5 High-Quality AI Information Sources to Beat AI Anxiety

What We Really Lack Isn’t AI Information—It’s Attention Management

Open dozens of AI tool websites every day, scroll through every tech media outlet, and 90% of it ends up being repetitive press releases and marketing fluff. The truly useful, insightful content is buried in a sea of noise.

I used to fall into this anxiety trap myself: afraid of missing out on something important, subscribing to a bunch of newsletters, joining several AI info groups, spending two or three hours a day just skimming through information.

And the result? I saw a lot, remembered very little, and applied even less.

Then I realized: this isn’t learning—it’s using the act of “getting information” to relieve anxiety.

The solution is to subtract—manage your attention.

Here are 5 high-quality information sources I’ve been using, along with the logic behind how I consume information.

No.1: AI Hot—A Curated Timeline from 168 Sources

URL: aihot.virxact.com

Best for: Quickly scanning what’s happening in AI every day

This open-source news hub by Kazike isn’t valuable because it’s “complete”—it’s valuable because it’s curated.

168 sources sounds like a lot, but with AI scoring and curation, you only see what’s worth seeing. The timeline is clear, and you don’t have to jump around between different sites.

Spend 10 minutes scanning it every morning, and you’ll have a solid grasp of the major AI developments. No missing important news, and no drowning in information overload.

It also has an AI daily digest feature. If you’re really short on time, just read that.

My usage habit: I connected the curated daily digest skill to my Hermes agent. Every morning at 9:00, it pushes the digest to me, and the AI combines it with my profile and account positioning to recommend 3 topics, which are then written into my operations multi-dimensional table via Feishu CLI.

No.2: BestBlogs.dev—A Developer Blog Aggregation Platform

URL: bestblogs.dev

Best for: Finding high-quality technical insights and real-world use cases

This platform automatically fetches articles, podcasts, and videos from over 600 feeds every day, then pushes them to you with AI-powered six-dimensional scoring, summaries, and translations.

It also supports RSS. I’ve turned its curated content into a skill that integrates into my workflow and pushes content to me on a schedule. Very convenient. Instead of actively searching for information, I let the information come to me.

Why I recommend it: It filters out most marketing fluff and low-quality content. What you see are real developer experiences and thoughts—not those clickbaity “10 AI tools you must try” articles.

For someone like me who creates AI content, these real-world cases and insights are far more valuable than a list of tools.

No.3: AIGC Weekly—A Stable AI Newsletter Running for Over Three Years

URL: quaily.com/op7418

Best for: Getting a deep weekly look at core AI developments

This AI newsletter by Gui Zang has been updating consistently every week since the week ChatGPT launched—over three years and counting.

One issue per week, covering major releases, core developments, quality content, and important paper interpretations in the AI space. High information density and solid aesthetics.

Why I keep reading it: Because it does one thing for me: connects the dots from scattered pieces of information.

Each day you see isolated points. Reading AIGC Weekly each week connects those points into a line—you can see the trends and direction of the AI field. That macro perspective is something you can’t get from daily browsing.

Plus, the editor is restrained—they don’t pad the content just to fill space. Just a handful of items each week, but every one of them is worth reading.

No.4: TW93’s Personal Blog—Deep Thoughts from a Product Engineer

URL: tw93.fun

Best for: Learning how to integrate AI tools into your actual workflow

TW93 is a product engineer based in Hangzhou who has built several popular GitHub tools.

I first came across his long-form posts on Twitter, and after following him, I found his deep content extremely valuable. Not the kind of “I used tool X” diary entries, but thoughtful pieces on integrating tools into workflows and solving real problems.

I learned a lot from his tutorial on Claude Code. The layout and design of his blog also have great aesthetic taste—worth checking out.

High-quality blog content often goes deeper than the trending-topic articles on social media. The author doesn’t feel pressured by traffic to change their approach—they craft their content like a work of art, fully focused on deep vertical exploration in their domain.

Content worth revisiting is usually created for passion, not for traffic.

No.5: The Path to AGI—The Largest Open-Source AI Knowledge Base in China

URL: waytoagi.com

Best for: Finding tools, resources, and building a comprehensive understanding of the AI tool landscape

This is the largest and earliest open-source AI knowledge base in China. It started as a Feishu document and has grown into a full community website. It catalogs thousands of AI tools, categorized by use case: writing, coding, design, video—you name it, it’s there.

But its biggest value isn’t its “completeness”—it’s that it filters out tools that fade after a moment’s hype.

Tools included here have generally been vetted by the community. You don’t have to waste time testing them yourself, worrying that a tool might disappear the next day.

My usage habit: When I need a tool for a specific scenario, I go to The Path to AGI first, search for it, see what proven options exist, and then dive deeper into the specific tool.

This saves a ton of trial-and-error time.

My Information Intake Logic: Only Look at What’s Useful, Don’t Chase Trends

Now that I’ve shared these 5 sources, let me talk about the logic behind them.

Many people doing AI content on social media chase every trend, exhausting themselves and still not differentiating.

My approach is the opposite: I only chase trends related to my direction. The rest of the time, I test tools, study cases, and think more.

This logic comes from mistakes I’ve made.

When I first started creating AI content, I chased everything—OpenAI releases, Google events, every new tool launch. I’d write articles and make videos immediately.

The result? Some traffic, but all one-time. Users would read and leave—no retention, no trust, no conversion.

Then I realized: chasing trends is using the act of “producing content” to relieve anxiety—it’s not building a personal brand.

Differentiation isn’t about being faster—it’s about being deeper.

So I adjusted my strategy:

• Only chase trends relevant to my direction. My focus is AI-powered content creation and solopreneurship, so I only follow developments in that space.
• Spend the rest of the time on deep research: test tools, study cases, deconstruct hits, review data, and consolidate methodology.
• Build my own cognitive framework. Instead of telling users “here’s a new tool,” I tell them “what’s the logic behind this tool, and how you can use it.”

The result: my posting frequency slowed down, but the quality and depth of each piece went up. Users walk away with a new insight, not just a tool recommendation.

It’s not about the number of information sources—it’s about precision. These 5 are enough.

I’m Jacky, focused on AI-empowered content creation. Follow me, and let’s grow infinitely in the AI era.