DoorDash’s AI Agent Pipeline, Git Worktrees & When Engineers Should Build Their Own Tools

This week on Software Sundays, KD breaks down the growing cybersecurity threats facing the internet and why artificial intelligence is changing the speed at which attackers can discover and exploit vulnerabilities.We start with a major PHP security vulnerability and its potential impact on websites, businesses, and the infrastructure that powers the internet. KD explains why vulnerabilities in widely used software can put sensitive data and entire systems at risk, how AI is lowering the barrier to entry for cyberattacks, and why businesses and engineers must be prepared to respond faster than ever before.Then we get into the challenges of maintaining legacy software, why upgrading dependencies can become increasingly difficult over time, and how neglected applications can create significant security risks when critical patches become necessary.In this week's Q&A, KD covers why reliable exception handling matters, what it really means to be a full stack engineer in 2026, and why today's developers need to understand more than frontend and backend development. We also discuss when unit testing becomes necessary, why 100% code coverage isn't always the goal, and how to decide whether a business process should be eliminated, delegated, or automated.We close with a mindset lesson on the relationship between passion, discipline, and value. KD shares his personal journey from struggling in his first computer science class to building a career in software engineering, and explains why developing valuable skills can sometimes lead you to discover a passion you didn't know you had.CHAPTER:00:34 Show introduction and the week’s PHP security news01:04 Why the PHP vulnerability put websites at risk03:37 AI lowers the barrier for vulnerability exploitation07:35 BLI University and the week’s Q&A08:25 Why neglected dependencies are harder to upgrade11:37 A Java 8-to-11 modernization in practice13:53 Handling exceptions without derailing the whole program16:56 What full-stack engineering includes today20:32 When unit tests help - and why 100% coverage isn’t essential24:06 Simplify and document before automating26:35 Monitor automation and keep appropriate human oversight28:01 Why career value can come before passion29:13 KD’s path from struggling in CS to finding a passion for tech32:53 Birthday and Veterans Day acknowledgmentsJoin BLI University: https://discord.gg/jpJHGq6kgSConnect with Build Learn Impact:- Instagram → https://www.instagram.com/build.learn.impact- Substack → https://buildlearnimpact.substack.comConnect with Kevin Dowdy:- Instagram → https://www.instagram.com/mrkevindowdy- LinkedIn → https://www.linkedin.com/in/kevinldowdy- Substack → https://substack.com/@kevinldowdy- GitHub → https://github.com/kevindowdyDISCLAIMER: This is not professional advice. The views are my own and those of the people quoted. Consult your own advisers for legal, business, or tax decisions based on information from this episode.Build Learn Impact is on a mission to help you create wealth and opportunity through technology.Subscribe if you're ready to build the future.#SoftwareSundays #CyberSecurity #AI #PHP #SoftwareEngineering #FullStackDevelopment #TechEducation #ArtificialIntelligence #LegacySoftware #UnitTesting #Automation #SoftwareSecurity #BuildLearnImpact #Programming #CareerGrowth

This week on Software Sundays, KD breaks down America's AI Action Plan, the growing debate over building versus buying software in an AI-first world, and the cybersecurity practices engineers need to deploy autonomous systems safely.We start with the progress of the US AI Action Plan, including the federal government's push to recruit technical talent, establish shared AI testing environments, and invest in the energy infrastructure needed to power the next generation of AI. KD also explores the challenges that remain, from outdated electrical grids and nuclear energy development to regulatory hurdles, funding constraints, and the shortage of specialized engineering talent.Then we get into the changing economics of software development. AI is making it easier and cheaper to build applications, but does that mean companies should stop buying software? KD breaks down the build vs. buy decision, why maintaining software still comes with significant costs, and how businesses should think about technical debt, third-party dependencies, and protecting their engineering resources.In this episode's Q&A, we cover three essential cybersecurity practices for autonomous AI systems, how Claude Code remote control sessions work, and why developers should carefully manage permissions and execution environments. We also explore what governance, risk, and compliance (GRC) analysts actually do, how automation can improve cybersecurity operations, and why securing Git repositories is critical to protecting intellectual property and software supply chains.We close with a reminder that nothing is guaranteed, even when you have a plan. Focus on what you can control, take action toward the outcomes you want, and don't waste energy worrying about everything else. With 60 days remaining in 2026, there's still time to execute, make progress, and finish the year strong.CHAPTERS:America's AI Action Plan and federal AI adoptionGovernment AI sandboxes, technical talent, and the Genesis MissionEnergy infrastructure, nuclear reactors, and AI data centersIdentity management, sandboxing, and monitoring autonomous AI agentsClaude Code remote control sessions and development environmentsBuild vs. buy decisions in an AI-first worldSoftware maintenance costs and third-party dependency risksThe role of governance, risk, and compliance (GRC) analystsGit repository security, signed commits, and access controlsStaying focused, managing uncertainty, and finishing 2026 strongJoin BLI University: https://discord.gg/jpJHGq6kgSConnect with Build Learn Impact:Instagram → https://www.instagram.com/build.learn.impactSubstack → https://buildlearnimpact.substack.comConnect with Kevin Dowdy:Instagram → https://www.instagram.com/mrkevindowdyLinkedIn → https://www.linkedin.com/in/kevinldowdySubstack → https://substack.com/@kevinldowdyGitHub → https://github.com/kevindowdyDISCLAIMER: This is not professional advice. The views are my own and those of the people quoted. Consult your own advisers for legal, business, or tax decisions based upon information from this episode.Build Learn Impact is on a mission to help you create wealth and opportunity through technology.Subscribe if you're ready to build the future.#SoftwareSundays #AI #SoftwareEngineering #Cybersecurity #ClaudeCode #AIAgents #BuildVsBuy #AIInfrastructure #GRC #GitHub #TechEducation #BuildLearnImpact #SaaS #AIActionPlan

This week on Software Sundays, KD breaks down the growing security risks surrounding artificial intelligence, the importance of protecting sensitive data, and the infrastructure powering the next generation of technology.We start with allegations that a former OpenAI employee secretly installed a recording device in a conference room used for sensitive discussions. KD explores what this situation reveals about insider threats, corporate espionage, intellectual property protection, and the growing competition between countries and companies to control AI technology.Then we get into cybersecurity and software engineering fundamentals. KD explains what it takes to work toward HIPAA compliance, why securing protected health information requires more than just technology, and how businesses can implement secure defaults, least-privilege access, logging, monitoring, and configuration standards to reduce their exposure to attacks.We also break down how engineers should decide where applications and workloads run, from virtual environments and containers to dedicated virtual machines. KD explores the three essential components of data center infrastructure — power, networking, and compute — and discusses the growing adoption of ARM processors, the role of GPUs, and the infrastructure investments shaping the future of AI.In our final technical Q&A, we explore the differences between SHA hashing algorithms and AES encryption, along with why cryptography matters for securing modern systems.We close with a reminder that you don't have to face every challenge alone. Seek support, listen to feedback, and surround yourself with people who genuinely want to see you succeed.**Timestamps:**00:14 - Welcome to Software Sundays 00:30 - Former OpenAI employee accused of installing a recording device 02:24 - Insider threats, corporate espionage, and AI competition 04:42 - Why AI intellectual property and national infrastructure matter 06:29 - Software engineering and cybersecurity Q&A 06:51 - What does it take to meet HIPAA compliance requirements? 09:18 - Encryption, least privilege, logging, and protecting health data 11:27 - Securing public-facing applications and cloud storage 14:21 - Three secure defaults every application should have 15:32 - Monitoring, observability, and secure configuration standards 19:21 - How to choose where applications and workloads should run 21:57 - Virtual environments, containers, VMs, and workload isolation 24:05 - Three essential components of every data center 26:31 - Networking infrastructure, wireless systems, and compute 28:44 - GPUs, high-performance computing, and ARM processors 31:13 - SHA vs. AES: Understanding hashing and encryption 35:28 - Mindset: Seek support and learn to accept help 37:27 - Birthday shoutout and outro **Join BLI University:** https://discord.gg/jpJHGq6kgS**Connect with Build Learn Impact:**Instagram → https://www.instagram.com/build.learn.impactSubstack → https://buildlearnimpact.substack.com**Connect with Kevin Dowdy:**Instagram → https://www.instagram.com/mrkevindowdyLinkedIn → https://www.linkedin.com/in/kevinldowdySubstack → https://substack.com/@kevinldowdyGitHub → https://github.com/kevindowdy**DISCLAIMER:** This is not professional advice. The views are my own and those of the people quoted. Consult your own advisers for legal, business, or tax decisions based upon information from this episode.Build Learn Impact is on a mission to help you create wealth and opportunity through technology.Subscribe if you're ready to build the future.#SoftwareSundays #OpenAI #CyberSecurity #ArtificialIntelligence #HIPAA #SoftwareEngineering #DataCenters #CloudSecurity #InsiderThreats #AIInfrastructure #ARM #Encryption #TechEducation #BuildLearnImpact #InformationSecurity

This week on Software Sundays, KD breaks down one of the biggest challenges facing businesses adopting artificial intelligence: the hidden cost of validating AI-generated work.We start with a study discussed by the Federal Reserve Bank of Atlanta examining how AI productivity gains can be reduced by the "validation tax" — the additional time and effort humans spend reviewing, verifying, and correcting AI outputs. KD explores why faster automation doesn't always translate into greater overall productivity, how AI creates new bottlenecks in engineering workflows, and why human expertise remains essential for maintaining reliable systems.Using vulnerability management as a real-world example, we discuss how automated security scanners and AI-powered tools can identify more vulnerabilities than ever before, but finding problems is only part of the job. Engineers still need to assess risk, test solutions, validate changes, and ensure fixes don't break other systems.In this episode's Q&A, we cover how to choose the right shell for cross-platform scripting, why standardizing environments can be more effective than building scripts for every operating system, and how teams can distribute responsibilities through better documentation and communication.KD also explains why privileged accounts like root and admin users introduce significant security risks, how technical experts can collaborate with non-technical business partners, and practical strategies for adapting to constantly changing priorities at work.We close with a mindset reminder about the relationship between vision and reality, the importance of developing your own ideas, and why builders must be intentional about the future they want to create.Chapters:00:00 - Welcome to Software Sundays00:31 - The AI validation tax and hidden productivity costs09:31 - Choosing the right shell for cross-platform scripting13:30 - Distributing team responsibilities and improving documentation18:29 - Why privileged accounts and root access create security risks26:32 - How technical and non-technical experts can collaborate29:48 - Adapting to shifting priorities in engineering teams36:59 - Mindset: Reality starts with your vision—Join BLI University: https://discord.gg/PFH8Qszk2A Connect with Build Learn Impact: Instagram →  https://www.instagram.com/build.learn.impactSubstack → https://buildlearnimpact.substack.com Connect with Kevin Dowdy: Instagram → https://www.instagram.com/mrkevindowdyLinkedIn →  https://www.linkedin.com/in/kevinldowdySubstack → https://substack.com/@kevinldowdyGitHub → https://github.com/kevindowdy DISCLAIMER: This is not professional advice. The views are my own and the people quoted. Consult your own legal, business or tax advisors before making decisions based upon information found in this episode.Build Learn Impact is on a mission to help our community create wealth and opportunity through technology. Subscribe if you’re ready to build the future. 

This week on Software Sundays, KD breaks down the next shift in computing as Qualcomm expands Linux support for its Snapdragon chips, ARM-based processors gain ground, and developers get more options for how they build and run software.We start with Qualcomm's push to bring better Linux compatibility to Snapdragon-powered devices and why this matters for developers, hardware manufacturers, and the future of computing. KD also explores Qualcomm's opportunities beyond smartphones, including laptops, connected devices, robotics, and the automotive industry.Then we get into the growing competition between ARM and x86 processors, why power efficiency matters, and how these competing architectures are changing the technology industry.In this episode's Q&A, we cover when to use virtual machines, how operating systems interact with computer hardware, what to consider when building a home lab, and why understanding the infrastructure behind your applications can make you a stronger engineer.KD also explores decentralization beyond cryptocurrency, including the risks of depending on a handful of companies for critical technologies like processors, operating systems, and computing infrastructure. We discuss what technology independence means for developers, businesses, and communities looking to build greater ownership.We close with a reminder that respect is the foundation of strong relationships, healthy communities, and meaningful collaboration.Timestamps:00:00 Introduction to Software Sundays Builders00:32 Qualcomm's Snapdragon X2 Series and Linux Support03:01 Transitioning from Windows to Linux in CPU Design04:29 Introduction to Software Sundays Builders05:05 Qualcomm's Snapdragon Chips and Linux Support11:33 Understanding Virtual Machines16:50 How Operating Systems Function22:54 Building a Home Lab27:46 Differences Between x86 and ARM Architectures32:33 Decentralization in Technology39:37 Mindset Tip: The Importance of RespectJoin BLI University: https://discord.gg/jpJHGq6kgSConnect with Build Learn Impact:Instagram → https://www.instagram.com/build.learn.impactSubstack → https://buildlearnimpact.substack.comConnect with Kevin Dowdy:Instagram → https://www.instagram.com/mrkevindowdyLinkedIn → https://www.linkedin.com/in/kevinldowdySubstack → https://substack.com/@kevinldowdyGitHub → https://github.com/kevindowdy**DISCLAIMER:** This is not professional advice. The views are my own and those of the people quoted. Consult your own advisers for legal, business, or tax decisions based upon information from this episode.Build Learn Impact is on a mission to help you create wealth and opportunity through technology.Subscribe if you're ready to build the future.#SoftwareSundays #Qualcomm #Linux #Snapdragon #ARM #x86 #SoftwareEngineering #TechEducation #HomeLab #VirtualMachines #OperatingSystems #Decentralization #CyberSecurity #BuildLearnImpact

This week on Software Sundays, KD breaks down why Apple is tightening access to user data as AI agents become more powerful — and why the battle over who controls your data is only getting started.We start with Apple’s move to put stronger controls around full disk access and what it means for developers building AI agents. As these tools gain the ability to read files, operate applications, browse the web, and take actions on our behalf, traditional security principles like least privilege become even more important. But there’s another side to the conversation: are Apple’s restrictions purely about protecting users, or do they also make its already-sticky ecosystem even harder to leave?KD also explores why AI adoption is happening dramatically faster than the original adoption of the internet. The infrastructure, devices, cloud platforms, digital payments, and user behaviors AI needs already exist. Instead of asking people to adopt an entirely new technological ecosystem, AI is being layered directly onto one they already use every day.In this episode’s Q&A, we cover why engineers need to understand the limitations of their favorite technology stacks, the difference between volumes and partitions, how storage architecture affects availability and scale, and the CIA triad of confidentiality, integrity, and availability.We also get practical about protecting your digital identity — including strong passwords, password managers, multi-factor authentication, and separating email identities based on how sensitive the accounts connected to them are.We close with a reminder that real growth happens in more than one direction. Becoming a stronger engineer or entrepreneur also means investing in your health, relationships, discipline, perspective, and life outside of technology.Chapters:00:00 Introduction to the episode and main themes00:29 Apple's new data control policies and privacy focus06:42 What is the engineering tip of the week?11:24 Differences between volumes and partitions in data storage17:06 Why AI adoption is happening so rapidly24:29 The CIA triad and its importance in cybersecurity28:47 Strategies for maintaining data privacy and security33:59 The importance of holistic growth and continuous learning36:10 Upcoming tech events and community engagementJoin BLI University: https://discord.gg/jpJHGq6kgSConnect with Build Learn Impact:Instagram → https://www.instagram.com/build.learn.impactSubstack → https://buildlearnimpact.substack.comConnect with Kevin Dowdy:Instagram → https://www.instagram.com/mrkevindowdyLinkedIn → https://www.linkedin.com/in/kevinldowdySubstack → https://substack.com/@kevinldowdyGitHub → https://github.com/kevindowdyDISCLAIMER: This is not professional advice. The views are my own and the people quoted. Consult your own advisers for legal, business or tax decisions based upon information from this episode.Build Learn Impact is on a mission to help you create wealth and opportunity through technology.Subscribe if you’re ready to build the future.#SoftwareSundays #AIAgents #Apple #AI #DataPrivacy #CyberSecurity #SoftwareEngineering #TechEducation #LeastPrivilege #CIAtriad #DataSecurity #Engineering #ArtificialIntelligence #BuildLearnImpact

This week on Software Sundays, KD breaks down the growing fear around artificial intelligence and why engineers and builders need to think beyond the headlines.We start with warnings from AI researchers about the potential risks of increasingly capable models, recent incidents involving frontier AI systems, and the lack of transparency surrounding how these models are developed. But instead of focusing only on worst-case scenarios, KD looks at the bigger question: who is building, deploying, and ultimately responsible for these systems?AI development isn’t stopping. Billions are being invested into the models, infrastructure, and data centers powering the next generation of AI. The opportunity for builders is learning how to understand these systems, deploy them responsibly, and determine where AI should operate autonomously versus where human judgment still matters.Then we get into this week’s engineering Q&A. KD breaks down what great performance actually looks like as a software engineer, why helping your team improve can be more valuable than individual output, and whether AI will eventually replace your job.We also cover where someone should start if they want to become a software engineer today, from choosing a programming language to moving beyond tutorials and building real projects. KD explains what accountability means when you own a project and shares a practical framework for prioritizing planned work, urgent requests, and long-term improvements.We close with a reminder that discipline matters, but your life shouldn’t become so structured that you stop experiencing anything new. Sometimes stepping outside the routine gives you the energy you need to keep going.Timestamps:00:00 - Welcome to Software Sundays00:30 - AI researchers are warning about catastrophic risk09:44 - What does great software engineering performance look like?14:20 - Will AI replace your job?19:21 - How to become a software engineer today24:08 - What does project accountability really mean?28:26 - How engineers should prioritize their work36:08 - Why disciplined people still need spontaneity39:14 - OutroJoin BLI University: https://discord.gg/jpJHGq6kgSConnect with Build Learn Impact:Instagram → https://www.instagram.com/build.learn.impactSubstack → https://buildlearnimpact.substack.comConnect with Kevin Dowdy:Instagram → https://www.instagram.com/mrkevindowdyLinkedIn → https://www.linkedin.com/in/kevinldowdySubstack → https://substack.com/@kevinldowdyGitHub → https://github.com/kevindowdyDISCLAIMER: This is not professional advice. The views are my own and the people quoted. Consult your own advisers for legal, business or tax decisions based upon information from this episode.Build Learn Impact is on a mission to help you create wealth and opportunity through technology.Subscribe if you’re ready to build the future.#SoftwareSundays #AI #ArtificialIntelligence #SoftwareEngineering #TechCareers #AIJobs #Engineering #Programming #CareerDevelopment #TechEducation #Leadership #SoftwareDeveloper #BuildLearnImpact

This week on Software Sundays, KD breaks down how DoorDash is using a multi-agent LLM pipeline to clean up more than 60,000 stale feature flags across hundreds of repositories — and why AI agents may become increasingly valuable for the engineering work teams know needs to get done but rarely have enough time to prioritize.Then we get into how engineering teams can actually burn down large backlogs faster than new work is created. KD covers reducing false positives, improving triage, prioritizing high-impact fixes, increasing development capacity, and why separate development environments and faster QA processes are critical for moving quickly without creating unnecessary risk.In this episode’s Q&A, KD explains why Git worktrees have become especially useful in the age of AI coding agents, how they allow multiple developers or agents to work in parallel without stepping on each other’s changes, and how they can fit into an existing branch and pull request workflow.We also break down what Datadog is used for, how logs and metrics support observability, how Datadog agents collect telemetry, and how teams can build dashboards and alerts around the systems they operate.KD also covers how to manage feature flags correctly — including choosing safe defaults, connecting flags to external systems like LaunchDarkly, monitoring rollouts, establishing rollback criteria, and making sure observability is in place before experimenting with production behavior.For this week’s engineering tip, KD challenges the idea that engineers should never reinvent the wheel. After needing better visibility into automated data pipelines, he built a custom log forwarder for Datadog rather than going through the process of deploying third-party software in a restricted environment. The lesson: build vs. buy decisions should depend on your constraints, the value of the solution, and what you learn from building it yourself.We close with a reminder that growth often requires putting yourself in rooms with people who are better than you. Whether you're developing as an engineer, architect, security professional, entrepreneur, or leader, your environment can either challenge you to improve or keep you comfortable at your current level.Chapters:00:00 DoorDash's Multi-Agent Feature Flag Cleanup LLM01:37 Using AI to Manage Stale Feature Flags05:06 Handling Backlogs and Accelerating Development07:26 Strategies for Reducing False Positives in Backlog Management12:15 Introduction to Git Work Trees for Parallel Development17:37 Monitoring with Datadog: Logs, Metrics, and Alerts21:44 Best Practices for Feature Flag Management25:15 Using Monitoring to Decide When to Roll Back Features26:52 Engineering Tips: Building vs Buying Solutions27:10 Engineering tip of the week33:09 Don't be the smartest in the room-------------------------Join BLI University: https://discord.gg/PFH8Qszk2A Connect with Build Learn Impact: Instagram →  https://www.instagram.com/build.learn.impactSubstack → https://buildlearnimpact.substack.com Connect with Kevin Dowdy: Instagram → https://www.instagram.com/mrkevindowdyLinkedIn →  https://www.linkedin.com/in/kevinldowdySubstack → https://substack.com/@kevinldowdyGitHub → https://github.com/kevindowdy DISCLAIMER: This is not professional advice. The views are my own and the people quoted. Consult your own legal, business or tax advisors before making decisions based upon information found in this episode.Build Learn Impact is on a mission to help our community create wealth and opportunity through technology. Subscribe if you’re ready to build the future.

This week on Software Sundays, KD breaks down a cybersecurity experiment that shows just how unpredictable AI agents can become when they are given a goal and enough room to operate.We start with an OpenAI cybersecurity evaluation where a sandboxed AI agent found a path outside of its restricted environment, chained together vulnerabilities across multiple systems, discovered zero-days, and even found ways to collaborate with other agents. KD unpacks what happened, why traditional sandboxing was not enough, and what this could mean as AI agents become more capable.From there, we get into how sandbox environments should actually be configured, including production isolation, network segmentation, infrastructure as code, monitoring, cost controls, and treating experimental environments as disposable infrastructure.In this episode’s Q&A, KD explains what a zero-day vulnerability is, why defense in depth matters, what cybersecurity engineers actually do, and the difference between red teams and blue teams.We also get into the growing distinction between vibe coding and agentic engineering. AI can write code quickly, but engineering still requires architecture, guardrails, design decisions, monitoring, and someone capable of recognizing when the system is going in the wrong direction.As AI-powered attacks begin operating at machine speed, defenders will increasingly need automation that can detect, isolate, respond to, and recover from threats just as quickly.We close with a reminder to seek quiet moments in an increasingly loud world, make space for your own voice, and be intentional about which voices you allow to influence your direction.Chapters:00:00 Introduction to the episode and main themes00:27 Recent AI cybersecurity incident between OpenAI and Hugging Face10:17 Configuring secure sandbox environments for AI development18:11 Understanding zero-day vulnerabilities and their risks24:07 Role of cybersecurity engineers and their responsibilities28:12 Vibe coding versus agentic engineering in AI development32:30 Red team and blue team roles in cybersecurity defense38:46 The importance of internal voice and mindfulness in a noisy worldJoin BLI University: https://discord.gg/PFH8Qszk2A Connect with Build Learn Impact: Instagram → https://www.instagram.com/build.learn.impactSubstack → https://buildlearnimpact.substack.com Connect with Kevin Dowdy: Instagram → https://www.instagram.com/mrkevindowdyLinkedIn → https://www.linkedin.com/in/kevinldowdySubstack → https://substack.com/@kevinldowdyGitHub → https://github.com/kevindowdy DISCLAIMER: This is not professional advice. The views are my own and the people quoted. Consult your own advisers for legal, business or tax decisions based upon information from this episode.Build Learn Impact is on a mission to help our community create wealth and opportunity through technology. Subscribe if you’re ready to build the future. 

This week on Software Sundays, KD breaks down how stablecoins are becoming part of the financial infrastructure businesses and financial institutions rely on — and why that shift is creating major opportunities for software engineers and builders.We get into what it actually takes to connect stablecoin products with existing financial rails, including APIs, authentication, treasury infrastructure, cybersecurity, compliance, fraud detection, and the engineering required to make faster and more global payments reliable.KD also explains why the next generation of financial technology will still need to integrate with legacy systems, and why understanding both software architecture and the regulated environments these systems operate in can make engineers more valuable as finance continues to evolve.In this episode’s Q&A, we cover how to manage a release cycle for a production application, why changes should be classified by risk, how canary deployments and rollback strategies reduce production failures, and why mission-critical systems require careful release planning.We also break down how to enable payments inside an application without rebuilding financial infrastructure from scratch, why services like Stripe can reduce complexity and compliance risk, which careers benefit from a software engineering background, and what a single point of failure means when designing reliable systems.We close with a reminder about the value of direct communication: sometimes the shortest path to solving a problem is simply saying clearly what needs to be said.Chapters:00:28 STABLECOIINS ARE BECOMING PART OF THE FINANCIAL INFRASTRUCTURE08:08 MANAGING RELEASE CYCLES FOR ENTERPRISE APPLICATIONS14:58 ENABLING PAYMENTS WITHIN YOUR APPLICATION USING THIRD-PARTY SERVICES17:41 THE VALUE OF A SOFTWARE ENGINEERING BACKGROUND IN FINANCE AND OTHER INDUSTRIES23:06 UNDERSTANDING AND MITIGATING SINGLE POINTS OF FAILURE IN SYSTEMS25:46 EFFECTIVE COMMUNICATION AND DIRECTNESS IN TEAM MANAGEMENTJoin BLI University: https://discord.gg/wvsWhZ3A Connect with Build Learn Impact: Instagram →  https://www.instagram.com/build.learn.impactSubstack → https://buildlearnimpact.substack.comConnect with Kevin Dowdy: Instagram → https://www.instagram.com/mrkevindowdyLinkedIn →  https://www.linkedin.com/in/kevinldowdySubstack → https://substack.com/@kevinldowdyGitHub → https://github.com/kevindowdy DISCLAIMER: This is not professional advice. The views are my own and the people quoted. Consult your own advisers for legal, business or tax decisions based upon information from this episode.Build Learn Impact is on a mission to help our community create wealth and opportunity through technology. Subscribe if you’re ready to build the future.