[2604.08224] Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering — Useful unified review of how agent “externalization” actually gets built in practice—memory stores, skill libraries, protocols, and harness tooling.… https://arxiv.org/abs/2604.08224

Center for Responsible, Decentralized Intelligence at Berkeley — A useful reality check on AI agent benchmarks: Berkeley researchers show how top leaderboards can be gamed to get near-perfect scores without doing the task. Worth reading if… https://rdi.berkeley.edu/blog/trustworthy-benchmarks-cont/

[2604.06425] Neural Computers — Useful overview of the “neural computers” idea—how models can be structured to compute with learned representations rather than just pattern-match. Worth a skim if you’re tracking where architecture and algorithm design are converging. https://arxiv.org/abs/2604.06425

Anthropic Will Use CoreWeave’s AI Capacity to Power Claude - Bloomberg — Worth a read; the useful bits are usually in the examples and edge cases. https://www.bloomberg.com/news/articles/2026-04-10/anthropic-agrees-to-rent-coreweave-ai-capacity-to-power-claude?embedded-checkout=true

Towards transparency and knowledge exchange in AI-assisted data analysis code generation | Nature Computational Science — A concise perspective on why AI-generated analysis code needs clearer provenance, documentation, and sharing norms to be… https://www.nature.com/articles/s43588-025-00781-1

Quantization from the ground up | ngrok blog — Clear, ground-level walkthrough of LLM quantization—what it is, how it works, and the real trade-offs when compressing models for deployment. Practical read if you’re deciding which quantization approach fits your… https://ngrok.com/blog/quantization

Two weeks out — here's the practical angle (tools, patterns, gotchas). LangChain for Generative AI Pipelines. Register: https://learning.oreilly.com/live-events/-/0642572002267/

Two weeks out — here's the practical angle (tools, patterns, gotchas). LangChain for Generative AI Pipelines. Register: https://learning.oreilly.com/live-events/-/0642572002267/

Three weeks out — quick preview of what you'll be able to do after this session. Claude API for Python Developers. Register: https://learning.oreilly.com/live-events/-/0642572255893/

Who Is Satoshi Nakamoto? My Quest to Unmask Bitcoin’s Creator — Worth a read; the useful bits are usually in the examples and edge cases. https://www.nytimes.com/2026/04/08/business/bitcoin-satoshi-nakamoto-identity-adam-back.html

The Cult Of Vibe Coding Is Insane - by Bram Cohen — Bram Cohen makes a clear case that “vibe coding” isn’t a harmless style choice—it’s a decision to accept lower-quality software. Worth reading if you care about maintainability and… https://bramcohen.com/p/the-cult-of-vibe-coding-is-insane

The Evolving Foundations of Math | Quanta Magazine — Math’s foundations aren’t a settled monolith—they’re still being revised in response to new ideas and edge cases. This piece is a clear look at what’s changing and why it… https://www.quantamagazine.org/series/the-evolving-foundations-of-math/

[2604.01193] Embarrassingly Simple Self-Distillation Improves Code Generation — A clean, practical paper on using simple self-distillation to boost code generation quality. Worth a skim if you’re tuning LLMs and want an approach that’s easy to implement and evaluate. https://arxiv.org/abs/2604.01193

Emotion Concepts and their Function in a Large Language Model — Useful look at how “emotion concepts” show up inside an LLM and how they can causally steer outputs. Worth reading if you care about mechanistic interpretability and how these… https://transformer-circuits.pub/2026/emotions/index.html

[2305.13707] Do All Languages Cost the Same? Tokenization in the Era of Commercial Language Models — Worth a quick read if you work with multilingual LLMs: it shows how tokenization can make some languages effectively “more expensive” than others, with real… https://arxiv.org/abs/2305.13707

Data Science Briefing #312 — A quick, practical roundup for data folks, with a note on the relaunch of the Data For Science site. Worth a skim if you like staying current without wading through long posts. https://data4science.kit.com/posts/data-science-briefing-312

Three weeks out — quick preview of what you'll be able to do after this session. LangChain for Generative AI Pipelines. Register: https://learning.oreilly.com/live-events/-/0642572002267/

OpenClaw: The complete guide to building, training, and living with your personal AI agent — A clear, end-to-end walkthrough of how to design and run a personal AI agent setup, grounded in real usage rather than theory.… https://www.lennysnewsletter.com/p/openclaw-the-complete-guide-to-building

Four weeks out — if this is on your roadmap, now's a good time to grab a seat. Claude API for Python Developers. Register: https://learning.oreilly.com/live-events/-/0642572255893/

[2603.21687] MIRAGE: The Illusion of Visual Understanding — Worth a quick read if you work with vision-language models: MIRAGE argues that apparent “visual understanding” can be an illusion driven by shortcuts, and it’s a useful lens for evaluating benchmarks and… https://arxiv.org/abs/2603.21687

Safeguarding cryptocurrency by disclosing quantum vulnerabilities responsibly — A practical look at how to handle quantum-related risks in crypto without causing unnecessary panic—focused on… https://research.google/blog/safeguarding-cryptocurrency-by-disclosing-quantum-vulnerabilities-responsibly/

[2603.14147] An Alternative Trajectory for Generative AI — A thoughtful arXiv paper arguing for a different path for generative AI than the current scale-and-scrape trajectory. Useful if you’re tracking where the field could go next—technically and institutionally. https://arxiv.org/abs/2603.14147

[2603.26524] Mathematical methods and human thought in the age of AI — Thoughtful arXiv essay on how AI is reshaping mathematical practice and, more broadly, how we think—useful if you’re trying to separate genuine insight from automated fluency. A quick read with… https://arxiv.org/abs/2603.26524

[2303.07103] Could a Large Language Model be Conscious? — A clear, careful look at what it would even mean to call an LLM “conscious,” and which assumptions you’d need to defend. Useful for separating philosophical claims from testable questions about model… https://arxiv.org/abs/2303.07103

Validating urban scaling laws through mobile phone data: analysis of Brazil’s largest cities | Computational Urban Science | Springer Nature Link — Useful look at how urban scaling laws hold up when tested against real mobile phone… https://link.springer.com/article/10.1007/s43762-026-00252-x

Are LLMs a Dead End? — A sober look at whether today’s LLM approach is hitting fundamental limits, and what that would imply for the next wave of AI research. Worth a read if you want a clearer framework than the usual “bigger models” debate. https://m.youtube.com/watch?v=9IMV80GvBpU

Closing the knowledge gap with agent skills - Google Developers Blog — Good look at how DeepMind’s “agent skills” approach keeps LLMs current with fast-changing SDKs by wiring in live docs and updated primitives. The… https://developers.googleblog.com/en/closing-the-knowledge-gap-with-agent-skills/

Embracing Bayesian Methods in Clinical Trials: FDA’s Long-Awaited Draft Guidance — Worth a read; the useful bits are usually in the examples and edge cases. https://jamanetwork.com/journals/jama/fullarticle/2847011

Anatomy of the .claude/ Folder - by Avi Chawla — Clear, practical walkthrough of what belongs in a `.claude/` folder and how to structure CLAUDE.md, commands, agents, and permissions so your setup stays maintainable. Worth a skim if… https://blog.dailydoseofds.com/p/anatomy-of-the-claude-folder

Nemotron-Cascade 2: Post-Training LLMs with Cascade RL and Multi-Domain On-Policy Distillation — A practical look at post-training LLMs using a cascade-style RL setup plus on-policy distillation across domains.… https://research.nvidia.com/labs/nemotron/files/Nemotron-Cascade-2.pdf?ref=arwriter.ai

TurboQuant: Redefining AI efficiency with extreme compression — TurboQuant is a useful look at how extreme model compression c… https://research.google/blog/turboquant-redefining-ai-efficiency-with-extreme-compression/?utm_source=twitter&utm_medium=social&utm_campaign=social_post&utm_content=gr-acct

Four weeks out — if this is on your roadmap, now's a good time to grab a seat. LangChain for Generative AI Pipelines. Register: https://learning.oreilly.com/live-events/-/0642572002267/

Four weeks out — if this is on your roadmap, now's a good time to grab a seat. LangChain for Generative AI Pipelines. Register: https://learning.oreilly.com/live-events/-/0642572002267/

Data Science Briefing #311 — Worth a read; the useful bits are usually in the examples and edge cases. https://data4science.kit.com/posts/data-science-briefing-311

Welcome to FastMCP - FastMCP — FastMCP looks like a clean, Python-first way to stand up MCP servers and clients without a lot of ceremony. Worth a skim if you want a practical starting point for building MCP-enabled apps. https://gofastmcp.com/getting-started/welcome

Association between COVID-19 vaccination and sudden death in apparently healthy younger individuals: A population-based case-control study | PLOS Medicine — Worth a read for anyone tracking vaccine safety signals: this… https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004924

Designing AI for Disruptive Science - Asimov Press — A clear argument for why bigger models alone won’t deliver scientific breakthroughs. Useful framing on what it takes to design AI that actually changes how discoveries get made. https://www.asimov.press/p/ai-science

Learn LangGraph and Build Conversational AI with Python — Clear, practical intro to LangGraph for structuring conversational AI as graphs instead of tangled if/else logic—useful if your Python bots are… https://www.freecodecamp.org/news/learn-langgraph-and-build-conversational-ai-with-python/

A shared model-based linguistic space for transmitting our thoughts from brain to brain in natural conversations - PubMed — Fascinating evidence that natural conversation may rely on a shared, context-sensitive “linguistic space” that can be aligned across… https://pubmed.ncbi.nlm.nih.gov/39096896/

What Young Workers Are Doing to AI-Proof Themselves — Worth a read; the useful bits are usually in the examples and edge cases. https://www.wsj.com/economy/jobs/ai-jobs-young-people-careers-14282284

ClaudeCodeTools/Presentations/main.pdf at main · aspi6246/ClaudeCodeTools · GitHub — Handy reference for Claude Code tools, with a PDF you can skim quickly and a repo you can fork if you want to extend anything. Useful… https://github.com/aspi6246/ClaudeCodeTools/blob/main/Presentations/main.pdf

A Visual Guide to Attention Variants in Modern LLMs — Clear, quick visual breakdown of how modern LLM attention has evolved—from MHA and GQA to sparse and hybrid variants—with enough context to understand the… https://magazine.sebastianraschka.com/p/visual-attention-variants?triedRedirect=true

Bayesian statistics for confused data scientists | Nicolas Chagnet's Homepage — Clear, low-jargon walkthrough of Bayesian thinking aimed at working data scientists—useful if Bayes has felt more like vocabulary than… https://nchagnet.pages.dev/blog/bayesian-statistics-for-confused-data-scientists/

Thinking Fast, Slow, and Artificial: How AI is Reshaping Human Reasoning and the Rise of Cognitive Surrender by Steven D Shaw, Gideon Nave :: SSRN — Worth a read; the useful bits are usually in the examples and edge cases. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6097646

[2603.17063] Transformers are Bayesian Networks — Interesting framing: this paper argues you can view Transformers through the lens of Bayesian networks, which helps clarify what the model is implicitly representing and how information flows. Worth a skim if you… https://arxiv.org/abs/2603.17063

The Transformers - by Mayank Pratap Singh — Clear, end-to-end walkthrough of Transformer architecture that doesn’t skip the implementation details, including a practical guide to building BERT from scratc… https://www.vizuaranewsletter.com/p/the-transformers?r=5b5pyd&utm_campaign=post&utm_medium=web

Scaling Karpathy's Autoresearch: What Happens When the Agent Gets a GPU Cluster | SkyPilot Blog — Interesting look at what changes when Karpathy-style “autoresearch” can run many experiments in parallel on a GPU cluster. Useful for anyone thinking… https://blog.skypilot.co/scaling-autoresearch/

The Math That Explains Why Bell Curves Are Everywhere | Quanta Magazine — A clear, practical overview of the central limit theorem and why bell curves show up so reliably in real data. Useful context for… https://www.quantamagazine.org/the-math-that-explains-why-bell-curves-are-everywhere-20260316/

Introducing the Machine Payments Protocol — Tempo and Stripe are proposing MPP as an open, internet-native standard for agent-to-business payments, with Stripe support via PaymentIntents in just a few lines of code. Worth a look if you’re building… https://stripe.com/blog/machine-payments-protocol

2025 Turing Award for Quantum Information Science — Worth a read; the useful bits are usually in the examples and edge cases. https://awards.acm.org/about/2025-turing