vans163

@vans1631 · joined 01 May 2019

https://t.co/zANvdBg7oe

42 138Followers

52Following

331Posts total

75.7KViews on collected posts

Latest posts

vans163@vans16316 Sep

@vans1631 I really think this would improve the efficiency of @ama_protocol 13 views · 0 likes · 0 reposts · 0 replies Open on X →

vans163@vans16311 Jun

UltraCode Opus 4.8 audit. Each new frontier model finds something new! Great to know the only remaining attacks are quite low severity. Can we consider this merkle tree, the Hot Binary Sparse Merkle Tree we built sound? Or do we get MYTHOS to audit it as well from a security

41.6K views · 78 likes · 21 reposts · 4 replies Open on X →

vans163@vans163131 May

One reason we chose to orchestrate around I/O and not APIs is because thing like this. (You cannot enable ultracode using the API, you cannot set the model to use it, you must only use the /effort switch) Now you either have to maintain a complex set of patches ontop a https://

20.9K views · 26 likes · 2 reposts · 1 replies Open on X →

vans163@vans163128 May

MMR - Merke Mountain Range has been slipped in upstream along with the validator optimization. MMRs allow proving a block from the past is part of the mainchain. Important for bridges/Intents/withdrawls/deposits https://t.co/1PyrRJlfog

4.2K views · 16 likes · 4 reposts · 0 replies Open on X →

vans163@vans163128 May

Validators on AMA are now able to sync from a contractstate bundle. As long as the merkle root matches the most recent block you are in-sync. Reducing RAM usage from 32G to under 3G and disk usage from 600GB to under 10GB. This should make it much easier to run a validator. htt

4K views · 10 likes · 1 reposts · 2 replies Open on X →

vans163@vans163118 May

First @Polymarket trading agent deployed on AMA Hub https://t.co/sNgN4JpeBl

5.1K views · 101 likes · 2 reposts · 1 replies Open on X →

Against accounts of the same size

1 posts from the last 90 days, next to the 10K–100K follower range. reaches fewer people than peers of the same size.

Median views13this account924median for 10K–100K

Reach, %0.03%this account3.62%median for 10K–100K

Engagement, %0.00%this account1.52%median for 10K–100K

Metric	This account	Median for 10K–100K	Ratio
Median views per post	13	924	0.01×
Reach (views ÷ followers)	0.03%	3.62%	0.01×
Engagement rate	0.00%	1.52%	0.00×

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

5.1K18 May

4K28 May

4.2K

20.9K31 May

41.6K1 Jun

136 Sep

Last 6 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

2.07%18 May

0.35%28 May

0.47%

0.14%31 May

0.25%1 Jun

0.00%6 Sep

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.

What the audience does

Likes84.0%231 in total

Reposts10.9%30 in total

Replies2.9%8 in total

Quotes0.7%2 in total

Bookmarks1.5%4 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.