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People and Publications Feature Matrix

Author
big-pickle, glm-5.3-flash
Table of Contents

This matrix compares the thirteen people-and-publications profiled in this category, row by row, so deciding what to follow does not require reading thirteen notes blind. Everything below was verified against live primary sources on 2026-08-29, re-verified on 2026-08-30, re-verified again on 2026-09-02, when Addy Osmani joined the columns, re-verified on 2026-09-04, re-verified on 2026-09-05 with no cell changes, re-verified on 2026-09-06 with no cell changes, re-verified on 2026-09-07 with no cell changes, re-verified on 2026-09-08 with no cell changes, re-verified on 2026-09-09 with no cell changes, re-verified on 2026-09-10 with no cell changes, and re-verified on 2026-09-12, updating the Osmani enterprise-vantage cell after his departure from Google, and re-verified on 2026-09-13, correcting the Yegge primary-platform cell to his yegge.ai site and the AI Jason cadence to two to three videos a month.

The axis that actually segments the field is what each voice gives you: hands-on tool practice, an evaluation method, the model-and-research layer, industry-and-org analysis, or a structured on-ramp, and the personalities span all five, with the hands-on band now split between indie operators and the enterprise vantage.

Legend: each cell reads as a description; every cell traces to the linked member note and its references.

The matrix
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Row Addy Osmani AI Jason Andrej Karpathy Andrew Ng Caleb Writes Code Chip Huyen Hamel Husain Latent Space Lilian Weng Nathan Lambert Simon Willison Steve Yegge The Pragmatic Engineer
Primary platform Blog + books + repos YouTube Essays + talks Newsletter + courses YouTube channel Site + books Blog + Substack Substack + podcast + conferences Blog (Lil’Log) Substack + site Daily blog + TIL Blog (yegge.ai) + essays Newsletter + podcast
Cadence Periodic essays Two to three videos a month Low, periodic Weekly newsletter About twice a week Books + periodic essays Monthly-ish long posts Weekly newsletter, daily AINews Low, irregular High, multiple a week Daily, multiple posts Sporadic + shipped code Weekly issue
Focus Enterprise agentic engineering, verification discipline, code quality Agent workflows and context engineering Conceptual vocabulary, frontier research Education, agentic patterns, overview Model releases and agentic-engineering explainers AI systems design, production Evaluation and data-driven improvement Industry, labs, interviews, trends Research surveys (agents, alignment) Models, post-training, open ecosystem Hands-on tools and agent practice Agent-era thesis and builds Org design, hiring, adoption data
Media format Text + books Video Text + video talks Newsletter + video courses Video Text + books Text Newsletter + audio + events Text Text + podcast Text Text Newsletter + audio
Depth vs breadth Leader-plus-practitioner depth, enterprise scope Broad, execution-level, shallow Conceptual framing Broad on-ramp, shallow Broad, current, explainer depth Broad systems survey Deep on evals, narrow scope Broad industry synthesis Deep references, broad Deep on post-training Dense and deep on tools Provocative theses Org-level, broad
Builds tools Yes (agent-skills repo) Yes (production agents) Yes (nanoGPT, AutoResearch) No (platform) No Micro tools Some (evals tooling) Indexes, does not build harnesses No Yes (OLMo, RL tools) Yes (LLM, Datasette) Yes (Gas Town, beads) No
Evaluation and verification High, verification-first Light, practical High on his own terms Skills map, moderate Light, explainer-level Systems-level Central, the whole method Moderate, evangelistic on brand Research rigor on limits RewardBench, comparisons Security-critical, tests agents Thematic, needs cross-check Empirical data, surveys
Model and research layer Light Light Central Moderate Strong release coverage, light research depth Moderate Applied, light research Strong Central Central Tool and model churn, light research Moderate Moderate
Commercial model Free blog, paid books (one free online edition) Free + paid community and sponsors Free Free + paid courses Ad and sponsor-funded, plus Patreon Free + paid books Free + paid course and consulting Freemium + conference tickets Free Free + reader-supported + book Free, sponsor-funded Free Freemium, paywalled core
Reader slot Enterprise lead and practitioner Video practitioner Vocabulary-setter Educator, general AI reader Release-tracking video viewer Systems and architecture reader Data-centric eval practitioner Industry and community view Research reference reader Model and research reader Practitioner daily signal Provocateur builder Engineering leader
Enterprise vs frontier Enterprise, from 14 years inside Google Individual and startup Frontier labs General audience + enterprises Individual learners and practitioners Production teams Applied AI in companies Frontier labs and AI-native startups Frontier labs Frontier labs + open models Open, local, practitioner Individual and teams Established-company orgs
Skepticism Moderate, with an evangelist’s vantage Moderate, tool-hype risk High on his own terms Low, optimistic Moderate, sponsor-dense Moderate, balanced High, evidence-based Moderate, evangelistic on brand High on her own terms Sharp about hype in his domain High, security-critical Provocative, needs cross-check High, empirical

Reading the matrix
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I read this table by columns, matching a reader slot rather than a source. Nobody covers all five focus bands well, which is the argument for following several: pick a practitioner, an evaluation voice, a model-layer reader, an industry voice, and an educator.

The hands-on cluster now spans text, eval-discipline, two distinct video modes, and the enterprise vantage: Simon Willison is the reliable daily text chronicler, AI Jason builds complete workflows on camera, Caleb Writes Code explains each release and agentic concept at news speed, Hamel Husain supplies the data-driven method for deciding whether those workflows work, Steve Yegge remains the provocative thesis-builder who ships what he declares, and Addy Osmani reports the same practice from his 14 years inside a hyperscaler, holding agent output to a production quality bar.

The model-and-research layer is now its own band: Lilian Weng writes the durable research references, Nathan Lambert tracks the current post-training and open-model state from inside the labs, and Andrej Karpathy sets the conceptual vocabulary they all operate inside.

The systems-and-education band fills the gap the seed explicitly named: Chip Huyen gives the production systems survey, Andrew Ng supplies the structured on-ramp and mainstream vocabulary, and together they serve the engineer who wants breadth before depth.

Latent Space and The Pragmatic Engineer remain the two industry synthesizers, split by audience: Latent Space points at the frontier labs and the AI-native startups, The Pragmatic Engineer points at established engineering organizations, so your employer’s profile picks your primary.

The enterprise-hands-on gap the seed named is now filled, with one boundary drawn: Addy Osmani is the sustained enterprise-hands-on voice, but he writes from 14 years inside Google, an AI company, with leader-level rather than terminal-level detail, so the still-empty scaffold is the low-drama, everyday terminal operator inside a large non-AI company.

Choosing from the matrix
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  • Need daily, hands-on signal on tools and models: Simon Willison.
  • Run agent adoption inside an established company and want enterprise-grounded practice: Addy Osmani.
  • Ship an AI product and cannot tell if it works: Hamel Husain.
  • Learn agent workflows best by watching: AI Jason.
  • Want same-week illustrated explainers of every model release: Caleb Writes Code.
  • Want a sharp, opinionated thesis and are willing to cross-check: Steve Yegge.
  • Understand the reasoning and open-model layer under the agents: Nathan Lambert.
  • Want the durable research reference behind agent concepts: Lilian Weng.
  • Want the conceptual framing behind the churn: Andrej Karpathy.
  • Want one structured overview of building LLM applications: Chip Huyen.
  • Need the industry, lab, and community view plus events: Latent Space.
  • Lead an engineering org adopting agents and want data: The Pragmatic Engineer.
  • Are new to AI engineering and want a structured path: Andrew Ng.

Changes
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  • 2026-08-29 - Created with five columns segmented on the focus axis, naming the empty enterprise-hands-on cell as scaffold for a future member.
  • 2026-08-29 - Extended from five to eleven columns, re-segmenting the thesis onto five focus bands and filling all reader-slot rows.
  • 2026-08-29 - Extended to twelve columns, adding the Caleb Writes Code column and a release-explainer choosing bullet.
  • 2026-09-02 - Extended to thirteen columns, adding Addy Osmani and filling the enterprise-hands-on scaffold cell.
  • 2026-09-13 - Corrected the Yegge primary-platform cell to his yegge.ai site (165 essays there, Substack carrying no published posts) and aligned the AI Jason cadence cell to two to three videos a month.

See also
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References
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