Beyond Coding

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

Beyond Coding is a technology podcast hosted by Patrick Akil, with 263 episodes on record and a Required Pod Score of 80. PitchCentric scores this show on Booking Probability, Listen Score, and live audience signals refreshed every 24 hours.

Patrick Akil hosts Beyond Coding, a technology show with 263 episodes published.

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  Beyond Coding

  Wes Bos: How Engineers Solve Problems Beyond Syntax

  Aug 12, 202625 min

  AI is changing what developers build, but code alone is no longer enough to prove what you can do. Wes Bos explains why engineers need to solve problems beyond syntax, how agent workflows are reshaping software development, and what still requires human thinking. In this conversation: The limits of generative UI and AI-generated design Agent loops, harnesses, and cheaper AI models The rising cost of AI coding and the case for local hardware Why developer education is shifting from syntax to problem-solving Personal branding, conferences, newsletters, and AI-generated content For developers navigating AI-assisted coding, this episode explores the skills and signals that still help you stand out. This podcast was recorded at JSNation, the key web dev conference. OUTLINE 00:00:00 - Code Is Not Enough for Developers 00:00:32 - Why Generative UI Still Feels Unfinished 00:04:35 - How Agent Loops Improve AI Coding 00:07:06 - When Agent Workflows Become Standard Tools 00:08:19 - Are Cheaper AI Models Good Enough? 00:10:44 - Can AI Coding Costs Stay Sustainable? 00:12:24 - What Engineers Need To Learn Now 00:14:23 - Why Fundamentals Matter Beyond Syntax 00:15:34 - How Non-Coders Are Building Production Tools 00:16:21 - Why In-Person Conferences Still Matter 00:18:11 - Personal Branding When Code Isn't Enough 00:20:37 - Can Newsletters Beat The Attention Crisis? 00:22:02 - Why AI-Generated Content Feels Insulting 00:24:12 - Use AI To Scaffold, Not Think

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  Episode #262

  How I Broke Production and Why I'm Glad I Did

  Aug 5, 202655 min

  Answering engineer questions on AI pressure, career growth, product thinking and impact. Including the production incident I'm glad happened, and the mindset I refuse to accept when things break. In this video, we cover: - Whether managers are really demanding more output because of AI - Balancing fundamentals with AI coding tools and agents early in your career - Specialist vs generalist and when to lean into each - Visibility, personal branding and who gets credit for your work - Product thinking, evaluating impact and what I got wrong about content being king For software engineers at any level who want honest answers on career strategy in the agent era, from someone doing both engineering and product. Timestamps: 00:00:00 - How to Spot the Next Big Thing 00:03:15 - The Saying I Hate Most 00:04:27 - The Production Mistake I'm Glad I Made 00:07:32 - Are Managers Demanding More Because of AI? 00:13:39 - Learning Fundamentals vs AI Coding Tools 00:19:00 - Will AI Ever Get Good at Distributed Systems? 00:20:51 - Specialist vs Generalist: When to Lean In 00:26:35 - How to Become More Visible in Your Org 00:31:49 - I Was Wrong: Content Isn't King 00:35:03 - Workflows, Priorities and Hiring an Editor 00:37:08 - What Being a Force Multiplier Really Means 00:41:26 - How to Evaluate What's Worth Building 00:45:01 - Product Thinking Without Years of Experience 00:48:13 - Energy Management, Curiosity and Defining Success 00:54:21 - Hair Talk

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  Episode #261

  The AI Spend Question Nobody Can Answer

  Jul 29, 20261h 22m

  How do you prove AI is shipping more features? Amos Haviv leads the Developer Workflow teams at Booking.com, supporting 4000 engineers operating 8000 repos. Everybody is burning through their AI budget right now and almost nobody can answer what it bought them. Amos can, because his team spent four years building an event system to debug their own SDLC before AI upped the urgency. In this video, we cover: Why verification is the bottleneck right now, and where it moves next Building an event store that separates KTLO from real feature delivery Why static dashboards create the metric they measure, and the cobra story behind it Agent cost, model routing, and why Booking ignores token maxing entirely Running a developer survey with a 92% response rate across 3k+ engineers Who should own skills and MCPs: a central platform team or the domain experts? For platform engineers, engineering leaders, and anyone being asked to prove ROI on AI tooling this quarter. Timestamps: 00:00:00 - Everyone is burning through their budget 00:00:32 - Verification Is the Bottleneck Every Team Hit 00:03:35 - 4,000 Engineers and 8,000 Repos at Booking.com 00:06:48 - Why Copying Google and OpenAI Will Break You 00:09:21 - Verification Is a Stack of Agents, Not One Review 00:13:27 - Cost Is Becoming a Bottleneck of Its Own 00:17:14 - Was the Internet a Bubble? What That Teaches Us 00:25:32 - What Working With the Frontier Labs Looks Like 00:28:26 - Debugging the SDLC With Four Years of Event Data 00:30:24 - Do Engineers Using AI Actually Ship More Features? 00:37:13 - Where to Start If You Measure Nothing Today 00:45:01 - The Cobra Effect: When a Metric Becomes a Target 00:52:23 - Everyone Is a Builder Now, and Everything Needs Support 01:01:21 - Is AI Turning Every Engineer Into a Manager? 01:03:46 - The Developer Survey With a 92% Response Rate 01:10:09 - Who Owns Skills, MCPs, and the Enterprise Harness 01:17:46 - Great Developer Experience Is High Velocity Mentioned in the episode: High Output Management by Andy Grove The Sovereign Individual (1997) The story of General Magic Views expressed are Amos's own and do not represent Booking.com. #AI #SoftwareEngineering #DeveloperExperience

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  Episode #260

  AWS Veteran: How Real Engineering Teams Run Agents

  Jul 22, 20261h 53m

  "I need to stop using Opus. This doesn't work." That was Heitor Lessa's conclusion after a refactor cost him 200 million tokens, and it forced him to rebuild the entire agent workflow now used across 1,400 engineers. Heitor spent 11 years at AWS, built Lambda Powertools to 230 billion API calls a week, and in this episode he walks through the full SDLC workflow on screen, from discovery to merge check. In this episode, we cover: The product loop: discovery, whiteboarding, and the /roadmap command Spec-driven development with Open Spec and why vanilla setups fail Three model tiers: SOTA for planning, mid-tier for implementation, cheap models for reviews Merge checks with adversarial reviewers and attestations that catch agents fabricating test results The /retro command: using the Socratic method to make your workflow more deterministic If you're an engineer figuring out how to work with agents at team scale without losing trust in your codebase, this is the workflow to steal. This is also the first Beyond Coding episode with visuals on screen, so let me know what you think of the format. Timestamps: 00:00:00 - The Math Doesn't Add Up 00:00:43 - Amazon Hypergrowth: 11 Years, 8 Different Roles 00:03:29 - Learning From the Trenches as a Technical Account Manager 00:08:38 - Developer Identity and the Birth of Lambda Powertools 00:10:20 - The Hard Parts of Working in Public 00:13:12 - How Powertools Hit 230 Billion API Calls a Week 00:16:42 - Career Advice: Learn Adjacent Roles, Not More Tech 00:19:37 - When Leadership Decisions Don't Make Sense to You 00:23:21 - The Product Loop Starts With Discovery 00:25:22 - From Whiteboard to /roadmap 00:27:37 - Why Humans Plan First and Agents Come Second 00:30:33 - Commands vs Skills Across 32 Different Models 00:33:38 - Adversarial Reviewers on Every Plan 00:36:07 - The Socratic Method, Explained 00:40:29 - Why He Only Takes Paper Notes 00:44:43 - The Five-Line Paper Trick for High-Stakes Meetings 00:48:18 - /new-work: Capturing Scope Creep Without Derailing 00:54:03 - The Dev Loop Begins: Open Spec Explore 00:56:34 - Three Model Tiers: SOTA, Mid, Cheap 00:57:43 - The $5,000/Month Per Engineer Question 00:58:57 - Guardrails vs Autonomy for 1,400 Engineers 01:04:22 - Auto-Sizer: Does This Task Even Need a Spec? 01:07:26 - Decision Fatigue and Why Frameworks Win 01:09:10 - The Plan Phase: Specs, Design, Formal Verification 01:13:07 - The Refactor That Cost 200 Million Tokens 01:15:11 - When Agents Forge Evidence They Ran Your Tests 01:17:27 - Local-First Architecture Explained 01:23:04 - The Apply Phase: Fully Autonomous Loops 01:24:30 - Coding Was Never the Bottleneck 01:26:39 - Why This Workflow Is an Investment 01:27:39 - Decision Logs and the /onboarding Command 01:29:06 - Running Agents Locally With Enterprise Governance 01:32:42 - Hooks: Making Quality Gates Deterministic 01:36:02 - Merge Checks: 15 Adversarial Reviewers Per Change 01:38:30 - /retro: Interviewing Yourself to Improve the Loop 01:43:12 - Trust, Loss of Trust, and Recovery With Agents 01:48:02 - Experience, Scars, and Critical Thinking 01:49:32 - Why Right Now Is the Time to Experiment 01:52:04 - Conviction Comes From Being in the Loop #softwareengineering #aiagents #aws

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  Episode #259

  What Senior Engineers do Differently (Vercel VP)

  Jul 15, 202628 min

  What senior engineers do differently has less to do with output than most career ladders suggest, and Lindsey Simon, VP of Engineering at Vercel, has watched the distinction sharpen as everyone in the valley becomes a "member of technical staff." From why new grads with hackathon years might out-prepare engineers with six years on the job, to what happens when PR throughput stops being your lever, this is a conversation about what earns seniority now. In this episode, we cover: Why engineering roles are consolidating into "member of technical staff" How to ask agents first and frame better questions to humans The scope-of-impact ladder and what the best engineers systematize Learning how to learn: closing gaps to 100% understanding Why writing is the skill that scales If you're wondering whether your years of experience still compound, or you're early-career and tired of the "woe is the juniors" narrative, this one reframes both. TIMESTAMPS 00:00:00 - Impact the Business 00:00:31 - FOMO all the time: The 2006 Google Interview 00:01:52 - Engineering Roles Are Consolidating 00:02:52 - The "Member of Technical Staff" trend in SF 00:03:33 - Interns Demo to the CTO 00:04:33 - How New Grads Out-Prepare Senior Engineers 00:06:10 - Ask Your Agent Before You Ask a Human 00:08:01 - Digging Backwards Into Fundamental Understanding 00:09:22 - "We're All Junior Engineers Again" 00:10:22 - Management Is Not Leadership 00:12:04 - Losing PR Throughput as Your #1 Lever 00:13:11 - Fulfillment Beyond Shipping Features 00:14:32 - Building for Fickle Engineers: Telemetry Beats Opinions 00:16:11 - Watching Users Struggle With Your Product 00:18:12 - Have Expectations for Seniors Actually Changed? 00:19:57 - Claude Says a Month, It Takes Two Hours 00:20:33 - What the Best Engineers Do Differently 00:21:30 - How Vercel React Skill Came to Be 00:22:23 - Why Conference Conversations Hit Different 00:23:35 - Learning How to Learn: Close Gaps to 100% 00:25:41 - The Case for Liberal Arts in Tech 00:27:03 - Get Feedback Early, Don't Hide in the Cave Guest - Lindsey Simon, VP of Engineering at Vercel: https://www.linkedin.com/in/lindseysimon #softwareengineering #ai #careergrowth

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