X AI Users Database

All 171 accounts from the source workbook.

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Showing 171 of 171 accounts

ID	Name	Username	Profile URL	Topics / Tags	What You Can Learn	Checked
1	Sam Altman	@sama	View profile	OpenAI; frontier models; strategy	OpenAI product direction, model launches, infrastructure bets, and the strategic framing behind frontier AI.	2026-08-09
2	Greg Brockman	@gdb	View profile	OpenAI; engineering; demos	OpenAI engineering culture, demos, infrastructure scale, and practical examples of new model capabilities.	2026-08-09
3	Dario Amodei	@DarioAmodei	View profile	Anthropic; scaling; safety	Anthropic's view on scaling, Claude, capability growth, alignment, and long-run AI impact.	2026-08-09
4	Daniela Amodei	@DanielaAmodei	View profile	Anthropic; enterprise; policy	How a frontier lab approaches product operations, enterprise deployment, responsible scaling, and policy.	2026-08-09
5	Mike Krieger	@mikeyk	View profile	Anthropic; product; consumer AI	How Claude evolves as a product, especially consumer UX, artifacts, projects, and practical AI experiences.	2026-08-09
6	Demis Hassabis	@demishassabis	View profile	Google DeepMind; Gemini; AI science	Frontier research, Gemini direction, AI for science, and how DeepMind thinks about AGI.	2026-08-09
7	Sundar Pichai	@sundarpichai	View profile	Google; Gemini; Search; Workspace	Macro product strategy for Gemini, Search, Workspace, infrastructure, and Google's AI platform shift.	2026-08-09
8	Mark Zuckerberg	@finkd	View profile	Meta; Llama; open weights; consumer AI	Meta's open-model strategy, AI assistants, wearables, and how AI is being pushed into consumer products.	2026-08-09
9	Aidan Gomez	@aidangomez	View profile	Cohere; transformers; enterprise AI	Enterprise LLM design, retrieval, multilingual systems, and the perspective of a Transformer-paper coauthor.	2026-08-09
10	Arthur Mensch	@arthurmensch	View profile	Mistral; open models; Europe	Open-weight model releases, European AI strategy, and the case for efficient frontier models.	2026-08-09
11	Clément Delangue	@ClementDelangue	View profile	Hugging Face; open source; models	Open-source AI ecosystem trends, new models on Hugging Face, community tooling, and open-model policy.	2026-08-09
12	Aravind Srinivas	@AravSrinivas	View profile	Perplexity; AI search; agents	AI-native search, answer engines, product velocity, agents, and competitive product strategy.	2026-08-09
13	Mustafa Suleyman	@mustafasuleyman	View profile	Microsoft AI; consumer AI; policy	How Microsoft approaches consumer AI, assistants, product distribution, and AI's societal implications.	2026-08-09
14	Mira Murati	@miramurati	View profile	Thinking Machines; frontier AI	Signals from a major new frontier lab, model/product philosophy, and high-level AI development direction.	2026-08-09
15	Ilya Sutskever	@ilyasut	View profile	SSI; deep learning; superintelligence	Rare but high-signal thinking about deep learning, superintelligence, and frontier-model research priorities.	2026-08-09
16	Logan Kilpatrick	@OfficialLoganK	View profile	Gemini API; AI Studio; developer tools	Gemini developer features, AI Studio workflows, multimodal APIs, and rapid prototyping with Google's models.	2026-08-09
17	Alex Albert	@alexalbert__	View profile	Anthropic; prompting; Claude	Claude prompting techniques, developer resources, model behavior, and practical Anthropic platform guidance.	2026-08-09
18	Boris Cherny	@bcherny	View profile	Claude Code; coding agents; workflows	How the creator of Claude Code uses coding agents: context, parallel work, agent loops, review, and setup patterns.	2026-08-09
19	Amanda Askell	@AmandaAskell	View profile	Anthropic; alignment; model behavior	Alignment, model behavior, character, instruction following, and the philosophy behind assistant behavior.	2026-08-09
20	Cat Wu	@_catwu	View profile	Anthropic; Claude Code; engineering	Claude Code engineering insights, coding-agent product details, and practical implementation choices.	2026-08-09
21	Thariq Shihipar	@trq212	View profile	Claude Code; context; skills	Advanced Claude Code usage, context engineering, skills, subagents, and how coding-agent features work.	2026-08-09
22	Thibault Sottiaux	@thsottiaux	View profile	OpenAI; Codex; ChatGPT engineering	Codex/ChatGPT engineering updates, coding-agent roadmap notes, and developer-facing product changes.	2026-08-09
23	Josh Woodward	@joshwoodward	View profile	Google Labs; product experiments	Google Labs experiments, AI-native product ideas, prototypes, and how new capabilities become consumer tools.	2026-08-09
24	Amjad Masad	@amasad	View profile	Replit; agents; vibe coding	How AI agents change software development, product-building speed, and the economics of creating software.	2026-08-09
25	Guillermo Rauch	@rauchg	View profile	Vercel; v0; AI SDK; web	AI-native web development, v0, AI SDK patterns, interfaces, and shipping production AI applications.	2026-08-09
26	Yann LeCun	@ylecun	View profile	world models; self-supervision; AGI	Contrarian research arguments, world models, self-supervised learning, and critiques of LLM-only paths to AGI.	2026-08-09
27	Geoffrey Hinton	@geoffreyhinton	View profile	deep learning; AI risk	Foundational deep-learning perspective plus arguments about capability growth, safety, and societal risk.	2026-08-09
28	Yoshua Bengio	@Yoshua_Bengio	View profile	deep learning; safety; governance	Deep-learning research, frontier risk, AI governance, and scientific approaches to safer systems.	2026-08-09
29	Andrew Ng	@AndrewYNg	View profile	AI education; agents; enterprise AI	Practical AI adoption, agentic workflows, project selection, education, and how businesses can use AI now.	2026-08-09
30	Fei-Fei Li	@drfeifei	View profile	computer vision; spatial intelligence; human-centered AI	Computer vision, spatial intelligence, human-centered AI, research direction, and AI policy.	2026-08-09
31	Andrej Karpathy	@karpathy	View profile	LLMs; neural nets; coding; education	First-principles understanding of LLMs, neural networks, AI coding, model intuition, and learning-by-building.	2026-08-09
32	Jeff Dean	@JeffDean	View profile	Google; ML systems; scaling	Large-scale ML systems, distributed training, research infrastructure, and foundational Google AI work.	2026-08-09
33	François Chollet	@fchollet	View profile	ARC-AGI; reasoning; Keras	Reasoning benchmarks, what intelligence means, limitations of current LLMs, and rigorous anti-hype analysis.	2026-08-09
34	Tri Dao	@tri_dao	View profile	FlashAttention; kernels; inference	Efficient attention, GPU-aware algorithms, inference/training speed, and systems work behind faster LLMs.	2026-08-09
35	Christopher Manning	@chrmanning	View profile	NLP; language models; Stanford	NLP fundamentals, language-model research, academic perspective, and conceptual foundations behind modern LLMs.	2026-08-09
36	Sasha Rush	@srush_nlp	View profile	Transformers; NLP; education	Reproducible ML research, Transformers, NLP, implementation-focused learning, and technical education.	2026-08-09
37	Jim Fan	@DrJimFan	View profile	robotics; embodied AI; agents	Embodied AI, robotics, multimodal agents, simulation, and how foundation models move into the physical world.	2026-08-09
38	Nathan Lambert	@natolambert	View profile	post-training; RLHF; open models	RLHF, preference learning, post-training, reasoning models, benchmarks, and open-model ecosystem analysis.	2026-08-09
39	Noam Brown	@polynoamial	View profile	reasoning; self-play; test-time compute	Reasoning models, self-play, test-time compute, and the ideas behind stronger deliberative AI systems.	2026-08-09
40	Jason Wei	@_jasonwei	View profile	chain-of-thought; reasoning; scaling	Chain-of-thought, emergent abilities, reasoning behavior, scaling, and frontier-model research.	2026-08-09
41	Chris Olah	@ch402	View profile	interpretability; neural networks	Mechanistic interpretability and clearer mental models for what neural networks represent internally.	2026-08-09
42	Lilian Weng	@lilianweng	View profile	agents; RLHF; reasoning; safety	Deep technical syntheses on agents, reasoning, reinforcement learning, safety, and modern LLM methods.	2026-08-09
43	David Ha	@hardmaru	View profile	generative models; agents; creativity	Unconventional research ideas, generative models, agent behavior, creativity, and experimental AI concepts.	2026-08-09
44	Sebastian Raschka	@rasbt	View profile	LLMs; PyTorch; training; fine-tuning	How LLMs work from code: architectures, fine-tuning, training, evaluation, and implementation details.	2026-08-09
45	Soumith Chintala	@soumithchintala	View profile	PyTorch; ML systems; open source	PyTorch, ML framework design, open-source engineering, and practical deep-learning infrastructure.	2026-08-09
46	Percy Liang	@percyliang	View profile	foundation models; evaluation; Stanford CRFM	Foundation-model evaluation, transparency, benchmarks, policy, and rigorous academic analysis of LLM systems.	2026-08-09
47	Chelsea Finn	@chelseabfinn	View profile	robot learning; meta-learning; embodied AI	Robot learning, reinforcement learning, meta-learning, and systems that learn adaptable behaviors.	2026-08-09
48	Sergey Levine	@svlevine	View profile	robotics; reinforcement learning	Deep reinforcement learning, robot learning, control, and how learning systems interact with the physical world.	2026-08-09
49	Anima Anandkumar	@AnimaAnandkumar	View profile	AI science; neural operators; NVIDIA	AI for science, foundation models for physical systems, scalable ML, and high-performance research.	2026-08-09
50	Yejin Choi	@YejinChoinka	View profile	NLP; common sense; human-centered AI	Language understanding, common-sense reasoning, AI limitations, and human-centered research perspectives.	2026-08-09
51	Pieter Abbeel	@pabbeel	View profile	robotics; RL; AI startups	Robotics, reinforcement learning, AI entrepreneurship, and research-to-product translation.	2026-08-09
52	Oriol Vinyals	@OriolVinyalsML	View profile	DeepMind; agents; sequence models	DeepMind research, sequence modeling, agents, games, and frontier-model science.	2026-08-09
53	Tim Dettmers	@Tim_Dettmers	View profile	quantization; efficient training; GPUs	Quantization, memory-efficient training, hardware constraints, and practical ways to run large models cheaper.	2026-08-09
54	Thomas Wolf	@Thom_Wolf	View profile	Hugging Face; open models; research	Open-source model culture, Hugging Face ecosystem, research trends, and the future of collaborative AI.	2026-08-09
55	Omar Sanseviero	@osanseviero	View profile	Hugging Face; open LLMs	Open-source LLM releases, model tooling, community projects, and hands-on Hugging Face workflows.	2026-08-09
56	Jeremy Howard	@jeremyphoward	View profile	fast.ai; practical deep learning	Practical deep learning, small-team research, AI coding, education, and learning by shipping real systems.	2026-08-09
57	Simon Willison	@simonw	View profile	LLMs; security; prompting; tools	Real LLM experiments, coding-agent workflows, prompt injection, APIs, model quirks, and honest tool testing.	2026-08-09
58	Swyx (Shawn Wang)	@swyx	View profile	AI engineering; agents; ecosystem	The AI-engineering stack, agents, tooling, model releases, industry structure, and what builders should learn next.	2026-08-09
59	Harrison Chase	@hwchase17	View profile	LangChain; LangGraph; agents	Agent architecture, orchestration, managed agents, LangGraph patterns, and production AI workflows.	2026-08-09
60	Jerry Liu	@jerryjliu0	View profile	LlamaIndex; RAG; document AI	RAG, document understanding, agentic data systems, retrieval, context layers, and production knowledge workflows.	2026-08-09
61	Jason Liu	@jxnlco	View profile	structured outputs; RAG; evals	Structured outputs, Instructor, RAG iteration, context engineering, evaluations, and enterprise LLM patterns.	2026-08-09
62	Hamel Husain	@HamelHusain	View profile	evals; error analysis; AI products	How to evaluate AI products, perform error analysis, build data flywheels, and improve unreliable LLM systems.	2026-08-09
63	Chip Huyen	@chipro	View profile	AI systems; agents; production	Production AI system design, agents, inference, data, evaluation, and the tradeoffs behind reliable AI products.	2026-08-09
64	Eugene Yan	@eugeneyan	View profile	ML systems; recommendation; evals	Production ML/LLM patterns, evaluation, recommendation systems, architecture, and practical system-design lessons.	2026-08-09
65	Philipp Schmid	@_philschmid	View profile	Gemini; fine-tuning; Hugging Face	Gemini development, fine-tuning, deployment, open models, and practical model-engineering tutorials.	2026-08-09
66	Shreya Shankar	@sh_reya	View profile	evals; data systems; AI products	User-centered AI evaluation, error discovery, data pipelines, and systematic ways to improve AI applications.	2026-08-09
67	Aran Komatsuzaki	@arankomatsuzaki	View profile	papers; open source; model research	Fast research discovery, new papers, open-model discussions, multilingual model issues, and research commentary.	2026-08-09
68	Louis-François Bouchard	@Whats_AI	View profile	AI engineering; harnesses; agents	AI-engineering roadmaps, agent harnesses, system design, career learning, and production-focused building.	2026-08-09
69	Addy Osmani	@addyosmani	View profile	AI coding; web; Chrome; performance	AI-assisted coding workflows, loop engineering, web performance, and safer ways to combine agents with software engineering.	2026-08-09
70	Thorsten Ball	@thorstenball	View profile	coding agents; Amp; agent internals	How coding agents work, tool loops, context, codebase interaction, and practical lessons from building agentic developer tools.	2026-08-09
71	Armin Ronacher	@mitsuhiko	View profile	agentic coding; software craft	Agentic coding from a veteran software engineer: codebase design, tools, tradeoffs, and how AI changes programming craft.	2026-08-09
72	Mario Zechner	@badlogicgames	View profile	minimal agents; coding harnesses	Minimal, steerable coding-agent design, why simpler harnesses can outperform complex stacks, and practical agent control.	2026-08-09
73	Theo Browne	@theo	View profile	TypeScript; AI dev tools; coding	Opinionated testing of AI coding tools, TypeScript/web stack changes, and developer workflows that actually ship.	2026-08-09
74	Peter Steinberger	@steipete	View profile	agents; OpenClaw; coding workflows	Boundary-pushing agent workflows, AI-native computer use, coding harnesses, and real tools built around agentic engineering.	2026-08-09
75	Matt Pocock	@mattpocockuk	View profile	agents; TypeScript; context	Context engineering, coding-agent patterns, TypeScript, agent spawning, skills, and practical developer education.	2026-08-09
76	Dex Horthy	@dexhorthy	View profile	12-factor agents; context; production	Production-agent principles, context management, human-in-the-loop design, and reliable software-factory patterns.	2026-08-09
77	Kieran Klaassen	@kieranklaassen	View profile	compound engineering; parallel agents	Parallel coding agents, compound engineering, voice-driven development, context patterns, and high-output AI workflows.	2026-08-09
78	Jesse Kriss	@obra	View profile	Claude Code; agent skills; software	Claude Code workflows, skills, agentic software-development practices, and repeatable approaches to AI-assisted coding.	2026-08-09
79	Ian Nuttall	@iannuttall	View profile	Claude Code; Cursor; indie building	Actionable Claude Code/Cursor best practices, quality and security checklists, and shipping small software businesses with AI.	2026-08-09
80	Ryo Lu	@ryolu_	View profile	agents; AI products; software	Practical AI product-building, agent workflows, coding-tool experimentation, and lessons from shipping AI software.	2026-08-09
81	Nan Yu	@thenanyu	View profile	AI engineering; agents; product	Hands-on AI engineering, agent/product experimentation, and practical ideas from a current builder feed.	2026-08-09
82	Madhu Guru	@realmadhuguru	View profile	AI building; agents; product	Builder-oriented AI workflows, product experiments, and practical examples of applying new model capabilities.	2026-08-09
83	Peter Yang	@petergyang	View profile	AI products; product management; startups	How AI changes product management, startup building, customer workflows, and what useful AI products look like.	2026-08-09
84	Nikunj Kothari	@nikunj	View profile	AI startups; products; investing	AI startup/product observations, tools, founder lessons, and emerging opportunities around new capabilities.	2026-08-09
85	Aditya Agarwal	@adityaag	View profile	engineering leadership; AI startups	Engineering leadership, product building, startup execution, and how strong teams adopt new AI workflows.	2026-08-09
86	Gergely Orosz	@GergelyOrosz	View profile	software engineering; AI coding; industry	How AI coding tools affect professional software teams, engineering careers, productivity, and developer-tool adoption.	2026-08-09
87	Santiago Valdarrama	@svpino	View profile	ML; AI coding; learning	Practical ML/AI learning, building advice, career development, and concise explanations for working engineers.	2026-08-09
88	John Carmack	@ID_AA_Carmack	View profile	AGI; systems; engineering	First-principles AGI and systems engineering from a legendary programmer; useful for separating hard engineering from hype.	2026-08-09
89	George Hotz	@realGeorgeHotz	View profile	tinygrad; hardware; efficient AI	First-principles ML systems, tinygrad, GPUs, autonomous driving, and building efficient AI with small teams.	2026-08-09
90	Pieter Levels	@levelsio	View profile	solo building; AI products; indie hacking	How a solo builder ships AI products quickly, validates demand, monetizes, and uses coding agents on real businesses.	2026-08-09
91	Dan Shipper	@danshipper	View profile	AI at work; agents; writing; coding	Everyday agent workflows for writing, coding, research, company operations, and personal productivity.	2026-08-09
92	Riley Brown	@rileybrown	View profile	n8n; agents; automation; vibe coding	n8n agent systems, automation, multi-agent workflows, vibe coding, and practical tool stacks.	2026-08-09
93	Sabrina Ramonov	@Sabrina_Ramonov	View profile	Claude Code; prompts; automation; tools	AI prompts, Claude/Codex workflows, agent setups, practical tool rankings, and automation playbooks.	2026-08-09
94	Matt Shumer	@mattshumer_	View profile	prompting; agents; productivity	Advanced prompting, coding-agent productivity, autonomous-agent experiments, and high-leverage AI workflows.	2026-08-09
95	Alex Finn	@AlexFinn	View profile	AI agents; autonomous workflows; creator tools	Personal swarms of AI agents, autonomous workflows, Mac-based agents, and experiments in AI-driven economic work.	2026-08-09
96	Ben Tossell	@bentossell	View profile	AI tools; coding agents; nontechnical building	AI tool discovery, coding agents for nontechnical builders, practical workflows, and product ideas.	2026-08-09
97	Greg Isenberg	@gregisenberg	View profile	AI startup ideas; communities; SaaS	AI startup ideas, niche software opportunities, product-market thinking, and business models you can build around new capabilities.	2026-08-09
98	Paul Couvert	@itsPaulAi	View profile	AI tricks; no-code; automation; productivity	Step-by-step AI tricks, no-code workflows, local AI, spreadsheet use cases, creative tools, and practical productivity hacks.	2026-08-09
99	Min Choi	@minchoi	View profile	prompts; image/video; tools; AI trends	New AI use cases, prompts, image/video experiments, creative workflows, and fast examples of what new models can do.	2026-08-09
100	Matt Wolfe	@mreflow	View profile	AI tools; news; tutorials	Daily AI tools, product releases, tutorials, and builder-friendly summaries of what changed recently.	2026-08-09
101	Allie K. Miller	@alliekmiller	View profile	enterprise AI; careers; product	Enterprise AI strategy, AI careers, practical resources, product adoption, and accessible explanations.	2026-08-09
102	Pietro Schirano	@skirano	View profile	AI design; UI; coding; prototyping	AI-assisted design, UI generation, creative coding, rapid prototypes, and visually polished AI product experiments.	2026-08-09
103	Javi Lopez	@javilopen	View profile	generative AI; image/video; experiments	Creative generative-AI experiments, visual prompting, prototypes, and unusual applications of new media models.	2026-08-09
104	Garry Tan	@garrytan	View profile	YC; startups; AI coding	What fast-moving startups are building with AI, coding-agent adoption, founder lessons, and early product patterns.	2026-08-09
105	Bindu Reddy	@bindureddy	View profile	models; agents; startups; commentary	Fast opinions and discussion on models, agents, open-source AI, AI startups, and emerging product patterns.	2026-08-09
106	Ethan Mollick	@emollick	View profile	AI at work; education; productivity	Evidence-based ways to use AI at work, teaching, creative tasks, and knowledge work—plus experiments showing what models can and cannot do.	2026-08-09
107	Aaron Levie	@levie	View profile	enterprise AI; agents; SaaS	How agents reshape enterprise software, SaaS, knowledge work, and company workflows; sharp product/market observations.	2026-08-09
108	Matt Turck	@mattturck	View profile	AI market; venture; data; startups	AI startup landscape, venture trends, enterprise data/AI, and market maps that help identify where companies are forming.	2026-08-09
109	Zara Zhang	@zarazhangrui	View profile	builders; China AI; ecosystem	Curated builder signal, AI ecosystem developments, China/US technology context, and practical sources worth following.	2026-08-09
110	Linus Ekenstam	@LinusEkenstam	View profile	AI tools; design; prompting	Creative AI tools, design workflows, prompting ideas, visual generation, and accessible experiments with new products.	2026-08-09
111	Bilawal Sidhu	@bilawalsidhu	View profile	spatial AI; video; 3D; generative media	Generative video, 3D/spatial AI, visual experiments, and technically informed breakdowns of new creative models.	2026-08-09
112	Nick St. Pierre	@nickfloats	View profile	image generation; prompting; visual AI	Image-generation techniques, visual prompting, model comparisons, and creative workflows for generative media.	2026-08-09
113	Kieran (NoCodeLife)	@nocodelife	View profile	no-code; Claude Code; app building	Building apps with AI/no-code, Claude Code workflows for nontraditional developers, and practical shipping tutorials.	2026-08-09
114	Prajwal Tomar	@PrajwalTomar_	View profile	Claude Code; coding agents; tutorials	Claude Code setup, skills, context, workflows, and builder-oriented tutorials for getting more reliable results.	2026-08-09
115	RohOnChain	@RohOnChain	View profile	agents; tutorials; AI workflows	Fast breakdowns of agent-building tutorials, Claude workflows, and useful learning resources circulating in the AI builder community.	2026-08-09
116	Avid	@Av1dlive	View profile	agent stacks; architecture; workflows	Agent-stack architecture, builder guides, memory/workflow design, and practical patterns for constructing AI systems.	2026-08-09
117	Aakash Gupta	@aakashgupta	View profile	product management; AI products; growth	AI product strategy, product management, growth, and how AI-native companies design and distribute products.	2026-08-09
118	Rowan Cheung	@rowancheung	View profile	AI news; tools; launches	Fast AI product/model news, tool launches, broad industry changes, and easily skimmable summaries.	2026-08-09
119	Deedy Das	@deedydas	View profile	benchmarks; model releases; startups	Concise summaries of model releases, benchmarks, AI companies, coding tools, and whether a launch actually matters.	2026-08-09
120	AK (Akhaliq)	@_akhaliq	View profile	papers; open-source models; research	Very fast discovery of new papers, open-source models, demos, and research projects before they hit mainstream coverage.	2026-08-09
121	Alex Volkov	@altryne	View profile	ThursdAI; open models; tools	Weekly model releases, open-source AI, inference/tooling updates, and live builder commentary across the ecosystem.	2026-08-09
122	Dwarkesh Patel	@dwarkesh_sp	View profile	interviews; research; frontier labs	Deep interviews with frontier researchers and lab leaders; learn how top people reason about scaling, science, and the future.	2026-08-09
123	Jack Clark	@jackclarkSF	View profile	Anthropic; policy; capabilities; Import AI	AI capabilities, safety, policy, compute, and long-term industry trends from a lab founder and longtime analyst.	2026-08-09
124	Kylie Robison	@kyliebytes	View profile	AI labs; industry reporting	Breaking reporting on AI labs, hiring, organizational changes, product moves, and industry dynamics.	2026-08-09
125	Alex Kantrowitz	@Kantrowitz	View profile	big tech; AI business; interviews	AI business reporting, interviews, Big Tech strategy, and practical context behind major AI-company moves.	2026-08-09
126	Lex Fridman	@lexfridman	View profile	podcasts; researchers; founders	Long-form interviews with researchers, founders, and technical leaders that reveal how major AI figures actually think.	2026-08-09
127	Gary Marcus	@GaryMarcus	View profile	AI criticism; reasoning; reliability	Skeptical analysis of model reliability, reasoning, hype, governance, and where current systems still fail.	2026-08-09
128	Kai-Fu Lee	@kaifulee	View profile	China AI; investing; startups	China's AI ecosystem, startup investing, commercialization, and a non-US perspective on AI adoption.	2026-08-09
129	Reid Hoffman	@reidhoffman	View profile	AI investing; startups; society	AI entrepreneurship, investing, labor/productivity implications, and optimistic frameworks for using AI at scale.	2026-08-09
130	Marc Andreessen	@pmarca	View profile	AI investing; tech strategy	Techno-optimist arguments, AI startup/investment themes, software markets, and strong opinions on technology direction.	2026-08-09
131	Vinod Khosla	@vkhosla	View profile	AI investing; macro; infrastructure	Long-cycle AI investing, labor and productivity implications, energy/compute infrastructure, and frontier startup theses.	2026-08-09
132	Steve Nouri	@stevenouri	View profile	AI news; agents; industry	High-volume AI roundups, agent use cases, tools, and industry shifts—a useful broad curation layer.	2026-08-09
133	Cassie Kozyrkov	@quaesita	View profile	decision intelligence; AI strategy	Decision-making with AI, statistical thinking, how to frame business problems, and communicating AI to nontechnical teams.	2026-08-09
134	Bernard Marr	@bernardmarr	View profile	AI strategy; enterprise; trends	Broad enterprise AI trends, business transformation, board-level implications, and accessible industry examples.	2026-08-09
135	Zain Kahn	@heykahn	View profile	AI tools; coding tips; productivity	Practical AI coding tips, tool roundups, prompt-style resources, productivity ideas, and beginner-friendly use cases.	2026-08-09
136	Timnit Gebru	@timnitGebru	View profile	AI ethics; accountability; social impact	Algorithmic accountability, harms, data/representation issues, power structures, and responsible AI criticism.	2026-08-09
137	Margaret Mitchell	@mmitchell_ai	View profile	model cards; ethics; governance	Responsible model release, model cards, evaluation, AI governance, and how organizations communicate model limitations.	2026-08-09
138	Helen Toner	@hlntnr	View profile	AI policy; national security; governance	AI policy, national security, governance, frontier-lab oversight, and institutional approaches to managing risk.	2026-08-09
139	Eliezer Yudkowsky	@ESYudkowsky	View profile	alignment; existential risk	The strongest version of existential-risk arguments, alignment concerns, and why some researchers want much stricter controls.	2026-08-09
140	Zvi Mowshowitz	@TheZvi	View profile	AI policy; model releases; risk	Detailed commentary on AI releases, policy, safety debates, forecasting, and second-order consequences.	2026-08-09
141	Melanie Mitchell	@MelMitchell1	View profile	complexity; intelligence; AI criticism	Careful analysis of intelligence, abstraction, reasoning, complexity, and the gap between benchmark performance and robust intelligence.	2026-08-09
142	Max Tegmark	@tegmark	View profile	AI safety; governance; future	AI safety advocacy, governance, long-term societal risk, and debates about how quickly powerful systems should be deployed.	2026-08-09
143	OpenAI	@OpenAI	View profile	GPT; ChatGPT; Codex; API	Official OpenAI model launches, ChatGPT/Codex features, API updates, research, safety reports, and product announcements.	2026-08-09
144	Anthropic	@AnthropicAI	View profile	Claude; Claude Code; research	Official Claude/Claude Code releases, Anthropic research, safety work, product features, and engineering updates.	2026-08-09
145	Google DeepMind	@GoogleDeepMind	View profile	Gemini; research; AI science	Official Gemini/DeepMind model releases, research breakthroughs, AI science, robotics, and benchmark updates.	2026-08-09
146	Meta AI	@MetaAI	View profile	Llama; open models; research	Official Meta AI research, Llama/open-model work, multimodal systems, and releases from Meta's AI organization.	2026-08-09
147	Mistral AI	@MistralAI	View profile	Mistral models; open weights; API	Official Mistral model releases, open-weight updates, APIs, coding models, and European AI news.	2026-08-09
148	Hugging Face	@huggingface	View profile	models; datasets; open source	New open-source models, datasets, Spaces, libraries, community releases, and tools across the AI ecosystem.	2026-08-09
149	Perplexity	@perplexity_ai	View profile	AI search; research agents; product	Perplexity product releases, search/agent features, model integrations, and AI-native information workflows.	2026-08-09
150	Cohere	@cohere	View profile	enterprise LLMs; RAG; multilingual	Enterprise LLM releases, retrieval, multilingual models, research, and deployment-focused product updates.	2026-08-09
151	LangChain	@LangChainAI	View profile	LangChain; LangGraph; agents	LangChain/LangGraph updates, agent orchestration, LangSmith evaluation/tracing, and production agent examples.	2026-08-09
152	LlamaIndex	@llama_index	View profile	RAG; document AI; agents	RAG, document parsing, context engineering, agentic data systems, framework releases, and examples.	2026-08-09
153	Replit	@Replit	View profile	AI coding; agents; app building	Agentic software-building features, Replit platform updates, vibe-coding examples, and product-building workflows.	2026-08-09
154	Cursor	@cursor_ai	View profile	AI IDE; coding agents	Cursor features, agentic coding workflows, IDE updates, and examples of AI-assisted software development.	2026-08-09
155	v0	@v0	View profile	UI generation; web; Vercel	AI-generated UI, web-app prototyping, front-end workflows, and new v0 capabilities.	2026-08-09
156	n8n	@n8n_io	View profile	automation; agents; integrations	Workflow automation, n8n agents, integrations, templates, and practical ways to connect AI to business tools.	2026-08-09
157	Weights & Biases	@wandb	View profile	evals; observability; ML tooling	LLM/agent evaluation, tracing, experiment tracking, observability, and production ML engineering.	2026-08-09
158	AI Engineer	@aiDotEngineer	View profile	AI engineering; talks; agents	Conference talks and practitioner insights on agents, context, evals, coding systems, and production AI engineering.	2026-08-09
159	The Rundown AI	@TheRundownAI	View profile	AI news; product launches; tools	Fast broad AI news, funding, model releases, product launches, and tool discovery.	2026-08-09
160	DAIR.AI	@dair_ai	View profile	papers; research education	Research papers, technical explainers, educational resources, and paper-of-the-week style discovery.	2026-08-09
161	alphaXiv	@askalphaxiv	View profile	papers; arXiv; research discussion	Discover trending AI papers, see what researchers are discussing, and find new research earlier.	2026-08-09
162	Together AI	@togethercompute	View profile	open models; inference; fine-tuning	Open-model inference, fine-tuning, kernels, performance engineering, and production deployment updates.	2026-08-09
163	Fireworks AI	@FireworksAI_HQ	View profile	inference; models; agents	Fast inference, model serving, function calling, agent infrastructure, and production model deployment patterns.	2026-08-09
164	NVIDIA AI	@NVIDIAAI	View profile	GPUs; models; robotics; AI infra	GPU/software launches, model infrastructure, robotics, inference, enterprise AI, and research from NVIDIA.	2026-08-09
165	Groq	@GroqInc	View profile	inference; LPU; low latency	Low-latency inference, serving, model support, and hardware/software approaches to fast LLM execution.	2026-08-09
166	Cerebras	@CerebrasSystems	View profile	AI chips; training; inference	Large-scale AI hardware, fast training/inference, model releases, and alternative compute architectures.	2026-08-09
167	Kaggle	@kaggle	View profile	ML competitions; datasets; notebooks	Hands-on ML competitions, datasets, notebooks, community projects, and practical ways to learn by doing.	2026-08-09
168	Google AI	@GoogleAI	View profile	Gemini; AI products; developer tools	Broader Google AI product launches, Gemini capabilities, creative AI tools, and developer announcements.	2026-08-09
169	Microsoft Research	@MSFTResearch	View profile	research; models; systems	Microsoft research papers, AI systems, multimodal research, agents, and scientific work beyond product marketing.	2026-08-09
170	DeepLearning.AI	@DeepLearningAI	View profile	courses; tutorials; AI news	Courses, short tutorials, practical AI education, The Batch content, and accessible learning paths.	2026-08-09
171	fast.ai	@fastdotai	View profile	deep learning; practical ML; open source	Practical deep learning, educational resources, notebooks, and accessible research from the fast.ai community.	2026-08-09

Sam Altman

@sama

Topics / Tags: OpenAI; frontier models; strategy
What You Can Learn: OpenAI product direction, model launches, infrastructure bets, and the strategic framing behind frontier AI.

Greg Brockman

@gdb

Topics / Tags: OpenAI; engineering; demos
What You Can Learn: OpenAI engineering culture, demos, infrastructure scale, and practical examples of new model capabilities.

Dario Amodei

@DarioAmodei

Topics / Tags: Anthropic; scaling; safety
What You Can Learn: Anthropic's view on scaling, Claude, capability growth, alignment, and long-run AI impact.

Daniela Amodei

@DanielaAmodei

Topics / Tags: Anthropic; enterprise; policy
What You Can Learn: How a frontier lab approaches product operations, enterprise deployment, responsible scaling, and policy.

Mike Krieger

@mikeyk

Topics / Tags: Anthropic; product; consumer AI
What You Can Learn: How Claude evolves as a product, especially consumer UX, artifacts, projects, and practical AI experiences.

Demis Hassabis

@demishassabis

Topics / Tags: Google DeepMind; Gemini; AI science
What You Can Learn: Frontier research, Gemini direction, AI for science, and how DeepMind thinks about AGI.

Sundar Pichai

@sundarpichai

Topics / Tags: Google; Gemini; Search; Workspace
What You Can Learn: Macro product strategy for Gemini, Search, Workspace, infrastructure, and Google's AI platform shift.

Mark Zuckerberg

@finkd

Topics / Tags: Meta; Llama; open weights; consumer AI
What You Can Learn: Meta's open-model strategy, AI assistants, wearables, and how AI is being pushed into consumer products.

Aidan Gomez

@aidangomez

Topics / Tags: Cohere; transformers; enterprise AI
What You Can Learn: Enterprise LLM design, retrieval, multilingual systems, and the perspective of a Transformer-paper coauthor.

Arthur Mensch

@arthurmensch

#10

Topics / Tags: Mistral; open models; Europe
What You Can Learn: Open-weight model releases, European AI strategy, and the case for efficient frontier models.

Clément Delangue

@ClementDelangue

#11

Topics / Tags: Hugging Face; open source; models
What You Can Learn: Open-source AI ecosystem trends, new models on Hugging Face, community tooling, and open-model policy.

Aravind Srinivas

@AravSrinivas

#12

Topics / Tags: Perplexity; AI search; agents
What You Can Learn: AI-native search, answer engines, product velocity, agents, and competitive product strategy.

Mustafa Suleyman

@mustafasuleyman

#13

Topics / Tags: Microsoft AI; consumer AI; policy
What You Can Learn: How Microsoft approaches consumer AI, assistants, product distribution, and AI's societal implications.

Mira Murati

@miramurati

#14

Topics / Tags: Thinking Machines; frontier AI
What You Can Learn: Signals from a major new frontier lab, model/product philosophy, and high-level AI development direction.

Ilya Sutskever

@ilyasut

#15

Topics / Tags: SSI; deep learning; superintelligence
What You Can Learn: Rare but high-signal thinking about deep learning, superintelligence, and frontier-model research priorities.

Logan Kilpatrick

@OfficialLoganK

#16

Topics / Tags: Gemini API; AI Studio; developer tools
What You Can Learn: Gemini developer features, AI Studio workflows, multimodal APIs, and rapid prototyping with Google's models.

Alex Albert

@alexalbert__

#17

Topics / Tags: Anthropic; prompting; Claude
What You Can Learn: Claude prompting techniques, developer resources, model behavior, and practical Anthropic platform guidance.

Boris Cherny

@bcherny

#18

Topics / Tags: Claude Code; coding agents; workflows
What You Can Learn: How the creator of Claude Code uses coding agents: context, parallel work, agent loops, review, and setup patterns.

Amanda Askell

@AmandaAskell

#19

Topics / Tags: Anthropic; alignment; model behavior
What You Can Learn: Alignment, model behavior, character, instruction following, and the philosophy behind assistant behavior.

Cat Wu

@_catwu

#20

Topics / Tags: Anthropic; Claude Code; engineering
What You Can Learn: Claude Code engineering insights, coding-agent product details, and practical implementation choices.

Thariq Shihipar

@trq212

#21

Topics / Tags: Claude Code; context; skills
What You Can Learn: Advanced Claude Code usage, context engineering, skills, subagents, and how coding-agent features work.

Thibault Sottiaux

@thsottiaux

#22

Topics / Tags: OpenAI; Codex; ChatGPT engineering
What You Can Learn: Codex/ChatGPT engineering updates, coding-agent roadmap notes, and developer-facing product changes.

Josh Woodward

@joshwoodward

#23

Topics / Tags: Google Labs; product experiments
What You Can Learn: Google Labs experiments, AI-native product ideas, prototypes, and how new capabilities become consumer tools.

Amjad Masad

@amasad

#24

Topics / Tags: Replit; agents; vibe coding
What You Can Learn: How AI agents change software development, product-building speed, and the economics of creating software.

Guillermo Rauch

@rauchg

#25

Topics / Tags: Vercel; v0; AI SDK; web
What You Can Learn: AI-native web development, v0, AI SDK patterns, interfaces, and shipping production AI applications.

Yann LeCun

@ylecun

#26

Topics / Tags: world models; self-supervision; AGI
What You Can Learn: Contrarian research arguments, world models, self-supervised learning, and critiques of LLM-only paths to AGI.

Geoffrey Hinton

@geoffreyhinton

#27

Topics / Tags: deep learning; AI risk
What You Can Learn: Foundational deep-learning perspective plus arguments about capability growth, safety, and societal risk.

Yoshua Bengio

@Yoshua_Bengio

#28

Topics / Tags: deep learning; safety; governance
What You Can Learn: Deep-learning research, frontier risk, AI governance, and scientific approaches to safer systems.

Andrew Ng

@AndrewYNg

#29

Topics / Tags: AI education; agents; enterprise AI
What You Can Learn: Practical AI adoption, agentic workflows, project selection, education, and how businesses can use AI now.

Fei-Fei Li

@drfeifei

#30

Topics / Tags: computer vision; spatial intelligence; human-centered AI
What You Can Learn: Computer vision, spatial intelligence, human-centered AI, research direction, and AI policy.

Andrej Karpathy

@karpathy

#31

Topics / Tags: LLMs; neural nets; coding; education
What You Can Learn: First-principles understanding of LLMs, neural networks, AI coding, model intuition, and learning-by-building.

Jeff Dean

@JeffDean

#32

Topics / Tags: Google; ML systems; scaling
What You Can Learn: Large-scale ML systems, distributed training, research infrastructure, and foundational Google AI work.

François Chollet

@fchollet

#33

Topics / Tags: ARC-AGI; reasoning; Keras
What You Can Learn: Reasoning benchmarks, what intelligence means, limitations of current LLMs, and rigorous anti-hype analysis.

Tri Dao

@tri_dao

#34

Topics / Tags: FlashAttention; kernels; inference
What You Can Learn: Efficient attention, GPU-aware algorithms, inference/training speed, and systems work behind faster LLMs.

Christopher Manning

@chrmanning

#35

Topics / Tags: NLP; language models; Stanford
What You Can Learn: NLP fundamentals, language-model research, academic perspective, and conceptual foundations behind modern LLMs.

Sasha Rush

@srush_nlp

#36

Topics / Tags: Transformers; NLP; education
What You Can Learn: Reproducible ML research, Transformers, NLP, implementation-focused learning, and technical education.

Jim Fan

@DrJimFan

#37

Topics / Tags: robotics; embodied AI; agents
What You Can Learn: Embodied AI, robotics, multimodal agents, simulation, and how foundation models move into the physical world.

Nathan Lambert

@natolambert

#38

Topics / Tags: post-training; RLHF; open models
What You Can Learn: RLHF, preference learning, post-training, reasoning models, benchmarks, and open-model ecosystem analysis.

Noam Brown

@polynoamial

#39

Topics / Tags: reasoning; self-play; test-time compute
What You Can Learn: Reasoning models, self-play, test-time compute, and the ideas behind stronger deliberative AI systems.

Jason Wei

@_jasonwei

#40

Topics / Tags: chain-of-thought; reasoning; scaling
What You Can Learn: Chain-of-thought, emergent abilities, reasoning behavior, scaling, and frontier-model research.

Chris Olah

@ch402

#41

Topics / Tags: interpretability; neural networks
What You Can Learn: Mechanistic interpretability and clearer mental models for what neural networks represent internally.

Lilian Weng

@lilianweng

#42

Topics / Tags: agents; RLHF; reasoning; safety
What You Can Learn: Deep technical syntheses on agents, reasoning, reinforcement learning, safety, and modern LLM methods.

David Ha

@hardmaru

#43

Topics / Tags: generative models; agents; creativity
What You Can Learn: Unconventional research ideas, generative models, agent behavior, creativity, and experimental AI concepts.

Sebastian Raschka

@rasbt

#44

Topics / Tags: LLMs; PyTorch; training; fine-tuning
What You Can Learn: How LLMs work from code: architectures, fine-tuning, training, evaluation, and implementation details.

Soumith Chintala

@soumithchintala

#45

Topics / Tags: PyTorch; ML systems; open source
What You Can Learn: PyTorch, ML framework design, open-source engineering, and practical deep-learning infrastructure.

Percy Liang

@percyliang

#46

Topics / Tags: foundation models; evaluation; Stanford CRFM
What You Can Learn: Foundation-model evaluation, transparency, benchmarks, policy, and rigorous academic analysis of LLM systems.

Chelsea Finn

@chelseabfinn

#47

Topics / Tags: robot learning; meta-learning; embodied AI
What You Can Learn: Robot learning, reinforcement learning, meta-learning, and systems that learn adaptable behaviors.

Sergey Levine

@svlevine

#48

Topics / Tags: robotics; reinforcement learning
What You Can Learn: Deep reinforcement learning, robot learning, control, and how learning systems interact with the physical world.

Anima Anandkumar

@AnimaAnandkumar

#49

Topics / Tags: AI science; neural operators; NVIDIA
What You Can Learn: AI for science, foundation models for physical systems, scalable ML, and high-performance research.

Yejin Choi

@YejinChoinka

#50

Topics / Tags: NLP; common sense; human-centered AI
What You Can Learn: Language understanding, common-sense reasoning, AI limitations, and human-centered research perspectives.

Pieter Abbeel

@pabbeel

#51

Topics / Tags: robotics; RL; AI startups
What You Can Learn: Robotics, reinforcement learning, AI entrepreneurship, and research-to-product translation.

Oriol Vinyals

@OriolVinyalsML

#52

Topics / Tags: DeepMind; agents; sequence models
What You Can Learn: DeepMind research, sequence modeling, agents, games, and frontier-model science.

Tim Dettmers

@Tim_Dettmers

#53

Topics / Tags: quantization; efficient training; GPUs
What You Can Learn: Quantization, memory-efficient training, hardware constraints, and practical ways to run large models cheaper.

Thomas Wolf

@Thom_Wolf

#54

Topics / Tags: Hugging Face; open models; research
What You Can Learn: Open-source model culture, Hugging Face ecosystem, research trends, and the future of collaborative AI.

Omar Sanseviero

@osanseviero

#55

Topics / Tags: Hugging Face; open LLMs
What You Can Learn: Open-source LLM releases, model tooling, community projects, and hands-on Hugging Face workflows.

Jeremy Howard

@jeremyphoward

#56

Topics / Tags: fast.ai; practical deep learning
What You Can Learn: Practical deep learning, small-team research, AI coding, education, and learning by shipping real systems.

Simon Willison

@simonw

#57

Topics / Tags: LLMs; security; prompting; tools
What You Can Learn: Real LLM experiments, coding-agent workflows, prompt injection, APIs, model quirks, and honest tool testing.

Swyx (Shawn Wang)

@swyx

#58

Topics / Tags: AI engineering; agents; ecosystem
What You Can Learn: The AI-engineering stack, agents, tooling, model releases, industry structure, and what builders should learn next.

Harrison Chase

@hwchase17

#59

Topics / Tags: LangChain; LangGraph; agents
What You Can Learn: Agent architecture, orchestration, managed agents, LangGraph patterns, and production AI workflows.

Jerry Liu

@jerryjliu0

#60

Topics / Tags: LlamaIndex; RAG; document AI
What You Can Learn: RAG, document understanding, agentic data systems, retrieval, context layers, and production knowledge workflows.

Jason Liu

@jxnlco

#61

Topics / Tags: structured outputs; RAG; evals
What You Can Learn: Structured outputs, Instructor, RAG iteration, context engineering, evaluations, and enterprise LLM patterns.

Hamel Husain

@HamelHusain

#62

Topics / Tags: evals; error analysis; AI products
What You Can Learn: How to evaluate AI products, perform error analysis, build data flywheels, and improve unreliable LLM systems.

Chip Huyen

@chipro

#63

Topics / Tags: AI systems; agents; production
What You Can Learn: Production AI system design, agents, inference, data, evaluation, and the tradeoffs behind reliable AI products.

Eugene Yan

@eugeneyan

#64

Topics / Tags: ML systems; recommendation; evals
What You Can Learn: Production ML/LLM patterns, evaluation, recommendation systems, architecture, and practical system-design lessons.

Philipp Schmid

@_philschmid

#65

Topics / Tags: Gemini; fine-tuning; Hugging Face
What You Can Learn: Gemini development, fine-tuning, deployment, open models, and practical model-engineering tutorials.

Shreya Shankar

@sh_reya

#66

Topics / Tags: evals; data systems; AI products
What You Can Learn: User-centered AI evaluation, error discovery, data pipelines, and systematic ways to improve AI applications.

Aran Komatsuzaki

@arankomatsuzaki

#67

Topics / Tags: papers; open source; model research
What You Can Learn: Fast research discovery, new papers, open-model discussions, multilingual model issues, and research commentary.

Louis-François Bouchard

@Whats_AI

#68

Topics / Tags: AI engineering; harnesses; agents
What You Can Learn: AI-engineering roadmaps, agent harnesses, system design, career learning, and production-focused building.

Addy Osmani

@addyosmani

#69

Topics / Tags: AI coding; web; Chrome; performance
What You Can Learn: AI-assisted coding workflows, loop engineering, web performance, and safer ways to combine agents with software engineering.

Thorsten Ball

@thorstenball

#70

Topics / Tags: coding agents; Amp; agent internals
What You Can Learn: How coding agents work, tool loops, context, codebase interaction, and practical lessons from building agentic developer tools.

Armin Ronacher

@mitsuhiko

#71

Topics / Tags: agentic coding; software craft
What You Can Learn: Agentic coding from a veteran software engineer: codebase design, tools, tradeoffs, and how AI changes programming craft.

Mario Zechner

@badlogicgames

#72

Topics / Tags: minimal agents; coding harnesses
What You Can Learn: Minimal, steerable coding-agent design, why simpler harnesses can outperform complex stacks, and practical agent control.

Theo Browne

@theo

#73

Topics / Tags: TypeScript; AI dev tools; coding
What You Can Learn: Opinionated testing of AI coding tools, TypeScript/web stack changes, and developer workflows that actually ship.

Peter Steinberger

@steipete

#74

Topics / Tags: agents; OpenClaw; coding workflows
What You Can Learn: Boundary-pushing agent workflows, AI-native computer use, coding harnesses, and real tools built around agentic engineering.

Matt Pocock

@mattpocockuk

#75

Topics / Tags: agents; TypeScript; context
What You Can Learn: Context engineering, coding-agent patterns, TypeScript, agent spawning, skills, and practical developer education.

Dex Horthy

@dexhorthy

#76

Topics / Tags: 12-factor agents; context; production
What You Can Learn: Production-agent principles, context management, human-in-the-loop design, and reliable software-factory patterns.

Kieran Klaassen

@kieranklaassen

#77

Topics / Tags: compound engineering; parallel agents
What You Can Learn: Parallel coding agents, compound engineering, voice-driven development, context patterns, and high-output AI workflows.

Jesse Kriss

@obra

#78

Topics / Tags: Claude Code; agent skills; software
What You Can Learn: Claude Code workflows, skills, agentic software-development practices, and repeatable approaches to AI-assisted coding.

Ian Nuttall

@iannuttall

#79

Topics / Tags: Claude Code; Cursor; indie building
What You Can Learn: Actionable Claude Code/Cursor best practices, quality and security checklists, and shipping small software businesses with AI.

Ryo Lu

@ryolu_

#80

Topics / Tags: agents; AI products; software
What You Can Learn: Practical AI product-building, agent workflows, coding-tool experimentation, and lessons from shipping AI software.

Nan Yu

@thenanyu

#81

Topics / Tags: AI engineering; agents; product
What You Can Learn: Hands-on AI engineering, agent/product experimentation, and practical ideas from a current builder feed.

Madhu Guru

@realmadhuguru

#82

Topics / Tags: AI building; agents; product
What You Can Learn: Builder-oriented AI workflows, product experiments, and practical examples of applying new model capabilities.

Peter Yang

@petergyang

#83

Topics / Tags: AI products; product management; startups
What You Can Learn: How AI changes product management, startup building, customer workflows, and what useful AI products look like.

Nikunj Kothari

@nikunj

#84

Topics / Tags: AI startups; products; investing
What You Can Learn: AI startup/product observations, tools, founder lessons, and emerging opportunities around new capabilities.

Aditya Agarwal

@adityaag

#85

Topics / Tags: engineering leadership; AI startups
What You Can Learn: Engineering leadership, product building, startup execution, and how strong teams adopt new AI workflows.

Gergely Orosz

@GergelyOrosz

#86

Topics / Tags: software engineering; AI coding; industry
What You Can Learn: How AI coding tools affect professional software teams, engineering careers, productivity, and developer-tool adoption.

Santiago Valdarrama

@svpino

#87

Topics / Tags: ML; AI coding; learning
What You Can Learn: Practical ML/AI learning, building advice, career development, and concise explanations for working engineers.

John Carmack

@ID_AA_Carmack

#88

Topics / Tags: AGI; systems; engineering
What You Can Learn: First-principles AGI and systems engineering from a legendary programmer; useful for separating hard engineering from hype.

George Hotz

@realGeorgeHotz

#89

Topics / Tags: tinygrad; hardware; efficient AI
What You Can Learn: First-principles ML systems, tinygrad, GPUs, autonomous driving, and building efficient AI with small teams.

Pieter Levels

@levelsio

#90

Topics / Tags: solo building; AI products; indie hacking
What You Can Learn: How a solo builder ships AI products quickly, validates demand, monetizes, and uses coding agents on real businesses.

Dan Shipper

@danshipper

#91

Topics / Tags: AI at work; agents; writing; coding
What You Can Learn: Everyday agent workflows for writing, coding, research, company operations, and personal productivity.

Riley Brown

@rileybrown

#92

Topics / Tags: n8n; agents; automation; vibe coding
What You Can Learn: n8n agent systems, automation, multi-agent workflows, vibe coding, and practical tool stacks.

Sabrina Ramonov

@Sabrina_Ramonov

#93

Topics / Tags: Claude Code; prompts; automation; tools
What You Can Learn: AI prompts, Claude/Codex workflows, agent setups, practical tool rankings, and automation playbooks.

Matt Shumer

@mattshumer_

#94

Topics / Tags: prompting; agents; productivity
What You Can Learn: Advanced prompting, coding-agent productivity, autonomous-agent experiments, and high-leverage AI workflows.

Alex Finn

@AlexFinn

#95

Topics / Tags: AI agents; autonomous workflows; creator tools
What You Can Learn: Personal swarms of AI agents, autonomous workflows, Mac-based agents, and experiments in AI-driven economic work.

Ben Tossell

@bentossell

#96

Topics / Tags: AI tools; coding agents; nontechnical building
What You Can Learn: AI tool discovery, coding agents for nontechnical builders, practical workflows, and product ideas.

Greg Isenberg

@gregisenberg

#97

Topics / Tags: AI startup ideas; communities; SaaS
What You Can Learn: AI startup ideas, niche software opportunities, product-market thinking, and business models you can build around new capabilities.

Paul Couvert

@itsPaulAi

#98

Topics / Tags: AI tricks; no-code; automation; productivity
What You Can Learn: Step-by-step AI tricks, no-code workflows, local AI, spreadsheet use cases, creative tools, and practical productivity hacks.

Min Choi

@minchoi

#99

Topics / Tags: prompts; image/video; tools; AI trends
What You Can Learn: New AI use cases, prompts, image/video experiments, creative workflows, and fast examples of what new models can do.

Matt Wolfe

@mreflow

#100

Topics / Tags: AI tools; news; tutorials
What You Can Learn: Daily AI tools, product releases, tutorials, and builder-friendly summaries of what changed recently.

Allie K. Miller

@alliekmiller

#101

Topics / Tags: enterprise AI; careers; product
What You Can Learn: Enterprise AI strategy, AI careers, practical resources, product adoption, and accessible explanations.

Pietro Schirano

@skirano

#102

Topics / Tags: AI design; UI; coding; prototyping
What You Can Learn: AI-assisted design, UI generation, creative coding, rapid prototypes, and visually polished AI product experiments.

Javi Lopez

@javilopen

#103

Topics / Tags: generative AI; image/video; experiments
What You Can Learn: Creative generative-AI experiments, visual prompting, prototypes, and unusual applications of new media models.

Garry Tan

@garrytan

#104

Topics / Tags: YC; startups; AI coding
What You Can Learn: What fast-moving startups are building with AI, coding-agent adoption, founder lessons, and early product patterns.

Bindu Reddy

@bindureddy

#105

Topics / Tags: models; agents; startups; commentary
What You Can Learn: Fast opinions and discussion on models, agents, open-source AI, AI startups, and emerging product patterns.

Ethan Mollick

@emollick

#106

Topics / Tags: AI at work; education; productivity
What You Can Learn: Evidence-based ways to use AI at work, teaching, creative tasks, and knowledge work—plus experiments showing what models can and cannot do.

Aaron Levie

@levie

#107

Topics / Tags: enterprise AI; agents; SaaS
What You Can Learn: How agents reshape enterprise software, SaaS, knowledge work, and company workflows; sharp product/market observations.

Matt Turck

@mattturck

#108

Topics / Tags: AI market; venture; data; startups
What You Can Learn: AI startup landscape, venture trends, enterprise data/AI, and market maps that help identify where companies are forming.

Zara Zhang

@zarazhangrui

#109

Topics / Tags: builders; China AI; ecosystem
What You Can Learn: Curated builder signal, AI ecosystem developments, China/US technology context, and practical sources worth following.

Linus Ekenstam

@LinusEkenstam

#110

Topics / Tags: AI tools; design; prompting
What You Can Learn: Creative AI tools, design workflows, prompting ideas, visual generation, and accessible experiments with new products.

Bilawal Sidhu

@bilawalsidhu

#111

Topics / Tags: spatial AI; video; 3D; generative media
What You Can Learn: Generative video, 3D/spatial AI, visual experiments, and technically informed breakdowns of new creative models.

Nick St. Pierre

@nickfloats

#112

Topics / Tags: image generation; prompting; visual AI
What You Can Learn: Image-generation techniques, visual prompting, model comparisons, and creative workflows for generative media.

Kieran (NoCodeLife)

@nocodelife

#113

Topics / Tags: no-code; Claude Code; app building
What You Can Learn: Building apps with AI/no-code, Claude Code workflows for nontraditional developers, and practical shipping tutorials.

Prajwal Tomar

@PrajwalTomar_

#114

Topics / Tags: Claude Code; coding agents; tutorials
What You Can Learn: Claude Code setup, skills, context, workflows, and builder-oriented tutorials for getting more reliable results.

RohOnChain

@RohOnChain

#115

Topics / Tags: agents; tutorials; AI workflows
What You Can Learn: Fast breakdowns of agent-building tutorials, Claude workflows, and useful learning resources circulating in the AI builder community.

Avid

@Av1dlive

#116

Topics / Tags: agent stacks; architecture; workflows
What You Can Learn: Agent-stack architecture, builder guides, memory/workflow design, and practical patterns for constructing AI systems.

Aakash Gupta

@aakashgupta

#117

Topics / Tags: product management; AI products; growth
What You Can Learn: AI product strategy, product management, growth, and how AI-native companies design and distribute products.

Rowan Cheung

@rowancheung

#118

Topics / Tags: AI news; tools; launches
What You Can Learn: Fast AI product/model news, tool launches, broad industry changes, and easily skimmable summaries.

Deedy Das

@deedydas

#119

Topics / Tags: benchmarks; model releases; startups
What You Can Learn: Concise summaries of model releases, benchmarks, AI companies, coding tools, and whether a launch actually matters.

AK (Akhaliq)

@_akhaliq

#120

Topics / Tags: papers; open-source models; research
What You Can Learn: Very fast discovery of new papers, open-source models, demos, and research projects before they hit mainstream coverage.

Alex Volkov

@altryne

#121

Topics / Tags: ThursdAI; open models; tools
What You Can Learn: Weekly model releases, open-source AI, inference/tooling updates, and live builder commentary across the ecosystem.

Dwarkesh Patel

@dwarkesh_sp

#122

Topics / Tags: interviews; research; frontier labs
What You Can Learn: Deep interviews with frontier researchers and lab leaders; learn how top people reason about scaling, science, and the future.

Jack Clark

@jackclarkSF

#123

Topics / Tags: Anthropic; policy; capabilities; Import AI
What You Can Learn: AI capabilities, safety, policy, compute, and long-term industry trends from a lab founder and longtime analyst.

Kylie Robison

@kyliebytes

#124

Topics / Tags: AI labs; industry reporting
What You Can Learn: Breaking reporting on AI labs, hiring, organizational changes, product moves, and industry dynamics.

Alex Kantrowitz

@Kantrowitz

#125

Topics / Tags: big tech; AI business; interviews
What You Can Learn: AI business reporting, interviews, Big Tech strategy, and practical context behind major AI-company moves.

Lex Fridman

@lexfridman

#126

Topics / Tags: podcasts; researchers; founders
What You Can Learn: Long-form interviews with researchers, founders, and technical leaders that reveal how major AI figures actually think.

Gary Marcus

@GaryMarcus

#127

Topics / Tags: AI criticism; reasoning; reliability
What You Can Learn: Skeptical analysis of model reliability, reasoning, hype, governance, and where current systems still fail.

Kai-Fu Lee

@kaifulee

#128

Topics / Tags: China AI; investing; startups
What You Can Learn: China's AI ecosystem, startup investing, commercialization, and a non-US perspective on AI adoption.

Reid Hoffman

@reidhoffman

#129

Topics / Tags: AI investing; startups; society
What You Can Learn: AI entrepreneurship, investing, labor/productivity implications, and optimistic frameworks for using AI at scale.

Marc Andreessen

@pmarca

#130

Topics / Tags: AI investing; tech strategy
What You Can Learn: Techno-optimist arguments, AI startup/investment themes, software markets, and strong opinions on technology direction.

Vinod Khosla

@vkhosla

#131

Topics / Tags: AI investing; macro; infrastructure
What You Can Learn: Long-cycle AI investing, labor and productivity implications, energy/compute infrastructure, and frontier startup theses.

Steve Nouri

@stevenouri

#132

Topics / Tags: AI news; agents; industry
What You Can Learn: High-volume AI roundups, agent use cases, tools, and industry shifts—a useful broad curation layer.

Cassie Kozyrkov

@quaesita

#133

Topics / Tags: decision intelligence; AI strategy
What You Can Learn: Decision-making with AI, statistical thinking, how to frame business problems, and communicating AI to nontechnical teams.

Bernard Marr

@bernardmarr

#134

Topics / Tags: AI strategy; enterprise; trends
What You Can Learn: Broad enterprise AI trends, business transformation, board-level implications, and accessible industry examples.

Zain Kahn

@heykahn

#135

Topics / Tags: AI tools; coding tips; productivity
What You Can Learn: Practical AI coding tips, tool roundups, prompt-style resources, productivity ideas, and beginner-friendly use cases.

Timnit Gebru

@timnitGebru

#136

Topics / Tags: AI ethics; accountability; social impact
What You Can Learn: Algorithmic accountability, harms, data/representation issues, power structures, and responsible AI criticism.

Margaret Mitchell

@mmitchell_ai

#137

Topics / Tags: model cards; ethics; governance
What You Can Learn: Responsible model release, model cards, evaluation, AI governance, and how organizations communicate model limitations.

Helen Toner

@hlntnr

#138

Topics / Tags: AI policy; national security; governance
What You Can Learn: AI policy, national security, governance, frontier-lab oversight, and institutional approaches to managing risk.

Eliezer Yudkowsky

@ESYudkowsky

#139

Topics / Tags: alignment; existential risk
What You Can Learn: The strongest version of existential-risk arguments, alignment concerns, and why some researchers want much stricter controls.

Zvi Mowshowitz

@TheZvi

#140

Topics / Tags: AI policy; model releases; risk
What You Can Learn: Detailed commentary on AI releases, policy, safety debates, forecasting, and second-order consequences.

Melanie Mitchell

@MelMitchell1

#141

Topics / Tags: complexity; intelligence; AI criticism
What You Can Learn: Careful analysis of intelligence, abstraction, reasoning, complexity, and the gap between benchmark performance and robust intelligence.

Max Tegmark

@tegmark

#142

Topics / Tags: AI safety; governance; future
What You Can Learn: AI safety advocacy, governance, long-term societal risk, and debates about how quickly powerful systems should be deployed.

OpenAI

@OpenAI

#143

Topics / Tags: GPT; ChatGPT; Codex; API
What You Can Learn: Official OpenAI model launches, ChatGPT/Codex features, API updates, research, safety reports, and product announcements.

Anthropic

@AnthropicAI

#144

Topics / Tags: Claude; Claude Code; research
What You Can Learn: Official Claude/Claude Code releases, Anthropic research, safety work, product features, and engineering updates.

Google DeepMind

@GoogleDeepMind

#145

Topics / Tags: Gemini; research; AI science
What You Can Learn: Official Gemini/DeepMind model releases, research breakthroughs, AI science, robotics, and benchmark updates.

Meta AI

@MetaAI

#146

Topics / Tags: Llama; open models; research
What You Can Learn: Official Meta AI research, Llama/open-model work, multimodal systems, and releases from Meta's AI organization.

Mistral AI

@MistralAI

#147

Topics / Tags: Mistral models; open weights; API
What You Can Learn: Official Mistral model releases, open-weight updates, APIs, coding models, and European AI news.

Hugging Face

@huggingface

#148

Topics / Tags: models; datasets; open source
What You Can Learn: New open-source models, datasets, Spaces, libraries, community releases, and tools across the AI ecosystem.

Perplexity

@perplexity_ai

#149

Topics / Tags: AI search; research agents; product
What You Can Learn: Perplexity product releases, search/agent features, model integrations, and AI-native information workflows.

Cohere

@cohere

#150

Topics / Tags: enterprise LLMs; RAG; multilingual
What You Can Learn: Enterprise LLM releases, retrieval, multilingual models, research, and deployment-focused product updates.

LangChain

@LangChainAI

#151

Topics / Tags: LangChain; LangGraph; agents
What You Can Learn: LangChain/LangGraph updates, agent orchestration, LangSmith evaluation/tracing, and production agent examples.

LlamaIndex

@llama_index

#152

Topics / Tags: RAG; document AI; agents
What You Can Learn: RAG, document parsing, context engineering, agentic data systems, framework releases, and examples.

Replit

@Replit

#153

Topics / Tags: AI coding; agents; app building
What You Can Learn: Agentic software-building features, Replit platform updates, vibe-coding examples, and product-building workflows.

Cursor

@cursor_ai

#154

Topics / Tags: AI IDE; coding agents
What You Can Learn: Cursor features, agentic coding workflows, IDE updates, and examples of AI-assisted software development.

v0

@v0

#155

Topics / Tags: UI generation; web; Vercel
What You Can Learn: AI-generated UI, web-app prototyping, front-end workflows, and new v0 capabilities.

n8n

@n8n_io

#156

Topics / Tags: automation; agents; integrations
What You Can Learn: Workflow automation, n8n agents, integrations, templates, and practical ways to connect AI to business tools.

Weights & Biases

@wandb

#157

Topics / Tags: evals; observability; ML tooling
What You Can Learn: LLM/agent evaluation, tracing, experiment tracking, observability, and production ML engineering.

AI Engineer

@aiDotEngineer

#158

Topics / Tags: AI engineering; talks; agents
What You Can Learn: Conference talks and practitioner insights on agents, context, evals, coding systems, and production AI engineering.

The Rundown AI

@TheRundownAI

#159

Topics / Tags: AI news; product launches; tools
What You Can Learn: Fast broad AI news, funding, model releases, product launches, and tool discovery.

DAIR.AI

@dair_ai

#160

Topics / Tags: papers; research education
What You Can Learn: Research papers, technical explainers, educational resources, and paper-of-the-week style discovery.

alphaXiv

@askalphaxiv

#161

Topics / Tags: papers; arXiv; research discussion
What You Can Learn: Discover trending AI papers, see what researchers are discussing, and find new research earlier.

Together AI

@togethercompute

#162

Topics / Tags: open models; inference; fine-tuning
What You Can Learn: Open-model inference, fine-tuning, kernels, performance engineering, and production deployment updates.

Fireworks AI

@FireworksAI_HQ

#163

Topics / Tags: inference; models; agents
What You Can Learn: Fast inference, model serving, function calling, agent infrastructure, and production model deployment patterns.

NVIDIA AI

@NVIDIAAI

#164

Topics / Tags: GPUs; models; robotics; AI infra
What You Can Learn: GPU/software launches, model infrastructure, robotics, inference, enterprise AI, and research from NVIDIA.

Groq

@GroqInc

#165

Topics / Tags: inference; LPU; low latency
What You Can Learn: Low-latency inference, serving, model support, and hardware/software approaches to fast LLM execution.

Cerebras

@CerebrasSystems

#166

Topics / Tags: AI chips; training; inference
What You Can Learn: Large-scale AI hardware, fast training/inference, model releases, and alternative compute architectures.

Kaggle

@kaggle

#167

Topics / Tags: ML competitions; datasets; notebooks
What You Can Learn: Hands-on ML competitions, datasets, notebooks, community projects, and practical ways to learn by doing.

Google AI

@GoogleAI

#168

Topics / Tags: Gemini; AI products; developer tools
What You Can Learn: Broader Google AI product launches, Gemini capabilities, creative AI tools, and developer announcements.

Microsoft Research

@MSFTResearch

#169

Topics / Tags: research; models; systems
What You Can Learn: Microsoft research papers, AI systems, multimodal research, agents, and scientific work beyond product marketing.

DeepLearning.AI

@DeepLearningAI

#170

Topics / Tags: courses; tutorials; AI news
What You Can Learn: Courses, short tutorials, practical AI education, The Batch content, and accessible learning paths.

fast.ai

@fastdotai

#171

Topics / Tags: deep learning; practical ML; open source
What You Can Learn: Practical deep learning, educational resources, notebooks, and accessible research from the fast.ai community.