Beyond Coding

Patrick Akil

For software engineers ready to level up. Learn from CTOs, principal engineers, and tech leaders about the skills beyond coding: from technical mastery to product thinking and career growth. Created by Patrick Akil

  1. How Top Engineers Are Solving the Code Review Bottleneck

    2日前

    How Top Engineers Are Solving the Code Review Bottleneck

    AI generates 10x more code, but your senior engineers still review it by hand and it's burning them out. Even Google admits code review is now the bottleneck nobody knows how to solve. Florian Buetow, AI engineer at Xebia, has been running experiments to eliminate the human from the review loop entirely, and what he found changes where engineers should focus their effort. In this episode, we cover: Why "stop doing code reviews" is a serious answer (and what replaces them)The guardrails that gave the most value: Semgrep rules, architectural unit tests, and stop hooksWhy your harness matters more than the modelHow Amazon and Google police AI-generated code with policiesAI burnout, cognitive debt, and "cognitive surrender": what stays your responsibilityStep one for adopting agentic software engineering in your team this weekWhether you're an individual developer drowning in AI-generated PRs or driving AI adoption across a large engineering org, you'll leave with concrete experiments to run. More from Florian:https://cracking-ai-engineering.com Timestamps:00:00:00 - Intro00:00:40 - Code Review Is Software Engineering's Biggest Bottleneck00:01:57 - How Amazon and Big Tech Police AI-Generated Code00:02:55 - Horizontal vs Vertical Scaling of AI Engineering00:04:37 - Why "No Code Reviews" Might Be the Answer00:05:22 - Engineering Environments That Give Agents Feedback00:06:46 - Why the Harness Matters More Than the Model00:07:21 - When Spec-Driven Development Failed and TDD Worked00:10:06 - Stop Hooks, Ralph Loops, and Automated Feedback00:11:30 - The Guardrails That Gave the Most Value00:14:00 - Architectural Constraints That Keep AI Code Sane00:15:07 - What Remains a Human Responsibility00:17:33 - Why All the Hard Work Moves Upfront Now00:18:47 - The Incredible Skill Junior Engineers Should Learn00:20:26 - AI Burnout: Why Engineers Are Exhausted00:22:42 - Cognitive Surrender: Letting the Agent Take Over00:23:25 - The Hand Grenade Problem with AI at Work00:24:08 - Outsourcing Code Review to AI Itself00:26:39 - Teams That Fully Adopted Spec-Driven Development00:29:01 - Can You Rebuild Software From Tests Alone?00:30:27 - How to Experiment and Stay Ahead00:33:15 - Spying on What Subagents Tell Each Other00:33:59 - Step One: How to Start with Guardrails00:36:08 - Data Mining Your Session Logs for Patterns00:37:00 - Stuck With One Harness? Here's What to Do00:38:28 - The One Experiment to Run This Week #softwareengineering #aicoding #codereview

    40分
  2. Google DeepMind Lead: The New Rules of Software Engineering

    6月3日

    Google DeepMind Lead: The New Rules of Software Engineering

    Are you ready to adapt to the rapidly evolving rules of software development? In this deep dive, Logan Kilpatrick, Director and Engineer at Google DeepMind, breaks down how AI agents, advanced model-product symbiosis, and tools like Gemini 3.5 Flash are fundamentally shifting the engineering bottleneck. Learn how to maintain your competitive advantage by moving beyond the keyboard to focus on problem-solving, architectural taste, and system understanding. In this video, we cover: The changing role of the IDE and the rise of agent managers in code generation.Overcoming team bottlenecks in code review and CI/CD test execution execution loops.Why "agent coverage" and context integration are the next big tech stack metrics.Building a bulletproof software portfolio through permissionless open-source contributions.The critical difference between outsourcing intelligence versus outsourcing understanding.This episode is for software engineers, tech leads, and computer science students looking to future-proof their careers and reset their ambitions in the era of autonomous engineering agents. Timestamps: #SoftwareEngineering #AIAgents #GoogleDeepMind

    24分
  3. Addy Osmani: Top Tier Software Engineers vs. AI Agents. The Mindset You Need

    5月28日

    Addy Osmani: Top Tier Software Engineers vs. AI Agents. The Mindset You Need

    As AI agents transform software engineering, how do you leverage them without losing your coding skills or risking production disasters? In this episode, Google Cloud AI Director Addy Osmani breaks down the shift from babysitting basic models to mastering advanced agent harnesses. Discover how to safely delegate complex technical tasks while maintaining your human engineering identity and setting up secure boundaries for your AI. In this episode, we cover: Human Identity vs. Machine Identity: How to avoid the trap of "cognitive surrender" and keep your critical thinking sharp.Stopping the AI "Babysitting" Cycle: How to transition from constant manual oversight to secure agent governance.Rising Abstractions: Why agent harnesses (like Claude Code and Antigravity) are changing how software is built.The Verification Bottleneck: Why coding is easy, but verifying that your agent didn't ruin production is the real challenge.This episode is a must-watch for software engineers and tech leaders looking to integrate AI agents into their workflows safely and effectively. You’ll walk away with actionable frameworks to boost your development velocity without letting your own technical edge rot. Guest:Addy Osmani is a Director at Google Cloud AI, famous for his work on Google Chrome and focused on AI agents in software engineering. Timestamps:00:00:00 - Intro 00:00:45 - The Reality of "Babysitting" Your AI Agent Setup 00:01:16 - How to Stop Babysitting and Build Secure AI Agents 00:02:36 - The Dangerous Mistakes of Uncontrolled AI Experiments 00:03:39 - Rising Abstractions: From Code to Agent Harnesses 00:05:18 - Why You Should Delegate Technical Tasks to AI 00:07:05 - How to Choose the Best AI Agent Harness 00:08:31 - How to Manage Your Developer Innovation Budget 00:10:17 - Are We Losing Pair Programming to AI Agents? 00:12:14 - Cognitive Surrender: The Hidden Threat of Generated Code 00:13:40 - The Verification Bottleneck: How to Trust AI Code 00:15:59 - How to Safely Scale Your Personal AI Bandwidth #AIAgents #SoftwareEngineering #DeveloperProductivity

    18分
  4. What World Class Software Engineers Do That You Don't

    5月20日

    What World Class Software Engineers Do That You Don't

    After 250 episodes of Beyond Coding, a pattern shows up again and again: the engineers who thrive aren't the ones chasing the newest tool or the cleanest code. They're the ones who learn fast, keep things simple, and understand the business they're building for. This special pulls the sharpest moments from recent guests into one conversation about what actually makes a great software engineer in 2026. We cover: Why learning is the only skill that outlives every tool, language, and platformHow the best architects act more like scouts than cartographersWhy "simple is complicated enough" beats clean code dogma at scaleHow to design systems that evolve instead of trying to predict 10 years outWhat junior engineers should actually do in the age of AI agentsFor software engineers who want to think clearer, build better, and grow into the kind of engineer companies can't replace. Timestamps: 00:00:00 - Intro 00:00:17 - Why You Should Increase Your Breadth, Not Just Focus 00:02:16 - The Only Skill That Survives Every Tech Cycle 00:04:14 - Buzzwords Are Just Old Ideas in New Clothes 00:05:26 - What Clients Say vs What They Actually Want 00:06:45 - The Bad Architects Are Easier to Spot 00:08:50 - Why Good Engineers Use Boring Technology 00:11:40 - Stop Building for 100x Scale on Day One 00:13:13 - The Dogma of Clean Code Is Hurting You 00:15:15 - Simple Is Complicated Enough at Scale 00:16:28 - Design Only for the Next Order of Magnitude 00:18:19 - How to Talk Tech with Non-Technical Stakeholders 00:19:30 - The $50,000-Per-Hour Container Terminal Lesson 00:22:11 - Architects Are No Longer Cartographers, They're Scouts 00:25:18 - Start with a Question, Not an Answer 00:26:49 - Junior to Senior in the Age of AI Agents 00:27:29 - Don't Be a Fool with a Tool 00:29:43 - From Explicit to Implicit Knowledge Economy 00:30:38 - Use AI to Validate, Not to Generate #softwareengineering #engineeringcareer #softwarearchitecture

    33分
  5. What Separates Cracked Software Engineers From Everyone Else

    5月6日

    What Separates Cracked Software Engineers From Everyone Else

    Reddit Reacts is back. I'm taking the most controversial takes on software engineering from Reddit and giving you my unfiltered perspective on what's happening, from juniors leveraging AI tools, to the culling of engineers who refuse to adapt, to whether you should take a gap year after a layoff. In this episode, we cover: How to become technically "cracked" and what really separates great engineersWhy juniors learning with AI have an edge over 20-year veteransThe future of writing code by hand (and why fulfillment is shifting)Vibe coding, security holes, and what happens after 6 monthsThe brutal reality of layoffs, gap years, and AI-driven hiringIf you're an engineer trying to figure out where this industry is going and how to stay competitive, this one is for you. Mentioned in the episode:⁠ADP List⁠ - free mentorship from senior engineers Timestamps: 00:00:00 - Intro 00:00:54 - How to Become Technically Cracked in 2026 00:05:35 - Will Juniors Who Only Code with AI Get Stuck? 00:09:26 - Will Senior Engineers Stop Writing Code By Hand? 00:11:11 - I Vibe Coded for 6 Months and It's a Disaster 00:15:04 - Why Leaders Demand Screen Sharing on Incident Calls 00:17:34 - "I Don't Do Anything and Still Get Promoted" 00:20:33 - Have the Best Engineers Stopped Applying? 00:25:39 - The Future of Software Engineering in the AI Era 00:32:15 - Are Most Programmers Actually Bad? 00:34:58 - Should You Take a Gap Year After a Layoff? #softwareengineering #aicoding #techcareers

    39分
  6. How the Best DevOps Engineers Are Using AI to Get Sh*t Done

    4月29日

    How the Best DevOps Engineers Are Using AI to Get Sh*t Done

    Most engineers are using AI coding tools without understanding what they actually are and it's costing them. Microsoft Certified Trainer Rob Bos has trained thousands of engineers on AI tooling, and he sees the same gaps in fundamentals show up again and again, regardless of seniority. This is what you need to know: What an LLM actually is (and why understanding this changes how you use it)Why prompt engineering isn't optionalHow AI magnifies your existing technical debt instead of fixing itThe 6-month learning curve nobody warns you aboutWhy your role as an engineer was never about writing codeThe environmental cost behind every promptWhether you're skeptical of AI tools or already living in agent mode, these are the fundamentals that separate engineers who get real value from those who get burned by the hype. Connect with Rob: https://www.linkedin.com/in/bosrob References:Token tracker: https://marketplace.visualstudio.com/items?itemName=RobBos.copilot-token-tracker Dev survey: https://www.activestate.com/wp-content/uploads/2019/05/ActiveState-Developer-Survey-2019-Open-Source-Runtime-Pains.pdf Timestamps: 00:00:00 - Intro 00:00:43 - The #1 Thing Engineers Get Wrong About AI 00:02:09 - How Much LLM Theory Do You Actually Need? 00:03:58 - Why Pair Programming Is Still the Best Way to Learn AI 00:05:26 - Why Rob Skips Tab Completion and Lives in Agent Mode 00:07:03 - The "AI Doesn't Increase Productivity" Debate 00:08:29 - Why Your Real Job Was Never Writing Code 00:09:14 - The 2-Hours-of-Coding Problem No One Talks About 00:11:02 - More Code = More Pressure on Your Review Process 00:12:21 - Why AI Magnifies Existing Technical Debt 00:13:39 - The Customer Who Couldn't Start AI With Developers Yet 00:15:11 - The Future Engineer: Reviewer, Not Writer 00:17:00 - Convincing the AI Skeptic Who Tried It Years Ago 00:19:17 - LLMs Explained Without Visuals (Attention & Semantics) 00:22:41 - Why Prompt Engineering Actually Matters 00:24:20 - From Zero to Hero: The 6-Month Learning Curve 00:26:18 - Is This Confrontational for 20-Year Veterans? 00:29:30 - Becoming a Better Engineer by Thinking in Systems 00:31:26 - Will AI Stop Working as Innovation Slows? 00:34:26 - The Lost Art of Pair Programming with AI 00:35:44 - Tribalism in AI Tools (And Why It's Pointless) 00:37:33 - Tool Agnostic: Start With the Foundations 00:39:40 - Is the IDE Still Relevant? 00:40:50 - The Bluescreen Story That Changed His Mind 00:41:47 - The Hidden Environmental Cost of AI Coding 00:44:15 - 36 Million Tokens in 30 Days: What Does It Mean? 00:45:47 - Running LLMs at the Edge to Cut the Footprint 00:46:48 - Why You Should Be Allowed to Wait Five Minutes Longer 00:47:05 - Outro #githubcopilot #aicoding #softwareengineering

    47分
  7. Why World Class Engineers Don't Apply For Jobs

    4月22日

    Why World Class Engineers Don't Apply For Jobs

    Most engineers approach open source the wrong way. They write code, open a PR, and wonder why it never gets merged. Bruno Schaatsbergen, Terraform core contributor and ex-HashiCorp engineer, breaks down the real craft behind contributions that actually land, and why AI is quietly breaking the ecosystem we all depend on. In this episode, we cover: Why pull requests get ignored (and the counterintuitive fix)How AI slop is killing open source from the insideUsing AI agents without losing your identity as an engineerWhy open source beats a tailored resume in today's marketHow consistent contributions can reshape your entire career If you've ever wanted to contribute to open source but didn't know where to start, this episode gives you a clear perspective from someone who's been on both sides. Connect with Bruno: https://www.linkedin.com/in/bschaatsbergen OUTILNE 00:00:00 - Intro 00:01:04 - How Open Source Shaped My Entire Career 00:02:14 - Why I Take Pride in Every PR I Write 00:03:16 - Open Source vs Personal Projects: The Real Difference 00:04:18 - Why Your PRs Get Ignored (And How to Fix It) 00:05:41 - Know Your Audience: The Counterintuitive PR Hack 00:06:35 - Dealing With Imposter Syndrome as a Contributor 00:07:10 - Read Code Like a Writer Reads Books 00:09:31 - My First Contribution (And How It Changed My Career) 00:10:51 - Should You Contribute to Open Source Early in Your Career? 00:12:46 - The Dark Side: When Contributions Become Noise 00:13:44 - Killed With Kindness: The AI Slop Problem 00:16:17 - How Maintainers Are Fighting AI Slop 00:18:02 - How I Actually Use AI Agents in My Workflow 00:19:11 - Don't Outsource Your Thinking to AI 00:20:11 - Who's Liable for AI-Generated Code? 00:21:16 - Earned Rights: Why Trust Matters in Open Source 00:22:52 - How to Approach People at Tech Conferences 00:24:52 - Open Source Is Not a Democracy 00:26:04 - Why Open Source Beats a Tailored Resume 00:27:12 - Never Contribute With the Goal of Getting Hired 00:28:38 - The Real Reason Consistency Pays Off 00:29:30 - Admitting I'm a University Dropout 00:30:42 - Why I Haven't Contributed in Weeks (And That's Okay) 00:32:07 - The Trap of Chasing Contributor Rankings 00:34:32 - Open Source Lets You Work With Anyone in the World 00:35:52 - Final Advice: Don't Let AI Steal Your Identity

    38分
  8. Software Expert: This Is How You Design Systems That Survive

    4月15日

    Software Expert: This Is How You Design Systems That Survive

    What separates software that survives from software nobody wants to touch? Nico Krijnen has spent 30 years building systems, coaching teams, and learning why some projects thrive while others quietly become the legacy code everyone avoids. In this episode, he shares why the real work starts after you ship, what actually turns a system into legacy, and why the knowledge in your team's heads matters more than the code itself. In this episode, we cover: Why production is where the real learning beginsThe team composition that consistently delivers resultsPeter Naur's Theory Building and why documentation alone falls shortHow knowledge leaving your team turns working systems into legacyWhy assuming you're wrong leads to better architectureWhether you're a senior engineer rethinking how you build or earlier in your career trying to understand what really matters, this episode will change how you think about software that lasts. Connect with Nico: https://realworldarchitect.dev TIMESTAMPS 00:00:00 - Intro 00:01:17 - Why He Keeps Choosing Engineering Over Management 00:04:01 - Three Seniors Solved in Three Weeks What Management Couldn't 00:05:14 - The Signals You Miss When You're Not in the Team 00:06:26 - The #1 Skill Behind Every Successful Project 00:08:04 - Why Production Is the Starting Line, Not the Finish 00:10:13 - The Habit Most Teams Skip After Deploying 00:11:28 - Why the Best Teams Mix Designers and Engineers 00:14:36 - Finding the Right People for the Job at Hand 00:17:01 - What Juniors Bring That Seniors Can't 00:20:57 - How to Handle Ideas You Disagree With as a Senior 00:24:21 - A Simple Technique to Surface Everyone's Best Ideas 00:27:09 - What Makes a System Survive Long-Term 00:30:53 - What Actually Makes a System "Legacy" 00:35:01 - The Knowledge That Keeps Software Alive 00:36:06 - Peter Naur's Theory Building: Why Documentation Isn't Enough 00:40:06 - How Knowledge Loss Is Killing Your Codebase 00:42:42 - The Hidden Risk of AI Tools for Team Knowledge 00:48:14 - Why You Should Assume Everything You Build Is Wrong 00:51:31 - Make Hard Things Easy to Change #SoftwareEngineering #SystemDesign #TechPodcast

    54分
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番組について

For software engineers ready to level up. Learn from CTOs, principal engineers, and tech leaders about the skills beyond coding: from technical mastery to product thinking and career growth. Created by Patrick Akil

情報

  • クリエイター
    Patrick Akil
  • 配信期間
    21年 - 26年
  • エピソード
    254
  • 制限指定
    不適切な内容を含まない
  • Copyright
    © Patrick Akil
  • 番組のWebサイト
    Beyond Coding

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