Videos

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  Debugging the Training Pipeline (PyTorch) Hugging Face

  Debugging the training pipeline is something every practitioner wrestles with, and this walkthrough nails the common pitfalls—especially the way it sh

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  CNCF On-Demand: Cloud Native Inference at Scale - Unlocking LLM Deployments with KServe CNCF [Cloud Native Computing Foundation]

  Finally, someone is addressing the fact that standard Kubernetes schedulers choke on token-based generation. The breakdown of the Gateway Inference Ex

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  The Production AI Playbook: Deploying Agents at Enterprise Scale — Sandipan Bhaumik, Databricks AI Engineer

  The £85K chatbot PoC story is exactly the kind of war story the industry needs more of — six weeks just to build the evaluation and tracing infrastruc

Shelves rotate as new material clears the bar. These kept their pages and their analysis.

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  Engineers... STOP Picking GPT-5.6 Sol OR Claude Fable 5… FUSE THEM IndyDevDan

  The 'GPT vs Claude' war is a distraction, and IndyDevDan is right to frame model fusion as the only sane engineering choice. The concept is just the o

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  What is OpenClaw? Inside AI Agents, LLMs and the Agentic Loop IBM Technology and IBM Developer

  IBM is finally pushing past the demo-stage chatbot narrative and explaining the actual feedback loop that turns passive LLMs into executing systems. T

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  AI agent design patterns Google Cloud Tech

  Google is finally codifying what most senior engineers already know intuitively: agent architecture is about control flow, not prompt engineering. The

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  FORGET Loop Engineering. Agentic Engineering is about THIS IndyDevDan

  Dan's core argument—loops are a mental model trap, the real game is building workflows inside a software factory—is sharp and cuts through the hype. B

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  DeepSeek Just Made Closed AI Look Ridiculous Two Minute Papers

  DeepSeek’s latest speed hack forces every closed‑source vendor to rethink latency budgets, as the team shows a V4 Pro that runs circles around traditi

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  When to Build Your Own Agent Harness | Harrison Chase, LangChain Sequoia Capital

  Harrison explains that a harness is the loop that stitches context to a model, and that you only need to build your own when the task pushes outside t

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  From Primitives to Production: How Anthropic Builds Agents Databricks

  Isabella He pulls back the curtain on Anthropic’s agent stack, and the modular "Skills" idea feels like the missing piece for clean context management

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  How to build and scale multi-agent AI systems on GKE Google Cloud Tech

  Google’s GKE agentic system demo is a love letter to platform engineering, but it’s also a missed opportunity for broader accessibility. The ‘Kubernet

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  AI agent long-term memory with memory bank Google Cloud Tech

  Google's ADK Memory Bank is addressing one of the most persistent agent problems — amnesia between sessions — and this codelab walks through it with t

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  Who’s afraid of an open-weight model? GLM, context bombing and post-Black Hat attacks IBM Technology

  IBM’s podcast episode is a masterclass in balancing hype and reality, but it’s also a reminder that AI security is still a Wild West. GLM-5.3’s ‘bette

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  My M5 Max, Gemma 4, MLX LOCAL Stack. (This KILLS MODEL PROVIDERS) IndyDevDan

  Ignore the clickbait rage-bait title; the actual MLX and Gemma 4 benchmarks on the M5 Max are genuinely impressive. It's wild to see local inference s

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  But what is a neural network? | Deep learning chapter 1 3Blue1Brown

  This 3Blue1Brown video, despite being from 2017, remains one of the best explanations for the core mechanics of neural networks. His intuitive visuali

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  Agentic AI Frameworks Explained: Workflows, Multi-Agent, & Production IBM Technology

  Meenakshi Kodati maps the messy landscape of agentic frameworks, pointing out when LangChain wins versus when AutoGen’s multi‑agent dance is worth the

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  Don't Build Agents, Build Skills Instead – Barry Zhang & Mahesh Murag, Anthropic AI Engineer

  The idea of packaging procedural knowledge as reusable “Skills” instead of building full‑blown agents is refreshingly pragmatic—especially when you co

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  Ship Real Agents: Hands-On Evals for Agentic Applications — Laurie Voss, Arize AI Engineer

  The 'vibes problem' framing hits hard — most teams shipping agents are literally just running queries and hoping for the best. That 0/13 versus 13/13

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  LongCat 2.0: The Beginning of the End of NVIDIA MOAT? bycloud

  The title screams clickbait, but the deep dive into LongCat 2.0’s sparse attention mechanism is actually high-quality engineering analysis. The real s

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  They Found a Way to Steal Frontier LLM’s Reasoning bycloud

  The bycloud exposé on stealing reasoning traces feels like a wake‑up call for anyone relying on closed‑API LLMs—he walks through the encrypted‑reasoni

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  How GPT, Claude, and Gemini are actually trained and served – Reiner Pope Dwarkesh Patel

  Reiner Pope’s blackboard deep‑dive is a rare look at the full LLM stack—from chip‑level efficiency to the economics of API pricing. He walks through a

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  Stealing Reasoning Traces from Proprietary LLM APIs — Ilia Shumailov & Alexander Panfilov Machine Learning Street Talk

  Ilia and Alex expose how a simple encrypted reasoning blob can become a cross‑user replay attack, letting a tiny model hijack a proprietary model’s ch

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  Qwen-AgentWorld The World Model for Agents Sam Witteveen

  Sam does a solid job dissecting the paper, specifically the jump in performance after RL training shown at the 6:15 mark. We're moving past simple pro

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  What is an Agent Harness? (And How We Built One) AWS Developers

  The concept of a 'model-agnostic harness' is the most underrated idea in agentic engineering right now, and this demo using the Strands framework nail

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  The Most Absurd Way To Train LLMs... With 3x Less Memory!? bycloud

  That headline is pure clickbait, but the DiffusionBlocks research actually delivers on its promise. By routing gradient computation through sparse str

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  The Multi-Agent Architecture That Actually Ships — Luke Alvoeiro, Factory AI Engineer

  Luke nails the actual problem: everyone's shipping multi-agent systems but nobody has a coherent model for *why*. The three-role taxonomy (orchestrato

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  Ray Summit 2025 Keynote: AI OSS Stack Panel with vLLM + PyTorch + Kubernetes Anyscale

  The panel brings together exactly the right people — Nishihara, Chen, Spisak, Mo — but stays at conference-keynote altitude. The interoperability and

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  From Chaos to Choreography: Multi-Agent Orchestration Patterns That Actually Work — Sandipan Bhaumik AI Engineer

  Finally, someone who's actually shipped multi-agent systems in production talking about the coordination nightmare nobody blogs about. Sandipan's poin

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  OpenAI Astra and Recurrent Depth / Looped Transformers Sebastian Raschka

  Sebastian's breakdown of the rumored recurrent depth design in Astra is the kind of architectural rabbit hole that keeps me up at night. The Nanbeige4

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  You Can Learn AI Agent Harness In Real Code In 20 Min | Loop Engineering, Memory, Eval, Open Source Sean‘s AI Stories and AutoManus

  The real move here is that Sean's not explaining agent concepts in the abstract — he's walking through actual code that schedules World Cup matches on