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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

Neueste Beiträge

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 →

Im Vergleich zu Konten gleicher Größe

6 Beiträge aus den letzten 90 Tagen, verglichen mit der Größenklasse 10K–100K Follower. wird weit gezeigt, aber nur wenige dieser Zuschauer reagieren.

Medianaufrufe13 006dieses Konto924Median für 10K–100K
Reichweite, %41.77%dieses Konto3.62%Median für 10K–100K
Interaktion, %0.40%dieses Konto1.52%Median für 10K–100K
KennzahlDieses KontoMedian für 10K–100KVerhältnis
Medianaufrufe pro Beitrag13 00692414.1×
Reichweite (Aufrufe ÷ Follower)41.77%3.62%11.5×
Interaktionsrate0.40%1.52%0.26×

Weitere Konten dieser Größe →   Mit einem anderen Konto vergleichen →   Wie diese Vergleichswerte entstehen →

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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