New Anthropic research: Natural Language Autoencoders. Models like Claude talk in words but think in numbers. The numbersโcalled activationsโencode Claudeโs thoughts, but not in a language we can reaโฆ

LinkedIn Content Strategy & Writing Style
๐ AI & Automation Educator | n8n Ambassador | skool.com/scrapes
1 person tracking this creator on ViralBrain
Solomon Salo positions himself as a high-level architect of agentic systems, moving far beyond basic prompt engineering to focus on the structural integrity of AI automation. His content strategy centers on the transition from "chatting with AI" to building a robust Agentic OS, emphasizing technical depth through n8n workflows, terminal-based agents, and modular memory structures. What makes Solomon notable is his refusal to trade long-term maintainability for early speed; he consistently advocates for "n8n-as-code" and sophisticated observability over fragile, one-off automations. His work represents a powerful intersection of technical education and product advocacy, where he translates complex developer concepts like OpenTelemetry and semantic retrieval into actionable frameworks for builders seeking maximum leverage.
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New Anthropic research: Natural Language Autoencoders. Models like Claude talk in words but think in numbers. The numbersโcalled activationsโencode Claudeโs thoughts, but not in a language we can reaโฆ
Here's how to get the most of your Claude MD file Here are 8 hands-on insights for building Claude Code projects the right way: P.S. We've got a free Claude Code fundamentals course here: https://lnโฆ

If you like the n8n execution view, just wait until you see n8n's new traces ๐ Starting in 2.22.0, n8n natively supports OpenTelemetry for workflow and node tracing After setting just two environmeโฆ
n8n-as-code just solved a major problem for coding agents building n8n workflows. Tools like Claude Code, Antigravity and Codex, often hallucinate n8n configurations because they were never given theโฆ

Track your AI Token Usage and estimate costs in n8n Ever tried to track token usage from your AI Agents? Itโs not easy. When you connect many tools, it can get messy. Thatโs why I built this n8n temโฆ

n8n just released an Official AI Benchmark During yesterday's live session, Liam McGarrigle demonstrated the new Official n8n AI Benchmark page that he's been working on for quite some time. A benchโฆ

2.5 posts/week
Posts / Week
20
Total Posts Analyzed
MEDIUM
Posting Frequency
805.4%
Avg Engagement Rate
STABLE
Performance Trend
180
Avg Length (Words)
HIGH
Depth Level
ADVANCED
Expertise Level
0.85/10
Uniqueness Score
YES
Question Usage
0.8%
Response Rate
Writing style breakdown
<start of post>
Most people are using AI agents all wrong.
They treat them like a faster search engine. They ask a question, get an answer, and move on.
But that is not how you build a competitive advantage.
๐ง๐๐ ๐ ๐๐ฆ๐ง๐๐๐
When you use AI as a one-off tool, you lose the most important asset: Context.
Every time you start a new chat, you are starting from zero.
You have to re-explain your tech stack.
You have to re-upload your documentation.
You have to remind the AI of your coding standards.
It is exhausting. And it is inefficient.
๐ง๐๐ ๐ฆ๐ข๐๐จ๐ง๐๐ข๐ก: ๐๐๐๐ก๐ง๐๐ ๐ ๐๐ ๐ข๐ฅ๐ฌ
We just updated our Agentic OS to include a persistent memory layer.
Now, the agent remembers every decision you made last week. It knows why you chose n8n over Zapier. It knows your preferred naming conventions for Docker volumes.
This is the difference between a tool and a teammate.
We are opening up 50 spots for our implementation challenge this month.
Sign up for the $77 plan.
Build one production-ready agent in 30 days.
Get a 100% refund and keep the system forever.
We want your feedback more than your money โก
Join the builders here: https://lnkd.in/example-link
See you on the inside! Drop a "READY" in the comments if you are in ๐
<end of post>
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