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Jo Kristian Bergum ✓

@jobergum · Trondheim, Norge · joined 19 Jul 2009

CEO https://t.co/qdJ3bIZOOU - The retrieval engine built for agents.

20 345Followers
1 548Following
15 259Posts total
19.5KViews on collected posts

Derniers posts

@jobergum @thorstenball @sqs that also means dev tools can’t assume users will inspect the generated code. validation, rollback, and clear failure states become core features when the builder isn’t an engineer. 5 views · 0 likes · 0 reposts · 0 replies Open on X →
Astra is actually quite good at using a browser (also faster, but not fast) 1.2K views · 2 likes · 0 reposts · 1 replies Open on X →
Maybe a bit harsh but even with infinite capable models agi or whatever you still need someone to like tell it what to build 1.3K views · 11 likes · 1 reposts · 1 replies Open on X →
@jobergum @sqs Yep. I think that's one of the points that @sqs made re: agents & bug tracking. Previously the bug tracker had leverage, now you can jump into code. 1.2K views · 0 likes · 0 reposts · 1 replies Open on X →
Tip of the day is to buy bananas cheap before they go bad and then put them to the freezer so you can use them for shakes 1.5K views · 6 likes · 0 reposts · 3 replies Open on X →
@jobergum @thorstenball @sqs Couldn't agree more. Appears that more knowledge workers are upskilling to meet the challenge of learning how software works. 44 views · 1 likes · 0 reposts · 1 replies Open on X →
Listened to raising an agent and @thorstenball and @sqs discussed every company now building dev tools. imho the natural reason for this is that now everyone are developers (thanks to models good at code) 2.6K views · 8 likes · 0 reposts · 4 replies Open on X →
@kishorelive Lack of imagination and agency has always been the bottleneck 1.5K views · 3 likes · 0 reposts · 0 replies Open on X →
@jobergum @HornetDev Here's how you can get a memory for your agents that retrives and saves automatically shared amongst all the agents. https://t.co/8PpCgkR9rh 8 views · 0 likes · 0 reposts · 0 replies Open on X →
@jobergum @HornetDev Are there other doors in the same building marked WASP, BEE and SCARY BIG FLY ? 215 views · 2 likes · 0 reposts · 0 replies Open on X →
@jobergum @HornetDev when the first release? 162 views · 1 likes · 0 reposts · 0 replies Open on X →
Behind this door we are redefining retrieval for agents. There has never been a better time to build. https://t.co/wj5dnb3beY
9.8K views · 51 likes · 2 reposts · 7 replies Open on X →

Face aux comptes de taille comparable

8 posts des 90 derniers jours, à côté de la tranche de 10K–100K abonnés. diffusé largement, mais peu de ces spectateurs réagissent.

Vues médianes1 276ce compte924médiane pour 10K–100K
Portée, %6.27%ce compte3.62%médiane pour 10K–100K
Engagement, %0.36%ce compte1.52%médiane pour 10K–100K
IndicateurCe compteMédiane pour 10K–100KRapport
Vues médianes par post1 2769241.38×
Portée (vues ÷ abonnés)6.27%3.62%1.73×
Taux d'engagement0.36%1.52%0.24×

Autres comptes de cette tranche →   Comparer avec un autre compte →   Comment ces repères sont établis →

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

9.8K21 Jan
162
215
829 Jun
1.5K7 Sep
2.6K
44
1.5K
1.2K
1.3K
1.2K
59 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

0.61%21 Jan
0.62%
0.93%
0.00%29 Jun
0.20%7 Sep
0.47%
4.55%
0.61%
0.08%
0.97%
0.26%
0.00%9 Sep

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

What the audience does

Likes73.9%85 in total
Reposts2.6%3 in total
Replies15.7%18 in total
Bookmarks7.8%9 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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