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Artificial Developer Intelligence

Shimin Zhang, Dan Lasky, & Rahul Yadav

Three engineer friends argue about AI so you don't have to.

Shimin Zhang, Dan Lasky, and Rahul Yadav are working developers who've been watching AI transform their profession in real time, and they got opinions on the robot takeover. Every week the three get together to riff on the latest AI news, geek out over research papers, roast each other's tool choices, and occasionally have an existential crisis about whether the craft is dying or just getting weird.

What you're signing up for:
- AI news without the LinkedIn cringe: model drops, acquisitions, open-source drama, and the other stuff that actually matters if you write code for a living.
- Technique corner: real tips from the trenches: spec-driven development, multi-agent orchestration, Claude.md tricks, and all the ways they've wasted hours so you don't have to.
- Two Minutes to Midnight: the show's running AI bubble tracker, complete with circular funding diagrams, hyperscaler CAPEX math, and a doomsday clock they keep arguing about moving.
- Deep dives that (occasionally) go deep: hallucination neurons, agentic memory, workflow automation economics, LLM architectures the papers nobody else is covering because they're hard.
- Dan's Rant: Dan frequently gets mad about things. It's a whole thing.
- The feelings segment: Yes, Shimin reads Tennyson on a tech podcast. Yes, Rahul wrote an AI-generated country song. No, they're not sorry.

Three friends with strong opinions, questionable metaphors, and genuine love for the craft they're also mourning for. If you want to understand AI deeply, use it without embarrassing yourself, and laugh at the absurdity of it all, pull up a chair.

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  • 22 episodes
  • weekly
  • Avg 1 hr 7 min
  • English

Episodes 22

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  • #18
    March 20 · 1 hr 8 min

    Ep 18: 8 Levels of AI Engineering, Meta AI Delays, and LLM Neuroanatomy

    This week, Dan, Shimin & Rahul covers Meta's struggles with its delayed "Avocado" AI model and potential Gemini licensing, NVIDIA's enterprise-ready NemoClaw fork of OpenClaw, SWE-bench analysis showing PRs wouldn't pass human review, prompting superstitions and developer identity, the 8 levels of agentic engineering, mainstream media framing of AI coding, legal liability for agent-written code, and a deep dive into LLM neuroanatomy where a researcher topped leaderboards by repeating model layers without changing weights. Takeaways: Meta may end up licensing Gemini despite massive AI investment — mirroring Apple's path SWE-bench failures were mostly code quality, not functionality — suggesting good enough may be good enough with proper agents.md A coworker analyzed 4.5 years of PRs to create a personalized coding style document for AI priming The fastest software paradigm adoption cycle ever may be the claw/agent paradigm Legal frameworks and insurance haven't caught up to agent-written code shipping to production Repeating later model layers (the "thinking" layers) can boost performance without fine-tuning — raising questions about whether chain-of-thought reasoning is essentially exercising these layers repeatedly Developers compared to ancient Egyptian scribes — language literacy as leverage Resources Mentioned Meta Delays Rollout of New A.I. Model After Performance Concerns NVIDIA NemoClaw Research note: Many SWE-bench-Passing PRs Would Not Be Merged into Main The Collective Superstitions of People Who Talk to Machines The 8 Levels of Agentic Engineering Coding After Coders: The End of Computer Programming as We Know It Built by Agents, Tested by Agents, Trusted by Whom? LLM Neuroanatomy: How I Topped the LLM Leaderboard Without Changing a Single Weight Chapters (00:00) - Introduction to AI in Software Development (02:42) - Meta's AI Model Delays and Market Position (09:51) - NVIDIA's New AI Developments (13:58) - Benchmarking AI Models and Code Quality (19:00) - Techniques Corner: AI Prompting and Creativity (22:56) - The Evolution of Coding and Creativity (28:46) - Levels of Agentic Engineering (34:58) - Mainstream Perspectives on AI and Software Development (43:00) - Trusting AI-Generated Code (44:40) - Metrics for Success in Autonomous Teams (46:59) - Legal and Ethical Implications of Autonomous Code (50:21) - Innovations in Language Model Architectures (01:01:02) - User Experience Challenges in Tech Development (01:03:47) - Market Predictions and Financial Insights Connect with ADIPod Email us at humans@adipod.ai you have any feedback, requests, or just want to say hello! Checkout our website www.adipod.ai

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  • #17
    March 13 · 1 hr 2 min

    Ep 17: Slop Garbage Collection, Cleanroom Rewrites, and Will Claude Ruin our Teams?

    In this episode, Dan and Shimin follow-up on the Anthropic Pentagon drama (supply chain risk designation, lawsuit, and big tech backing Anthropic), open-source licensing controversy around AI-generated clean room rewrites, team dynamics in the age of AI coding tools, OpenAI's harness engineering blog post, two vibe-and-tell segments (Dan building custom Arch Linux images for a TuringPie cluster board, Shimin building FlatterProof — an AI sycophancy training app), and a bubble clock update driven by Oracle job cuts and AWS AI-related downtime. Takeaways AI as a force multiplier for team culture: good teams move faster, bad teams explode faster Prompt debt is now a real concern alongside technical debt — agents.md files rot just like code Code garbage collection (periodic AI-driven cleanup) is emerging as a best practice Cross-functional pair programming with AI (PM + engineer) represents a bright future for team collaboration Senior engineers now required to sign off on AI-assisted changes at Amazon, but review fatigue is unsustainable AI-generated SVG icons are surprisingly good and practical for real projects Oracle may be the canary in the coal mine for the AI bubble, not the frontier labs themselves Resources Mentioned Pentagon Refuses to Say If AI Was Used to Select Elementary School as Bombing Target Anthropic sues to block Pentagon blacklisting over AI use restrictions Alibaba’s Qwen tech lead steps down after major AI push Did Alibaba just kneecap its powerful Qwen AI team? Key figures depart in wake of latest open source release Can coding agents relicense open source through a “clean room” implementation of code? GNU and the AI reimplementations Will Claude Code ruin our team? Harness engineering: leveraging Codex in an agent-first world Oracle plans thousands of job cuts as data center costs rise, Bloomberg News reports After outages, Amazon to make senior engineers sign off on AI-assisted changes Chapters (00:00) - Introduction (02:50) - Anthropic and Pentagon Drama (05:01) - Alibaba's Qwen Development Team Changes (07:34) - Open Source Drama with CharDat Library (24:08) - The Impact of AI on Team Dynamics (29:15) - Harness Engineering and Codecs in AI Development (31:39) - Empowering Agents with Tools (34:06) - The Importance of Documentation (36:26) - Architectural Boundaries and Testing (38:29) - Innovative Projects and Personal Experiments (46:56) - Flatterproof: Combating AI Synchrofancy (54:27) - The AI Bubble Clock: Current State of Affairs (01:02:29) - ADI Intro.mp4 Connect with ADIPod Email us at humans@adipod.ai you have any feedback, requests, or just want to say hello! Checkout our website www.adipod.ai

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Showing 21–22 of 22 episodes