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Chip Huyen ✓

@chipro · San Francisco, CA · joined 30 Jun 2008

@aisysbooks @goodailist AI Engineering: https://t.co/94dv4uTU1H Designing MLSys: https://t.co/G81hL2dWmr Reading @chipslib

148 015Followers
722Following
587Posts total
4.6MViews on collected posts

Últimas publicaciones

i'm researching best practices for skills. what's the most number of skills you've had installed for your agents? 16.3K views · 42 likes · 2 reposts · 40 replies Open on X →
real question: why does gpt 5.6 over engineer so much? 138.1K views · 1K likes · 27 reposts · 235 replies Open on X →
what's a good model tiering system? i'm sick of telling my agent orchestrator things like: "for Claude, use model X, for OpenAI, use model Y, etc." i want to be able to tell my orchestrator: "use models tier ..." for this kind of task 32.1K views · 184 likes · 9 reposts · 49 replies Open on X →
that's the problem he should've sent them in all caps https://t.co/zqNe1FPI7I
19.3K views · 99 likes · 11 reposts · 4 replies Open on X →
this seems to have reached a corner of the internet that my innocent soul wasn't ready for. "why do you hate em dashes so much?" this isn't about punctuation. this is about getting AI to follow simple instructions "what model was it?" 4o "why not use a thinking model? it works 47.5K views · 162 likes · 0 reposts · 27 replies Open on X →
@chipro you're absolutely right! it's not just insane — it's maddening! 55.8K views · 2.3K likes · 8 reposts · 8 replies Open on X →
$100 for anyone who can show me how to get ChatGPT to stop using emdashes. it's driving me insane https://t.co/cr7t0PMIor
3.8M views · 8.7K likes · 214 reposts · 1.3K replies Open on X →
@chipro great overview. looking at the current state of agents a planner is the centerpiece of a multi agent strategy cauz the stuff doesn’t work well enough in a multi turn fashion.and like you said that is as easy as prompting it. we don’t really need abstractions for agents. 842 views · 2 likes · 0 reposts · 1 replies Open on X →
@chipro thanks huyen for writing this. time to grab coffee and dig into this cool guide. solid work 😌 896 views · 2 likes · 0 reposts · 0 replies Open on X →
@chipro I found the high level definition of agent of @swyx quite concise "agent = llm + memory + planning + tools + while loop" (some objective would be implied here) https://t.co/KJBP9rDj52 for a lightweight agent library I liked the approaches of OpenAI (Swarm 8.6K views · 38 likes · 2 reposts · 1 replies Open on X →
My 8000-word note on agents: https://t.co/x5IzSUwO5b Covering: 1. An overview of agents 2. How the capability of an AI-powered agent is determined by the set of tools it has access to and its capability for planning 3. How to select the best set of tools for your agent 4. 417.7K views · 2.9K likes · 459 reposts · 69 replies Open on X →
@simonw agent = llm + memory + planning + tools + while loop https://t.co/qEd8jixioW 27.9K views · 285 likes · 11 reposts · 13 replies Open on X →

Frente a cuentas del mismo tamaño

4 publicaciones de los últimos 90 días, junto al rango de 100K–1M seguidores. llega a mucha gente, pero pocos de esos espectadores reaccionan.

Visualizaciones medianas25 728esta cuenta5 983mediana de 100K–1M
Alcance, %17.38%esta cuenta1.49%mediana de 100K–1M
Interacción, %0.67%esta cuenta0.93%mediana de 100K–1M
MétricaEsta cuentaMediana de 100K–1MProporción
Visualizaciones medianas por publicación25 7285 9834.30×
Alcance (visualizaciones ÷ seguidores)17.38%1.49%11.7×
Tasa de interacción0.67%0.93%0.72×

Otras cuentas de este rango →   Comparar con otra cuenta →   Cómo se construyen estas referencias →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

27.9K7 Oct
417.7K7 Jan
8.6K
896
842
3.8M3 Aug
55.8K
47.5K4 Aug
19.3K10 Aug
32.1K17 Aug
138.1K25 Aug
16.3K

Last 12 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

1.11%7 Oct
0.82%7 Jan
0.48%
0.22%
0.36%
0.28%3 Aug
4.21%
0.40%4 Aug
0.59%10 Aug
0.75%17 Aug
0.92%25 Aug
0.51%

Reactions — likes, reposts, replies and quotes — divided by views. Median for 100K–1M accounts is 0.93%.

What the audience does

Likes64.1%15 773 in total
Reposts3.0%743 in total
Replies7.0%1 727 in total
Quotes2.4%592 in total
Bookmarks23.5%5 781 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.

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