codila ✓
@0xCodila · AI industry · joined 18 Aug 2015
AI - researcher & coder | writing about what I use myself
21 191Followers
80Following
1 320Posts total
17.4MViews on collected posts
Posts recentes
Procurando novos posts…
@0xCodila Thing is jev is a copy of another developer's work
https://t.co/EYPMmSn4UC
985 views · 4 likes
· 1 reposts · 0 replies
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A US frontier AI lab (TypeSafe AI) just announced a "breakthrough" System 1 architecture. The problem? An independent Indian developer built, published, and open-sourced the exact same single-pass RL architecture a full year ago.
The frontier lab generalized it, slapped a new h
191.4K views · 3.6K likes
· 447 reposts · 81 replies
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@0xCodila OMG WHAT'S A BANGER! I just found out about this engineering today, and you're the first one to post a complete guide on how to use Jev
Thanks bro booked and going to start reading it right now
9.2K views · 5 likes
· 0 reposts · 1 replies
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Jev is the "Internet" moment for the AI industry
It tells your agents and LLMs what to do next, in milliseconds and at almost zero cost
If you set it up correctly, you will have the AI engineer’s stack for 2028
In this article, I show you how https://t.co/x3qn41ejnr
1.6M views · 3.1K likes
· 379 reposts · 70 replies
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This is actually insane. This uses @typesafeai Jev model, as a plugin in Claude to review all the un-nesseasary tool calls, and it takes 1s to run!
Like, literally, 1 second to take my Claude session from nearly 1M to ... 86K tokens! 😮
Ask your claude to install it and be http
1.2M views · 8.4K likes
· 464 reposts · 164 replies
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found the perfect use case for @typesafeai Jev:
instant compaction
in 2026, why is compaction still a summarization prompt?
Jev can make it instant by scoring every tool call and dropping what’s irrelevant https://t.co/h6NzKzNpCg
3.8M views · 10.8K likes
· 667 reposts · 419 replies
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0:05
I used Jev to classify 1,018 AI research papers.
The result: $0.08 total cost and 256ms median end-to-end latency per paper.
The pipeline was:
1. Summarize each paper with DeepSeek V4 Flash
2. Send the title + summary + 24 possible topics to Jev
3. Use Jev to classify each htt
172.3K views · 2K likes
· 140 reposts · 122 replies
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0:10
Breaking: Browser Use + Jev = Ultrafast ⚡
Findings flights took 7s and cost only $0.0039 🤯
> new action space every step
> DOM state space
> small LLM fallback to type
(this video is at 1x speed btw)
Built a tiny open source browser agent. try it below ↓ https://t.co/AplCBRYC
3.2M views · 9K likes
· 650 reposts · 286 replies
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0:07
Yeah Jev by @typesafeai is very cool. It classified 500 emails in seconds. And it costed 3.5 cents. https://t.co/4UoATmN050
295.3K views · 3.9K likes
· 98 reposts · 124 replies
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0:32
SpaceXAI engineer (ex-Cursor):
"I don’t hire people anymore. My ~20 GrokBot agents replace a SpaceXAI engineers
I mistakenly used GrokBot like a chatbot. But now Chief of Staff bot orchestrates +20 agents across 100 companies - without waiting for my next prompt."
In 30-min, h
4.8K views · 41 likes
· 5 reposts · 9 replies
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32:37
SpaceXAI just replaced a 30-person company by building +15 GrokBot agents with loops & graphs - live in 1 hour:
· 01:08 → steal first GrokBot from the SpaceXAI team
· 29:13 → scale 1 GrokBot into a team of 25+ agents
· 36:23 → Chief of Staff: delegate the delegation
· http
10.1K views · 88 likes
· 10 reposts · 8 replies
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71:51
SpaceXAI engineer, Lauren Tan:
"99% of people spend time creating new GrokBot agents. My Chief of Staff creates an army of GrokBots - I don’t prompt anymore
I built this system in ~3 days, and it already saved me weeks of work. One PM agent sets a goal for the team, one CEO htt
43.1K views · 331 likes
· 39 reposts · 13 replies
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34:18
SpaceXAI team just compressed 1 month of GrokBot learning into 3-hour course: from "What is GrokBot?" to automating your entire life 24/7:
0% → 0:35 - what is GrokBot from scratch
30% → 34:17 - first Grok Bot team with workflow from team
45% → 42:40 - run +20 GrokBots in https:
116.5K views · 924 likes
· 124 reposts · 23 replies
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154:05
@0xCodila one of the best articles on grok bot i have seen!
2.5K views · 2 likes
· 0 reposts · 1 replies
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@0xCodila great work, definitely worth checking out!
2.4K views · 2 likes
· 0 reposts · 1 replies
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@0xCodila WOW! Graph Engineering with new grok bots it's something that i really waited for
thank you, will use!
571 views · 2 likes
· 0 reposts · 0 replies
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@0xCodila 1000 loops in one window sounds impressive, but concurrency is not the hard UX problem. Legibility is. If a human cannot see ownership, dependencies and failure state, the graph is just a prettier log stream.
346 views · 2 likes
· 0 reposts · 0 replies
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@0xCodila Agent engineering was fun. Graph engineering looks like the next level. 👀
5.6K views · 3 likes
· 0 reposts · 1 replies
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@0xCodila wow man, graph engineering is hot, saving for tonight
4.8K views · 2 likes
· 0 reposts · 1 replies
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Em comparação com contas do mesmo porte
21 posts dos últimos 90 dias, ao lado da faixa de 10K–100K seguidores. aparece para muita gente, mas poucos desses espectadores reagem.
Mediana de visualizações43 059esta conta924mediana para 10K–100K
Alcance, %203.19%esta conta3.62%mediana para 10K–100K
Engajamento, %0.35%esta conta1.52%mediana para 10K–100K
| Métrica | Esta conta | Mediana para 10K–100K | Proporção |
|---|---|---|---|
| Mediana de visualizações por post | 43 059 | 924 | 46.6× |
| Alcance (visualizações ÷ seguidores) | 2.0× audience | 3.62% | 56.1× |
| Taxa de engajamento | 0.35% | 1.52% | 0.23× |
Outras contas desta faixa → Comparar com outra conta → Como estas referências são construídas →
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
2.5K19 Aug
116.5K15 Sep
43.1K16 Sep
10.1K
4.8K
295.3K17 Sep
3.2M
172.3K
3.8M
1.2M18 Sep
1.6M
9.2K
191.4K19 Sep
985
Last 14 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.
Engagement rate per post
0.12%19 Aug
0.93%15 Sep
0.89%16 Sep
1.05%
1.14%
1.40%17 Sep
0.33%
1.32%
0.32%
0.79%18 Sep
0.22%
0.07%
2.20%19 Sep
0.51%
Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.
What the audience does
Likes41.3%44 667 in total
Reposts3.2%3 422 in total
Replies1.3%1 382 in total
Quotes1.0%1 039 in total
Bookmarks53.3%57 580 in total
Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.
Followers by day
17 Sep
Daily snapshots since 17 Sep 2026; the dashed line is the starting count.
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