How an AI Curator Keeps Me Sharp on AI Research Every Morning

I took a week off in January. When I came back, there was a new reasoning model, two open-source releases that changed the agent framework landscape, and a paper that invalidated an approach I'd been planning to implement. I found out about all of it from a coworker's Slack message that said "did you see this?"

If you work in AI or adjacent fields, you already know the feeling. The field moves so fast that missing a single week can leave you genuinely behind.

Why is keeping up with AI research so exhausting?#

The volume is the problem. Arxiv publishes roughly 500 AI-related papers per week. Hacker News surfaces maybe 30 relevant discussions a day. There are 20+ newsletters you could subscribe to, each giving you "the top 10 AI stories this week." Twitter has real-time takes but also an enormous amount of noise.

So what do most people do? They either spend an hour every morning doom-scrolling HN and Twitter, getting distracted by things that aren't relevant. Or they subscribe to 5 newsletters, fall behind on reading them, and end up with 47 unread emails from The Batch and Import AI.

I tried the manual approach for months. My system was: check HN before breakfast, skim arxiv abstracts during lunch, read Twitter during coffee breaks. It sort of worked, but it consumed mental energy I needed for actual building. And I still missed things. I'd find out about a major release 4 days late because it happened on a day I was deep in a debugging session.

The real issue isn't access to information. It's filtering. You need someone or something to read everything and tell you the 3-5 things that actually matter for what you're working on. That's curation, and it's exactly what an AI agent is good at.

What does an AI learning curator agent do?#

The agent runs in Telegram and acts like a research assistant who reads everything so you don't have to.

Daily morning digest. Every day at 8am, you get a message with 3-5 curated links. Each one includes the title, source, a 2-sentence summary, and why it's relevant to your specific interests. Not "this paper is interesting." More like "This paper proposes a new approach to tool-use in agents that's directly relevant to the skill system you're building."

Here's what a real digest looks like:

🔬 AI Digest — Feb 24

1. "ReAct-2: Grounded Reasoning with Verifiable Actions"
   arxiv — Published yesterday
   Extends ReAct with action verification. Relevant because
   you're building agent workflows with tool validation.

2. "Anthropic releases Claude Opus 4.6"
   HN #3 — 847 points
   New model with improved agentic capabilities.
   Directly affects your LiteLLM routing config.

3. "Why RAG is dying and what's replacing it"
   Simon Willison's blog
   Argues for hybrid retrieval. Challenges assumptions
   in your knowledge base implementation.

Weekly deep-dive. On Sundays, the agent picks the most significant paper or development of the week and gives you a proper breakdown. Not just a summary but context: what it means, how it relates to your work, what you should consider changing.

Interest profile that evolves. When you first set up the agent, it asks what you care about. AI agents, distributed systems, LLM infrastructure, whatever. But it doesn't stop there. As you interact with the digests, marking things as useful or not relevant, it sharpens its filter. After two weeks, it stops surfacing things about computer vision because you never clicked those links. It surfaces more about agent orchestration because that's what you engage with.

Spaced repetition for key concepts. This is the part I didn't expect to love. The agent periodically quizzes you on concepts from papers you've read. "Explain the difference between RAG and fine-tuning in 3 sentences." "What's chain-of-thought prompting and when does it fail?" It's a gentle way to make sure you actually retain what you read instead of just skimming headlines.

Learning goals with tracking. You can set goals like "Read 2 papers per week on agent orchestration." The agent tracks your progress and nudges you. "You're 1 paper behind this week. Here's one that takes 15 minutes to read."

Everything feeds into your knowledge base. Every paper summary, every digest, every quiz response gets stored. Three months in, you can ask "What do I know about RLHF?" and get a synthesized answer drawing from everything you've consumed. It's like building a personal research library without the effort of maintaining one.

How do you set up an AI learning curator?#

RapidClaw has a Learning Curator template. Select it, connect Telegram, and configure your interests. The whole thing takes about 60 seconds.

During onboarding, the agent asks a few questions: What topics matter most? Which sources do you trust? What time do you want your daily digest? Do you want quizzes?

The agent starts curating from day one. The first few digests might include things that aren't perfectly targeted, but within a week it's dialed in based on your feedback. Just react to the messages, "useful" or "not relevant," and the filter tightens fast.

No APIs to configure. No RSS feeds to manage. The agent handles all the source monitoring internally, crawling arxiv, HN, key technical blogs, and AI Twitter.

Who is this for?#

Engineers and researchers who need to stay current but don't have hours to spend scrolling. ML engineers tracking new model releases and training techniques. Backend developers watching how AI tools affect their stack. Technical leads who need to make informed decisions about which AI capabilities to adopt.

It's also great for people preparing for interviews at AI companies. If you're targeting Anthropic, OpenAI, or similar, you need to be fluent in recent developments. The curator makes sure you don't walk into an interview not knowing about a paper published last week.

If you're already running a newsletter or curating for others, this helps too. Let the agent do the initial filtering, then you add your own analysis.

How much does an AI learning curator cost?#

Manual curation services like Readwise or specialized newsletter subscriptions can run $5-20/month each, and you'd need several to cover different sources. Hiring a research assistant for daily curation would cost $500+/month.

RapidClaw starts at $19/month and the Learning Curator template is included. AI credits for the daily crawling and summarization are built into the plan. One agent, all sources, personalized to you.

Frequently Asked Questions#

What sources does the agent monitor?#

Arxiv (cs.AI, cs.CL, cs.LG, and related categories), Hacker News, major technical blogs (Simon Willison, Lilian Weng, The Gradient, etc.), AI Twitter/X accounts, and company engineering blogs from Anthropic, OpenAI, Google DeepMind, Meta AI, and others. You can add custom sources during setup or anytime via Telegram.

Can I customize the digest for a non-AI field?#

Yes. The interest profile is fully customizable. While the template is optimized for AI/ML, you can configure it for any technical domain: cloud infrastructure, security, web development, blockchain, whatever. The agent just needs to know what topics and sources to monitor.

How is this different from just subscribing to newsletters?#

Newsletters are one-size-fits-all. Everyone gets the same 10 links. The agent curates specifically for your interests and what you're working on. It also does spaced repetition, tracks your learning goals, and builds a searchable knowledge base from everything you consume. Newsletters can't do any of that.

Does the agent read full papers or just abstracts?#

For the daily digest, it reads abstracts and key sections (intro, conclusion, results). For the weekly deep-dive, it reads the full paper. When you ask it to go deeper on something, it reads the entire document. The summarization is done by AI, so the quality of understanding is high, but it always links to the original so you can read the full thing yourself.

What if I'm overwhelmed by even 3-5 links per day?#

You can dial it down. Set the digest to 2 links per day, or switch to a weekly digest instead of daily. The agent adapts to your pace. Some users only check the weekly deep-dive and skip the dailies entirely. It's your learning system; configure it however works for you.