Brent Traut ✓
@btraut · Washington, USA · joined 25 May 2008
dad • rock climber • photographer • eng @openai
14 858Followers
144Following
4 057Posts total
2.6MViews on collected posts
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If you think this is just text transcription, I promise you it's not; humans are hard-wired to communicate through language, and this seriously leaps across the uncanny valley to something real and powerful.
8.7K views · 46 likes
· 0 reposts · 3 replies
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I have smart light switches hooked into homebridge which are then hooked into Apple Home. Something in chat chain breaks all the time, and it turns out that ChatGPT is great at diagnosing…
So now I just use ChatGPT voice to turn my lights on and off.
3.7K views · 22 likes
· 0 reposts · 4 replies
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When we first built the desktop app, models weren't as smart or dedicated and therefore just didn't produce as much data. As models improved, threads became longer and longer. Then the release of /goal really blew things up.
99.4K views · 545 likes
· 5 reposts · 16 replies
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Since the beginning, ChatGPT would naively load all of your thread's data (for all time) even if you just wanted to see the last few messages. This meant that thread data, and thus memory usage, was essentially unbounded.
81.9K views · 387 likes
· 3 reposts · 5 replies
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Last week, I pushed a change to the ChatGPT desktop app that makes the loading of threads faster. Not just a little faster. A LOT faster.
✅ Long threads now load over 90% faster.
✅ Decreased the memory footprint of long threads by over 90%.
2.1M views · 5.6K likes
· 206 reposts · 488 replies
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Not only is cold loading faster, but forking chats and creating side chats should now be nearly instantaneous. What was once an unbounded problem is now both bounded and fast.
41.2K views · 353 likes
· 4 reposts · 7 replies
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This took over 300 PRs over a couple months, and while we're extremely proud of the work, we know there's much more we can do.
In the coming weeks, we're going to drop memory usage by another order of magnitude. Stay tuned!
36.4K views · 759 likes
· 9 reposts · 30 replies
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With this update, we now lazy load data. When you navigate to a thread, we load the latest few turns, and you only pay the cost of loading more when you scroll back. This required a major re-architecture of how ChatGPT stored and loaded files on disk.
53.6K views · 433 likes
· 4 reposts · 7 replies
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@Rudeg continues to cook up experiences in the app that are easy to use, obvious in retrospect, and yet fresh and new. How long before competitors have custom sections?
12.5K views · 30 likes
· 0 reposts · 9 replies
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ChatGPT Work has quietly become the best travel agent on the planet.
I just got back from an absolutely epic road trip along the Oregon coast with my family, and I give most of the credit to Chat. I never would've been able to plan this on my own.
5.5K views · 39 likes
· 0 reposts · 1 replies
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Custom sidebar sections just landed in ChatGPT/Codex desktop app 🗂
organize your tasks and projects into sections or just ask codex to organize the sidebar for you! https://t.co/VbbPTLzrjW
164.7K views · 505 likes
· 52 reposts · 55 replies
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Against accounts of the same size
12 posts from the last 90 days, next to the 10K–100K follower range. shown widely, but few of those viewers react.
Median views38 838this account924median for 10K–100K
Reach, %261.39%this account3.62%median for 10K–100K
Engagement, %0.64%this account1.52%median for 10K–100K
| Metric | This account | Median for 10K–100K | Ratio |
|---|---|---|---|
| Median views per post | 38 838 | 924 | 42.0× |
| Reach (views ÷ followers) | 2.6× audience | 3.62% | 72.2× |
| Engagement rate | 0.64% | 1.52% | 0.42× |
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
164.7K28 Aug
5.5K29 Aug
12.5K
53.6K30 Aug
36.4K
41.2K
2.1M
81.9K
99.4K
6.4K
3.7K2 Sep
8.7K4 Sep
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
0.37%28 Aug
0.73%29 Aug
0.31%
0.83%30 Aug
2.19%
0.88%
0.30%
0.48%
0.57%
1.45%
0.71%2 Sep
0.56%4 Sep
Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.
What the audience does
Likes81.6%8 773 in total
Reposts2.6%283 in total
Replies5.8%625 in total
Bookmarks9.9%1 065 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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