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Lisan al Gaib

@scaling01

lead them to paradise LisanBench: Impressum & Datenschutz:

  • Posts in English
scaling01.profile
Lisan al Gaib
LLMs
Followers
62,788
Median views / post
13,797
Engagement / views
1.86%
Own posts in sample
12

Observed 27 Oct 2026 · Saved sample, up to 20 own posts.

Ways to collaborate

Give your launch
a familiar voice.

Start with a Boost. Choose the formats that fit your product and budget.

quote.exe

Quote post

Your launch, with their perspective.

€280per collaboration
Plan a quote
post.exe

Original post

A new post built around your brief.

€390per collaboration
Plan a post
repost.exe

Repost

Your original post, shared further.

€120per collaboration
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comment.exe

Comment

Add a voice to the conversation.

€85per collaboration
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Chals Channel rates in EUR, before taxes. The platform fee is added to the creator budget according to your plan. See plans ↗

Behind the profile

Get to know the work.

Lisan al Gaib publishes in English about LLMs.

Use the topics and the recorded sample to compare this profile with the rest of your shortlist. Match the creator to your product, then build the campaign in your assistant.

How to read these numbers

These are saved observations from up to 20 own posts, not live measurements or a complete calendar period. Median views describe the sample, not promised campaign reach. Engagement is measured against views. A creator’s location does not establish the location of their audience.

a_post_from_the_sample.exe

An example of their content

Anthropic spending commitments are crazy…

101,460 recorded views

Read the original on X ↗

A practical launch guide

Reasoning benchmark interpretation: the @scaling01 comparison

For reasoning benchmark interpretation, use Claude with Chals Channel to compare @scaling01 against profiles with related work. The profile references benchmarking, while the sample discusses spending commitments. Evaluate a relevant launch through benchmark design and transparent scoring. The comparison below uses saved catalog observations and rates; it does not establish current activity, audience demographics or a creator agreement.

How does @scaling01 relate to reasoning benchmark interpretation?

The saved catalog associates this profile with LLMs. The profile references benchmarking, while the sample discusses spending commitments. Evaluate a relevant launch through benchmark design and transparent scoring.

State task coverage, scoring rules and the benchmark's known blind spots. Check the linked original example and the profile bio for context. A prominent personal or unrelated post should not be treated as evidence about a technical product or buyer demand.

What should Claude or ChatGPT compare?

The observation dated 2026-10-27 records 62,788 followers, 13,797 median views per sampled post and 12 own posts. Followers describe account size; the median describes this saved sample. Neither measures unique campaign reach or predicts your launch results.

@osanseviero is catalogued with LLMs; its saved sample has 13,811 median views across 20 own posts, observed 2026-10-21. @TheAhmadOsman is catalogued with Open source, LLMs; its saved sample has 13,594 median views across 19 own posts, observed 2026-10-27. Compare the linked work and the product explanation before preferring a larger figure. Different observation dates and samples are not a controlled campaign comparison.

What do the saved format rates mean for a launch?

The saved quote-post rate for @scaling01 is €280. In an illustrative €1,000 creator budget, one quote uses 28% and leaves €720. A quote plus one comment from this profile would use €365 of creator spend. These are arithmetic examples using the listed formats, before account-specific platform fees and tax; they are not reach forecasts or confirmed creator participation.

Start with Boost when your brand owns the main launch post: a quote adds a perspective, a comment adds discussion and a repost reshares the original. Use a sponsored original when the explanation needs its own post. Research and planning are free; review the actual booking on the Chals Channel website.

How can I prepare a brief for reasoning benchmark interpretation?

State task coverage, scoring rules and the benchmark's known blind spots. Give the assistant the product, intended user, launch date, time zone and creator-spend ceiling. Ask what evidence is still missing before it recommends a shortlist.

Keep the observed profile data separate from the proposed demonstration. The saved sample is not live analytics, a creator location is not audience geography, and a public listing does not establish availability or endorsement.

Try this in your assistant

Use Chals Channel to compare X creators for reasoning benchmark interpretation with Claude. My product is [product], used by [intended user] for [task]. Compare @scaling01 with @osanseviero and @TheAhmadOsman. For the brief: State task coverage, scoring rules and the benchmark's known blind spots. Explain the fit and exclusion reasons, show observation dates and sample sizes, and compare listed format rates. Ask for my budget and launch date. Propose Boost first and keep booking for my review on the website.

By Chals Channel · Editorial updated . Profile observations: 27 Oct 2026. How campaigns work ↗

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Review and confirm any booking on the Chals Channel website.