Poolside

@poolsideai · San Francisco, CA · joined 12 May 2023

We build models for agentic coding and long-horizon tasks. Try Laguna: https://t.co/setRB1BuGD

14 781Followers

2Following

229Posts total

204.7KViews on collected posts

Against accounts of the same size

9 posts from the last 90 days, next to the 10K–100K follower range. shown widely, but few of those viewers react.

Median views10 395this account1 756median for 10K–100K

Reach, %70.33%this account5.38%median for 10K–100K

Engagement, %0.52%this account1.75%median for 10K–100K

Metric	This account	Median for 10K–100K	Ratio
Median views per post	10 395	1 756	5.92×
Reach (views ÷ followers)	70.33%	5.38%	13.1×
Engagement rate	0.52%	1.75%	0.30×

Others in this range → Compare with another account → How these benchmarks are built →

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

78.4K28 Jul

36.4K11 Aug

12.8K

9.3K12 Aug

5.6K

10.4K13 Aug

38.9K14 Aug

8.1K17 Aug

4.8K

Last 9 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.52%28 Jul

0.24%11 Aug

1.46%

0.59%12 Aug

0.45%

0.36%13 Aug

0.25%14 Aug

0.94%17 Aug

0.54%

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.75%.

What the audience does

Likes66.3%808 in total

Reposts8.9%109 in total

Replies3.9%47 in total

Quotes3.1%38 in total

Bookmarks17.7%216 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.

Latest posts

We’ll be at ModCon ’26 in SF on August 18! @varunrandery is joining the frontier models panel to talk about building models for long-horizon agentic work, where open models differentiate, and what it takes to get them into production. Join us in SF or tune in online ↓ 4.8K views · 23 likes · 2 reposts · 1 replies 17 Aug 2026 Agentic evals are messy. A benchmark score tells you something about model performance, but it also reflects the whole system around it: the harness, sandbox, dependencies, timeouts and sometimes a loophole the agent found in the task. That’s why trajectories matter so much to 8.1K views · 65 likes · 8 reposts · 2 replies 17 Aug 2026 Meet… Arena Conversations. @petergostev sits down with @poolsideai researchers,Connor Adams and Aalhad Patankar, to discuss how they’re building frontier open coding models. Episode drops today at 10am PT on our YouTube. They dig into Poolside's Laguna model family, why the htt 38.9K views · 87 likes · 6 reposts · 4 replies 14 Aug 2026 Building frontier models involves a hundred decisions rarely discussed publicly: when to stop scaling, what data to keep, how to differentiate, whether to release the weights. On August 18th at ModCon '26, Paige Bailey of @GoogleDeepMind, Joseph Spisak of @reflection_ai, Victor 10.4K views · 28 likes · 4 reposts · 2 replies 13 Aug 2026 Come hear @mgalle and @sudip_r0y get into the weeds on post-training, agent RL, continuous learning, and what it takes to make models work reliably in production! 5.6K views · 22 likes · 2 reposts · 0 replies 12 Aug 2026 First episode of Field Notes, our new monthly series on the leaders shaping AI. @sudip_r0y, Adaption Co-founder, and @mgalle, post-training lead at @poolsideai discuss the last 5% of reliability and what it actually costs. https://t.co/smBmJa0yYh 9.3K views · 33 likes · 11 reposts · 8 replies 12 Aug 2026 we knew the community could make Laguna faster. 2.6x faster is pretty fun :) huge congrats to the winner, and to all 35 solvers who spent the last few weeks pushing Laguna XS 2.1 further! more reasons to build in the open, together 🤝 12.8K views · 162 likes · 15 reposts · 8 replies 11 Aug 2026 We started the https://t.co/VYBsJdCyNl challenge with @poolsideai with one key question. How much faster can the community make Laguna XS 2.1 run on a Mac? The answer so far has been 2.6x faster. Nearly 1,800 submissions and 35 solvers later, the challenge comes to a close http 36.4K views · 67 likes · 11 reposts · 1 replies 11 Aug 2026 Today, we’re releasing Poolside Desktop Assistant. One place to run coding agents across macOS, VS Code, and Visual Studio. We built it for ourselves and have used it every day for the past year. Now we’re opening it up to everyone. https://t.co/b4L4pGITZK 78.4K views · 321 likes · 50 reposts · 21 replies 28 Jul 2026