), to dive headfirst into the beautiful, deeply expensive illusion that migrating your legacy infrastructure to a major hyperscaler magically grants it instant immortality. It doesn't. We break down the shared responsibility model for resilience, which was conveniently cribbed straight from the security model, and analyze how the foundational promise of automated fault isolation boundaries routinely crumbles.

             

    From cloud providers sticking multiple "independent" availability zones inside the exact same physical building, to multi-AZ cascading anomalies, to regional power grid failures, it's clear your provider's abstractions aren't nearly as resilient as their marketing slides suggest.

             

    Discussed within is the "Thundering Herd" phenomenon, that can't be ignored even when the failover clusters are designed correctly. From cross-organization KMS re-encryption loops to the horror of fragmented application logs across CloudFront edge regions, at the end of the day, true resilience isn't achieved by forcing your engineering team to implement features, it's about architecting your baseline, confidentiality for the inevitability of production burning to the ground.

             
    💡 Notable Links:         
    🎯 Picks:         
    5 June 2026, 12:00 am
  • 59 minutes 17 seconds
    Eat your security vegetables

    Share Episode         
             
    This week's adventure tackles the absolute absurdity of modern enterprise infrastructure, where a single company can easily find itself running multiple different CI/CD platforms due to unchecked mergers and acquisitions. We've brought in Chris Farris, AWS Security Hero and consults with companies via Securosis. And dig deep to find the security cracks and philosophize about the real world impacts of tech debt in the AI age.

             

    Management rarely prioritizes standardization, leaving security teams to defend a chaotic swamp of mixed cloud providers, GitHub repositories, and nostalgic on-prem Bitbucket instances. We define this accumulated technical debt not as some abstract concept, but as literal potholes on the infrastructure Autobahn—annoying speed bumps that permanently damage velocity and set organizations up for an inevitable disaster. We contrast this with the evolution from old-school sysadmins cutting their fingers on rack screws to modern engineers spinning up entire architectures with a few lines of code, noting that the ease of deployment has far outpaced our willingness to clean up our own mess.

             

    The crisis is only accelerating now that the cost of writing code (but not having to maintain it) is rapidly approaching zero. While letting an AI agent autonomously build a website or manipulate an AWS sandbox over a single Saturday afternoon sounds magical, it creates a terrifying volume of unreviewed, context-devoid software. Compounding this systemic frailty, massive cloud provider layoffs mean the crucial institutional memory and human operational experience required to survive are walking right out the door. We expose the fundamental flaw of modern agentic tooling: they completely lack fine-grained access control, operating on a dangerous all-or-nothing identity model. Until autonomous agents are engineered with actual conscience, consequence, and common sense, security teams will continue fighting a losing battle against a digital supply chain.

             
    💡 Notable Links:         
    🎯 Picks:         
    29 May 2026, 12:00 am
  • More Episodes? Get the App