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Karim Atiyeh

@karimatiyeh · Miami, FL · joined 04 Jun 2009

Cofounder at Ramp (@tryramp) 💳

193 369Followers
2 181Following
1 527Posts total
440.7KViews on collected posts

Últimas publicaciones

We built Token Spend Management to understand AI costs and Router to use the most efficient model for the task. Now, both are available to customers. Inspect comes from the same instinct: if we need a better tool, we build it. Less than a year and over 1M+ sessions later, 75% 13.7K views · 95 likes · 4 reposts · 8 replies Open on X →
It's rare to see a non-AI frontier lab build an in-house AI coding tool that works so much better than what frontier labs have to offer. Ramp did this with Inspect: an AI coding harness fully integrated with their systems, running on cloud machines, and being a smash hit inside h
54.3K views · 97 likes · 12 reposts · 3 replies Open on X →
The world has changed: choosing an AI model is now a full-time job. GPT-5.6 Luna, Sol, or Terra? Claude Opus 4.8 or Sonnet 5? Gemini 3.1 Pro, Kimi K3, or GLM 5.2? Medium, high, or xhigh reasoning? Best solve rate, lowest cost, or fastest response? And next week, the answer 40.9K views · 210 likes · 15 reposts · 18 replies Open on X →
Contrarians tend to do very well at Ramp. @shevchenkoaalex, who runs @ramplabs, is one of them. High-agency people doing hard work should have real say in what work is worth chasing. Especially when everyone else says "that sounds too hard" or "that'll never work." Those are 25.9K views · 126 likes · 13 reposts · 8 replies Open on X →
Most people judge AI models by what they can do today. @rahulgs judges the slope. When we started Ramp, people had tasted better software at home and could no longer tolerate the tools they were handed at work. So we built something better. Same thing is happening now with AI.
0:46
130.5K views · 329 likes · 30 reposts · 50 replies Open on X →
Why did a spend management platform start its own AI research lab? @karimatiyeh describes @RampLabs as a “collection of crazy ambitious people that don’t like to be told that something is impossible”. It started about a year ago and has since worked on projects like building ht
5:36
117.9K views · 130 likes · 13 reposts · 16 replies Open on X →
Proud of this one. What started as an internal cost-saving hack now routes AI for 70,000 customers and today it's open to everyone. The best model changes every week. Your code doesn't have to. 57.5K views · 214 likes · 8 reposts · 24 replies Open on X →

Frente a cuentas del mismo tamaño

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

Visualizaciones medianas54 275esta cuenta4 544mediana de 100K–1M
Alcance, %28.07%esta cuenta1.75%mediana de 100K–1M
Interacción, %0.43%esta cuenta1.35%mediana de 100K–1M
MétricaEsta cuentaMediana de 100K–1MProporción
Visualizaciones medianas por publicación54 2754 54411.9×
Alcance (visualizaciones ÷ seguidores)28.07%1.75%16.0×
Tasa de interacción0.43%1.35%0.32×

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

57.5K20 Jul
117.9K7 Aug
130.5K
25.9K10 Aug
40.9K19 Aug
54.3K25 Aug
13.7K26 Aug

Last 7 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.43%20 Jul
0.14%7 Aug
0.31%
0.57%10 Aug
0.59%19 Aug
0.21%25 Aug
0.78%26 Aug

Reactions — likes, reposts, replies and quotes — divided by views. Median for 100K–1M accounts is 1.35%.

What the audience does

Likes65.5%1 201 in total
Reposts5.2%95 in total
Replies6.9%127 in total
Quotes0.4%7 in total
Bookmarks22.0%404 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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