Coding Agents Are Secretly General Agents

Coding Agents Are Secretly General Agents

Author: Demetrios June 27, 2026 Duration: 1:12:02

In this episode:

🧠 Coding agents are generalist agents — why "positive transfer" means an agent that's better at code is better at everything, and how that makes them "AGI-complete"

⏳ "Code will be solved in a year" — what the automation of knowledge work actually looks like, and why Jay joined ClickUp to be on it

🏗️ Why the labs are crushing AI startups — free-for-two-years deals, Windsurf losing Claude access, and the brutal economics of building on top of frontier models

🔗 The real moat is convergence — context, surfaces, and unit economics, a.k.a. "Cursor for your whole job"

💬 Slack's data walls & the Glean problem — why fragmentation is the enemy and a single system of record wins

🧪 RLVR & verifiability — why code became the perfect training ground for agents, and how to tell if you're even getting better

🔬 LLMs are running the frontier of science — Putnam 12/12, Erdős problems, simulating a cell, and vibe-writing economics papers

🚗 The car wash test that still breaks GPT-5 — spiky models, world models, Plato's cave, and the "stochastic parrot" debate

🏖️ Plus: mechanistic interpretability as "brain surgery," catastrophic forgetting, the danger of deleting knowledge from models, and a pitch for a "resort for LLMs"


Whether you're building agents, leading an AI team, or just trying to figure out what "agentic" really means for everyday work — this one's a fun, deep ride.


đź”— Links & Resources

Jay Hack: linkedin.com/in/jayhack

ClickUp: clickup.com

MLOps Community: go.mlops.community


Mentioned: Gödel, Escher, Bach (Douglas Hofstadter) · "Machine Learning: The High-Interest Credit Card of Technical Debt" (Sculley et al.) · Periodic Labs · Ginkgo Bioworks · Physical Intelligence


⏱️ Timestamps

[00:00] AI Timeline

[00:22] AI Startups and Timing

[06:30] GPT-3 Impact

[13:24] Selling CodeGen to ClickUp

[19:31] AI Interaction Patterns

[28:41] Slack and AI Agents

[36:11] ClickUp Task Automation

[41:32] AI in Scientific Research

[48:48] Human Understanding vs AI

[54:18] Catastrophic Forgetting Explained

[59:59] AI Delegating to Humans

[1:05:00] Agent-Based Game Integration

[1:08:42] LLM vs Game Design

[1:11:27] Wrap up


#AIAgents #AgenticAI #ClickUp


Hosted by Demetrios, MLOps.community is a space for honest, meandering talks about the real work of making artificial intelligence systems actually work. This isn't about hype or theoretical papers; it's about the messy, practical, and often surprising journey of taking models from a notebook into a live environment. You'll hear from engineers and practitioners who are in the trenches, discussing the tools, the frustrations, and the occasional breakthroughs that define the day-to-day. The conversations are deliberately relaxed, covering everything from traditional machine learning pipelines to the new world of large language models and even the intangible "vibes" of team culture and process. Each episode peels back a layer on what "production" really means, whether that involves deploying a predictive service, managing an agentic system, or maintaining reliability as everything scales. Tuning into this podcast feels like grabbing a coffee with colleagues who aren't afraid to dig into the technical nitty-gritty while keeping the tone conversational and accessible. It's for anyone who builds, manages, or is just curious about the operational backbone that allows AI to deliver value, offering a grounded perspective often missing from the broader conversation.
Author: Language: en-us Episodes: 50

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