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Alif Khan ✓

@Alifkhanzxx · Pennsylvania, USA · joined 03 Jul 2021

Al Enthusiast | Ghostwriter | Software Developer l Robotics Chatgpt . DM for collab ✉️ clixplixx@gmail.com

31 135Followers
11 402Following
176 597Posts total
357.6KViews on collected posts

Posts recentes

Context hygiene is the new code optimization. Stop hoarding old logs and stale tool outputs in your agent's memory. Keep it lean and watch your API bills drop. 3.8K views · 16 likes · 3 reposts · 0 replies Open on X →
Most people burn tokens. A few stretch them. Here's how to get more out of every token on OpenClaw & Hermes. https://t.co/KGgi1O43Aw 11.1K views · 25 likes · 1 reposts · 6 replies Open on X →
This is the kind of benchmark finance AI actually needs. 123 carefully selected tasks, 50+ finance professionals, 138 mapped sources and rubrics that evaluate both answers and evidence. FinFIRST isn't just measuring whether an agent can answer. It's measuring whether you can 9.3K views · 36 likes · 2 reposts · 3 replies Open on X →
Since its release, FinFIRST has drawn a lot of interest. Built with finance experts, it uses atomic rubrics to assess both answers and evidence, including how agents search, handle timely real world tasks, combine sources, choose reliable evidence, calculate and make results easy
185K views · 96 likes · 38 reposts · 48 replies Open on X →
Healthcare is one domain where AI benchmarks actually matter. Ling-3.0-flash-Sante isn't just optimized for medical knowledge. It's built around reasoning, evidence retrieval, research and safety. With only 5.1B active parameters, reaching competitive performance across major 14.9K views · 37 likes · 6 reposts · 5 replies Open on X →
The screenshot-to-website demo is seriously interesting. Give Ling-3.0-flash-VL a visual reference and it can build the page, render it, compare the output against the reference and improve the code. That's a very different coding loop: show the AI what “good” looks like, then 24.5K views · 79 likes · 6 reposts · 2 replies Open on X →
A senior Google engineer just dropped a 421-page doc called Agentic Design Patterns. Every chapter is code-backed and covers the frontier of AI systems: → Prompt chaining, routing, memory → MCP & multi-agent coordination → Guardrails, reasoning, planning This isn’t a blog http
109K views · 296 likes · 73 reposts · 39 replies Open on X →

Em comparação com contas do mesmo porte

6 posts dos últimos 90 dias, ao lado da faixa de 10K–100K seguidores. aparece para muita gente, mas poucos desses espectadores reagem.

Mediana de visualizações13 006esta conta924mediana para 10K–100K
Alcance, %41.77%esta conta3.62%mediana para 10K–100K
Engajamento, %0.40%esta conta1.52%mediana para 10K–100K
MétricaEsta contaMediana para 10K–100KProporção
Mediana de visualizações por post13 00692414.1×
Alcance (visualizações ÷ seguidores)41.77%3.62%11.5×
Taxa de engajamento0.40%1.52%0.26×

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

109K13 Jun
24.5K4 Sep
14.9K5 Sep
185K
9.3K
11.1K7 Sep
3.8K

Last 7 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.38%13 Jun
0.36%4 Sep
0.32%5 Sep
0.10%
0.44%
0.47%7 Sep
0.50%

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

What the audience does

Likes44.1%585 in total
Reposts9.7%129 in total
Replies7.8%103 in total
Quotes2.5%33 in total
Bookmarks35.9%477 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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