Beyond Coding

Hosted by Patrick Akil

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Aug 2026

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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

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August 19, 2026Episode 26441 min

How Amazon Turns Real Failures Into Better AI Models

How does Amazon build its agentic AI? Michael Giannangeli, Head of Product for Amazon Nova and Agentic AI, breaks down evals, RL gyms, and model routing. He also explains why the bottleneck in software has shifted away from engineering hours and what takes its place. In this video, we cover: The eval lifecycle: building from real failure modes, saturation, and why 100% means delete RL gyms: training models on real environments like migrations, DevOps, and pen testing Model routing, cost-per-token trade-offs, and why routing isn't solved The agent stack of an Amazon product lead: Claude Code, Codex, and Kiro Autonomous migrations, trust, and how much human-in-the-loop survives For engineers and product people building with AI agents who want to see how a frontier lab actually closes its feedback loops. Recorded at the AI4 conference 2026. Timestamps: 00:00:00 - Intro 00:00:36 - The Agents an Amazon Product Lead Uses Daily 00:03:36 - Why Nobody's Heard of Amazon Nova 00:04:55 - Model Costs and the Routing Problem 00:08:10 - Why Building Good Evals Is So Hard 00:10:05 - When Evals Saturate and Get Deleted 00:12:17 - Turning Real Failure Modes Into Hundreds of Evals 00:15:26 - Improving Models Without Training on Customer Data 00:18:26 - If Everyone Uses Agents, You Need Agents 00:20:22 - The Bottleneck Is No Longer Engineering Hours 00:23:20 - Ship Fast to Validate the Right Thing 00:26:44 - Staying at the Frontier Amid Constant Noise 00:29:37 - Spend 10-20% of Your Time Experimenting 00:32:54 - RL Gyms: How Models Learn From Failure 00:37:09 - Will Migrations Become Fully Autonomous? Guest: Michael Giannangeli - Head of Product, Agentic AI & Amazon Nova at Amazon #AmazonNova #AgenticAI #AIEngineering

August 12, 202624 min

Wes Bos: How Developers Stand Out When AI Writes the Code

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

August 5, 2026Episode 26255 min

Career Advice Every Software Engineer Needs Right Now

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

July 29, 2026Episode 2611 hr 22 min

DX Expert: What The Best Engineers Solve After The Code Review Bottleneck

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

July 22, 2026Episode 2601 hr 53 min

AWS Veteran: The New Software Development Life Cycle

"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 available for 1400 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

July 15, 2026Episode 25928 min

Vercel VP: What Senior Engineers do Differently

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. This podcast was recorded at TechLead Conference, a conference for engineering leaders on adopting AI. 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

July 9, 2026Episode 25840 min

Cracked Solo Dev: Why the Fastest Engineers Are Falling Behind

The fastest engineers are falling behind, and Kitze was one of them. He built his reputation on raw coding speed, then realized his coding wasn't competing with anyone's coding anymore, it was competing with their setups. Wake-up call for developers: Kitze now runs 140 projects solo with agent loops, and in this episode he breaks down what separates the engineers pulling ahead from the ones getting left behind. In this episode, we cover: Vibe coding vs vibe engineering, and how to get better results from your agents Police files: Self-correcting loops that end every agent turn with zero errors Why teams of 10 are collapsing into teams of 2, and who survives The rude awakening coming for engineers who refuse to adapt The number one advice to stay on track and fight FOMO For individual contributors, tech leads, and principal engineers who don't plan on falling behind This podcast was recorded at React Summit, the biggest React conference worldwide. TIMESTAMPS: 00:00:00 - Intro 00:00:40 - Vibe Coding vs Vibe Engineering: The Real Difference 00:02:16 - Police Files: The Self-Correcting Loop on Every Turn 00:05:23 - Capture Every Frustration as a Rule 00:06:53 - Why Being the Fastest Coder Stopped Mattering 00:09:45 - Problem Solver vs Problem Lover: Pick One 00:10:43 - The Rude Awakening Engineers Don't Want 00:12:05 - Why Teams of 10 Become Teams of 2 00:13:09 - Loop Engineering: The Edge Anyone Can Build 00:16:08 - Why No Agent Orchestrator Works Yet 00:17:07 - Starting a Fresh Codebase: What Kitze Transfers 00:19:14 - No Sidebars: Inventing an Agentic OS 00:21:07 - How Kitze Shipped 300 Changes Across 200 Repos 00:23:40 - We Are Becoming the Bottleneck 00:24:25 - Why Leadership Must Give Engineers Room to Experiment 00:26:16 - The Token Divide: Not Everyone Can Compete 00:27:41 - Learn Now or Lose Access Later 00:29:33 - The Culling: Coasting Is Going Away 00:30:45 - Why LLM Code Reviews Beat Tired Seniors 00:33:21 - Solo Engineers With Agent Swarms vs Teams 00:34:53 - Agents Climbing the Org Chart to CEO 00:36:03 - What Distinguishes the Best Engineers: Unblocking 00:36:50 - Ego Is the Real Bottleneck 00:37:55 - Kitze's #1 Advice: Stick to One Model

July 1, 2026Episode 25758 min

AI Cloud CTO: Why These Engineering Skills Get You Hired No Matter What

Danila Shtan runs engineering at Nebius, one of the biggest AI clouds in the world, and he told me exactly which engineers he hires on the spot. There are only hundreds of people on the planet with the skill he wants most, and it is not the one you are grinding on. We get into which engineering skills are actually scarce and well paid today, and which ones are quietly on the way out. In this episode we cover: The engineering skills in highest demand right now and which ones are on the way out Why an AI cloud CTO restricts Claude Code inside his own company Dan's rule for merging any AI-written code into production Why working with an agent is like managing a junior engineer The interview question that surfaces top tier engineer qualities Why he still runs algorithm interviews today If you are an engineer trying to work out where the value sits now that agents write the easy code, this is a straight answer from the person building the infrastructure underneath all of it. Timestamps: 00:00:00 - AI Agents doing everything is a lie 00:00:44 - What Nebius Actually Does 00:04:31 - The Engineers In Highest Demand Right Now 00:06:58 - Inside the Hiring Process 00:08:12 - The Bootcamp: You Join the Company, Not a Team 00:10:51 - Why You Can't Use AI in Their Interviews 00:16:31 - Why He Banned the Word "Headcount" 00:22:25 - Why a CTO Is Not a Technical Role 00:24:49 - The One Skill Every Manager Needs 00:25:48 - Why Smart People Fail at This 00:28:17 - "The Promise of Agents Is Bullshit" 00:31:39 - How AI Multiplies Your Baseline Skill 00:35:32 - Why an AI Agent Is Just a Junior Engineer 00:36:57 - Why He Won't Let His Team Use Claude Code 00:37:46 - His Rule for Merging AI-Written Code 00:40:28 - The Interview That Predicts Great Engineers 00:42:32 - From T-Shaped to Round-Shaped Engineers 00:44:30 - Is There Still a Path for Juniors? 00:45:28 - Why Hard Skills No Longer Matter 00:47:11 - The Engineers Who Will Become Obsolete 00:50:04 - The Real Reason People Stay at Banks 00:52:26 - Where AI Agents Actually Help 00:54:40 - Why He Still Uses Algorithm Interviews 00:56:05 - Tech Enthusiasts vs. Real Engineers #AIEngineering #TechCareers #SoftwareEngineering

June 24, 2026Episode 25746 min

Tech Career Expert: Why Applying to Jobs No Longer Works

120,000 tech workers have been laid off in 2026, yet there are 60,000 open roles. Engineers applying are sending out 100 applications for zero replies. Former Reddit, Uber and Disney Plus recruiter Keki Mwaba breaks down why the market broke, why every resume now looks identical, and what gets you hired when yours looks like everyone else's. In this video, we cover: Why 120,000 layoffs and 60,000 open roles don't add up Why CVs have become too good and it's no longer enough How to treat LinkedIn as a platform Getting into companies like OpenAI and Anthropic How to reach out to people without seeming fake If you're a software engineer trying to stand out in the most competitive tech market in years, this is the playbook. Timestamps: 00:00:00 - Intro 00:00:35 - How bad is the tech job market in 2026? 00:02:38 - 120,000 laid off, 60,000 jobs open: the math is not mathing 00:04:05 - LinkedIn isn't a CV, it's a platform 00:08:30 - The underrated move: comment your way into a job 00:10:48 - Is AI ruining LinkedIn? 00:13:50 - Never feel safe: how to prepare before a layoff 00:15:34 - What layoffs do to the people who stay 00:17:03 - "Did I just automate myself out of a job?" 00:18:48 - Why every resume now looks the same 00:20:11 - Why referrals beat applications 00:22:13 - Do software engineers still have a future? 00:23:32 - The staff engineer who wants to quit for plumbing 00:26:16 - Patrick on his own job security 00:30:21 - 70% of job descriptions now demand AI skills 00:31:34 - Is middle management disappearing? 00:33:53 - The impossible ask: stay current, deliver, and not burn out 00:37:02 - How to get hired at OpenAI or Anthropic 00:39:18 - How to message someone without seeming fake 00:41:42 - Build a portfolio that shows your thinking 00:45:12 - Your personal branding plan for the next few weeks Guest: Keki Mwaba, career and recruitment expert: https://www.linkedin.com/in/keki-mwaba #techjobs #softwareengineering #careeradvice

June 17, 2026Episode 25551 min

AI Frontrunners: Why Coding is Solved But Engineering is Not

Jeroen Gordijn and Jeroen Dee: two frontrunners who stopped writing code months ago and say software development is already solved. Typing code is no longer necessary, but what matters more now? If you're an engineer that loves coding, you're in a tougher spot than you might realize. In this video, we cover: - Why writing code is "solved" but engineering isn't - Spec-driven development and how to get it started in your team - The "Dark Factory" and why code review is a huge bottleneck - Model vs harness: what matters more, and why - The unhealthy side of agentic coding If you write software for a living and you're trying to work out what your job becomes next, start here. Timestamps: 00:00:00 - Coding Is No Longer Necessary 00:00:43 - Why "Software Development Is Already Solved" 00:02:57 - Should You Even Read the AI's Code? 00:05:05 - What Is a "Dark Factory"? 00:06:52 - If You Can Regenerate It, Why Care About Quality? 00:07:49 - Spec-Driven Development Explained 00:11:32 - Adopting Specs Without Starting From Scratch 00:13:23 - Model vs Harness: What Matters More? 00:17:27 - Is Your Harness the New IDE? 00:20:18 - Why Everyone Plateaus (and the Innovation Token) 00:22:50 - Where to Actually Spend Your Time 00:24:57 - The Unhealthy Side: "It's Free Cocaine" 00:28:00 - Is This Sustainable, or Just Subsidized? 00:30:33 - Should You Run Models Locally? 00:34:31 - Looping, Scale, and Automating Review 00:37:53 - What's Left for Engineers to Do? 00:39:13 - If You Love Writing Code, You're in Trouble 00:41:18 - Why Teams Are Getting Smaller 00:43:03 - What an "Agentic Company" Looks Like 00:46:25 - How to Start: Find Your Spark 00:50:13 - The One Habit That Keeps You Ahead Guests: Jeroen Gordijn: https://www.linkedin.com/in/jeroengordijn Jeroen Dee: https://www.linkedin.com/in/jeroendee #AgenticEngineering #SoftwareEngineering #Agents