Twitter/X Follow List¶

30 handles. Curated. No filler.

The philosophy¶

Do NOT scroll Twitter’s main timeline. It will destroy your attention span and radicalize you politically. Instead:

Create a private List called “Inference Eng” and add the 30 handles below.
Access ONLY via that list URL. Bookmark it. Delete the main app.
15 min × 5 weekdays = 75 min/week. Scan for: paper releases, kernel tricks, hiring signals, engine features shipping.
Never post political takes. Never quote-tweet drama. Never subtweet. This is a professional channel.

X handles change; verify by the person’s known org / pinned tweet before following. Handles below are known-good as of 2025–2026.

Tier 1: The kernel + attention crown (5)¶

Handle	Person	Why
@tri_dao	Tri Dao	FlashAttention 1/2/3 author, Mamba, Together AI. Frequent technical threads.
@cHHillee	Horace He	PyTorch core, torch.compile, FlexAttention. The “brrr” post author.
@jeremyphoward	Jeremy Howard	fast.ai, GPU MODE lectures, systems-first pedagogy.
@marksaroufim	Mark Saroufim	GPU MODE cofounder, PyTorch/Meta, TorchAO, TorchTitan.
@thom_wolf	Thomas Wolf	HuggingFace cofounder; deep systems posts, Ultra-Scale Playbook lineage.

Tier 2: Inference engines / research (7)¶

Handle	Person	Why
@woosuk_k	Woosuk Kwon	vLLM cofounder, PagedAttention lead author.
@zhuohan123	Zhuohan Li	vLLM cofounder, LMSYS.
@simon_mo_	Simon Mo	vLLM project lead.
@lm_zheng	Lianmin Zheng	SGLang cofounder, Chatbot Arena.
@ying11231	Ying Sheng	SGLang cofounder, RadixAttention.
@yzh119	Zihao Ye	FlashInfer author (CMU).
@HaoAILab	Hao AI Lab (Hao Zhang UCSD)	Speculative decoding, engine research.

Tier 3: Quantization + compression (4)¶

Handle	Person	Why
@Tim_Dettmers	Tim Dettmers	LLM.int8(), QLoRA, bitsandbytes, GPU-buying-guide author.
@younesbelkada	Younes Belkada	HF integrations for quant methods; bitsandbytes co-maintainer.
@gaunernst	Thien Tran	Quantized training, GPU MODE Lec 30.
@danielhanchen	Daniel Han	Unsloth author; low-level optimization posts.

Tier 4: Distributed / training systems (4)¶

Handle	Person	Why
@StasBekman	Stas Bekman	HF/Snowflake, distributed training practitioner writings.
@sea_snell	Charlie Snell	Test-time compute research; UCB.
@kellerjordan0	Keller Jordan	Modded-nanogpt speedrun, Muon optimizer, training microtricks.
@lambdaviking	William Merrill	Formal capabilities + parallelism research.

Tier 5: The pedagogues + synthesizers (5)¶

Handle	Person	Why
@karpathy	Andrej Karpathy	nanoGPT, education, occasional infra posts. Rate-limits himself, high signal.
@chipro	Chip Huyen	AI Engineering author; product/ML platform.
@rasbt	Sebastian Raschka	LLM From Scratch, monthly synthesis essays.
@simonw	Simon Willison	Daily curation + annotation of the entire LLM release firehose.
@natolambert	Nathan Lambert	RLHF/post-training + industry commentary; Interconnects.

Tier 6: Hardware + industry (3)¶

Handle	Person	Why
@dylan522p	Dylan Patel	SemiAnalysis; data center + GPU supply-chain intel.
@dzhulgakov	Dmytro Dzhulgakov	Fireworks AI CTO; production serving posts.
@soumithchintala	Soumith Chintala	PyTorch cofounder; industry perspective.

Tier 7: Guest passes (rotate in/out; 2 at a time) (2)¶

Use these slots for people relevant to what you’re currently building. Suggestions:

Building attention kernels? @tri_dao is already up; add @realDanFu (Dan Fu, Together / co-Mamba) and @simran_s_arora (ThunderKittens/Based).
DeepSeek/MoE deep-dive? DeepSeek doesn’t have canonical individual handles; follow the @deepseek_ai org account.
Reading vLLM source? Add @robertshaw21 (Robert Shaw, Neural Magic/RH), @mgoin_ (Michael Goin).
Local/GGUF? Add @ggerganov (Georgi Gerganov, llama.cpp).
Long-context/scaling? Add @_akhaliq (Ahmed Awadallah, HF paper firehose).
RL infra? Add @nrehiew_ / @vwxyzjn (Costa Huang, TRL).

Handles I intentionally did NOT include¶

Big-name AI CEOs and VCs. Signal-to-noise ratio catastrophic for this roadmap.
Random “AI influencer” accounts. They regurgitate primary sources with delay. Read the primary sources.
Anon accounts with no verifiable technical output. High risk, low reward.
Corporate accounts except @deepseek_ai and @vllm_project (which post announcements). Follow the people.

Weekly X protocol¶

Open your List URL on Mon/Wed/Fri morning (15 min max).
Save (bookmark) 3–5 threads/links per session.
Batch-read the saved bookmarks Sunday morning during your r/LocalLLaMA half-hour.
Reply only when you have a real technical addition. Never for engagement bait. Never “great post!” replies.
Post-original-content cadence: maximum once every 2 weeks; content = your blog post / repo / benchmark. Not commentary.

When to post from your own account¶

Do post:

A concrete new artifact (blog, repo, benchmark) with a screenshot and a link. Once.
A well-scoped technical question a specific expert can answer, tagged politely. Once, and if no answer, drop it.
A correction to a wrong number in someone else’s post, backed by your reproduction. Rare, valuable, do it well.

Do NOT post:

Vague hot takes about the industry.
Reposts of press releases.
“Excited to share” without a link to the actual thing.
Anything late at night, angry, or under 200 characters of substance.

Handle-verification workflow¶

Before adding: check pinned tweet + bio + “About” panel for known-org affiliation. If you can’t verify identity in 30 seconds, don’t add. Impostor accounts of famous ML people exist.

If a handle above turns out inactive or renamed by the time you read this, search: [real name] site:x.com or [real name] twitter — pinned tweets and org affiliations are the disambiguator.