Charles Chen

[Peter Yang @petergyang]

Take one hour tonight to follow my Hermes tutorial below to install the app, set up your Telegram bot, enable voice, connect Google Workspace, and create a few routines.

I made it super beginner friendly and walked through all the steps live in 45 min. You won't regret it.

📌 Watch here: https://t.co/RPAtyPKGQS

[Ridark @ridark_eth]

I genuinely don't understand why everyone isn't using this yet

Andrej Karpathy, a co-founder of OpenAI, posted a simple idea that hit 16 million views: stop using AI to write code, use it to build a second brain.

You point Claude Code at a folder, drop in any source, an article, a transcript, a PDF, and Claude reads it, links it, and files it into a living wiki of everything you know. It compounds like interest, the more you feed it, the smarter it gets.

Here's the whole thing:

> Install Obsidian, create a vault, open it in Claude Code

> Paste Karpathy's wiki idea file and tell Claude to build it

> Claude makes three folders: raw for sources, wiki for its pages, a CLAUDE.md that runs it

> Drop any source into raw and say "ingest this"

> Ask questions across everything, forever

Five minutes to set up, and you never start from a blank chat again.

Full step-by-step guide with Claude and Obsidian, link below.

Bookmark this

[Kun Chen @kunchenguid]

many people asked me to make a video about my complete agentic engineering workflow

excited to share it's finally here!!!

it took me about 20 hours in total to record this 45 minutes of walkthrough - it covers everything i do to ship production quality code at an average 40+ PRs/day velocity

hope this can be a useful reference to everyone exploring good ways to use AI. and would appreciate a reshare with anyone you think might benefit from this!

enjoy! https://t.co/oA0UCrBvqo

[Avid @Av1dlive]

Garry Tan (CEO of Y-Combinator): "when someone asks how I 'prompt' my AI, the answer is: I don't. the skills are the prompts."

[if I had this weekend to master skills and how to use them to automate workflows:]

→ read the Skillify 11-item checklist (SKILL.md in gbrain)
→ watch Murag + Barry Zhang: "Don't Build Agents. Build Skills Instead."
→ Read "Designing, Refining, and Maintaining Agent Skills at Perplexity"
→ do one workflow. type /skillify. watch it become permanent. that's the whole day.

here is how to set it up:
1. clone GBrain (his open-source second brain, Postgres-backed memory + 30 skills)
2. add GStack (23 battle-tested slash-command skills, drops right in)
3. do anything once → type /skillify → it's a skill forever

prompting is dead. skillifying is next.

[Peter Yang @petergyang]

How to build AI skills that check their own work and improve over time:

1. Give it context

Ask AI: "Create a skill for this [repeated task]. Here are examples of good output so it knows what good looks like."

2. Make it easy to trigger

“Write a clear skill description using this pattern: Use when the user wants to [do this].”

3. Add evals

"Create an evals md with 10 pass/fail checks for common errors in the skill's output."

4. Add memory

"Create a memory md to capture one-sentence learnings from past chats using this skill."

5. Build a skill to edit skills

"Create a skill that cleans up other skills by removing duplicate or stale instructions, vague rules, and AI slop."

📌 Watch my full walkthrough here: https://t.co/u434ytNSZd

[Lenny Rachitsky @lennysan]

Today I'm releasing my entire newsletter archive (350+ posts) and all podcast transcripts (300+ episodes) as AI-friendly Markdown files. Plus an MCP server and GitHub repo.

A few months ago I shared my podcast transcripts on a whim, and y'all built the most amazing things—an RPG game, a parenting wisdom site, infographics, a Twitter bot, and 50+ other projects.

Let's see what happens when I give you even more data.

Grab the data here: https://t.co/xEPCcPiZHO.

Paid subscribers get all of the data (some 350 posts and 300 transcripts). Free subscribers get a subset.

I don’t think anyone’s ever done anything like this before, and I’m excited to give you this excuse to play with that AI tool you've been meaning to try.

Here’s my challenge to you: build something, and let me know about it. I’ll pick my favorite and give you a free 1-year subscription to the newsletter. Just post a link to your project in the comments here: https://t.co/yJDmuCQfOx.

If you’ve already built something, slurp in this new data and submit it, too. I’ll pick a winner on April 15th.

Check out today's newsletter post for inspiration on what you could to build: https://t.co/yJDmuCQfOx

LFG.

[Om Patel @om_patel5]

THIS GUY JUST GAVE CLAUDE CODE THE ABILITY TO WATCH VIDEOS

claude code can't natively see video or hear audio

which means every time you want it to "look at this video" you have to screenshot frames manually and transcribe the audio yourself

so this guy built a plugin that does the whole perception layer for you

> extracts frames with adaptive fps based on your question (claude picks the rate automatically, denser frames for "what happens right before the crash" vs "summarize this talk")
> runs audio through gemini, local whisper, or openai whisper for transcription with timestamps
> feeds the frames and transcript to claude as one combined input so it reasons about them together

you just drop a .mov in and ask questions

the install takes 3 commands inside claude code AND it's fully open source, no paywall or account needed

claude code just got eyes and ears

[wincy.eth @gusik4ever]

the fastest growing GitHub repos in finance this week:

1. shiyu-coder/Kronos (+6.5K ★)

first open-source foundation model for financial candlesticks. trained on 45+ global exchanges. predicts OHLCV candles as tokens — literally GPT for price charts. accepted at AAAI 2026.

2. virattt/ai-hedge-fund (+4.9K ★)

a team of AI agents simulating Buffett, Munger, Ackman, Cathie Wood and others. each agent runs its own strategy, a Portfolio Manager makes the final call. one of the most viral finance repos right now.

3. TauricResearch/TradingAgents (+~3K ★)

multi-agent LLM trading framework. fundamental analyst, sentiment analyst, technicals, risk manager — all working together. supports GPT-5.x, Gemini 3.x, Claude 4.x, Grok. built by UCLA/MIT researchers.

4. ZhuLinsen/daily_stock_analysis (+~2K ★)

LLM stock analyzer for US, A-share and H-share markets. auto-builds a daily decision dashboard with exact entry/exit levels. pushes to WeChat/Telegram/Discord/Email via GitHub Actions. zero cost, zero server.

5. hsliuping/TradingAgents-CN (+~1.5K ★)

Chinese fork of TradingAgents. fully localized for A-share markets (Shanghai/Shenzhen), Chinese data sources, and domestic LLMs. 5.1K forks — very active community.

6. OpenBB-finance/OpenBB (+~1K ★)

open-source Bloomberg alternative. stocks, crypto, options, derivatives, fixed income — one platform. integrates with AI agents via MCP. 66K total stars and still climbing.

7. freqtrade/freqtrade (+~700 ★)

free, open-source crypto trading bot in Python. supports all major exchanges, full backtesting, strategy optimization, Telegram control. release 2026.3 just dropped.

8. AI4Finance-Foundation/FinGPT (+~500 ★)

open-source financial LLMs trained on real market data — news, filings, earnings. built for sentiment analysis and robo-advisors. models on HuggingFace, ready to deploy.

9. juspay/hyperswitch (+~400 ★)

open-source payments router in Rust. one API to connect Stripe, Adyen, PayPal and 50+ providers. smart routing, high performance, built for fintech scale.

10. microsoft/qlib (+~350 ★)

Microsoft's AI quant investment platform. covers the full pipeline: alpha seeking, backtesting, model training, live trading. supports ML/DL, RL, and auto-quant.

bookmark this and start today.

[wincy.eth @gusik4ever]

the fastest growing GitHub repos in finance this week:

1. mvanhorn/last30days-skill (+2.1K ★)

AI agent skill that searches Reddit, X, YouTube, HN, Polymarket and the web in parallel — then scores results by upvotes, likes, and real money, not editors. drop it into Claude Code or OpenClaw. zero config to start.

2. ZhuLinsen/daily_stock_analysis (+1.2K ★)

LLM-powered stock analyzer for US, A-share and H-share markets. real-time news + multi-source data + decision dashboard with exact buy/stop/target levels. runs on GitHub Actions on a schedule at zero cost. pure automation.

3. juspay/hyperswitch (+667 ★)

open-source payments infrastructure written in Rust. modular by design — pick only what you need: routing, retries, vaulting, reconciliation, cost observability. built by the team behind payment infrastructure for 400+ enterprises. the "Linux for payments"

4. HKUDS/AI-Trader (+655 ★)

agent-native trading platform where AI agents join, share signals, debate ideas, and copy each other's trades. send one message to any agent and it registers itself. supports OpenClaw, Claude Code, Codex, Cursor and more.

5. hsliuping/TradingAgents-CN (+471 ★)

Chinese-enhanced fork of TradingAgents. same multi-agent LLM trading architecture, fully localized for Chinese markets, A-share data, and domestic LLMs like DeepSeek and Qwen. 23K stars and climbing.

6. ashishpatel26/500-AI-Agents-Projects (+436 ★)

curated collection of 500+ AI agent use cases across healthcare, finance, education, retail and more. organized by industry and framework — CrewAI, AutoGen, LangGraph, Agno. the best reference list if you're figuring out what to build next.

7. OpenBB-finance/OpenBB (+355 ★)

open-source financial data platform for quants, analysts and AI agents. "connect once, consume everywhere" – same data layer exposes to Python, Excel, MCP servers for agents, and REST APIs. the open-source Bloomberg alternative.

8. microsoft/qlib (+349 ★)

AI-oriented quant investment platform from Microsoft. covers the full pipeline from data to live trading: alpha seeking, risk modeling, portfolio optimization, order execution. deep learning, RL, auto-quant – all in one place.

9. tradingview/lightweight-charts (+318 ★)

one of the smallest and fastest financial chart libraries for the browser. built with HTML5 canvas, weighs almost nothing, renders like native. if you're building any kind of trading UI on the web, this is what you reach for first.

bookmark this and start today.

[Ramya Chinnadurai 🚀 @code_rams]

Every human capability is now an API for AI agents.

Email: AgentMail
WhatsApp: Kapso
Phone: Vapi
Voice: ElevenLabs
Browser: Browserbase, Browser Use, Steel
Web crawl: Firecrawl
Search: Exa
Computer: E2B, Daytona
Memory: Mem0, Zep, Letta, Honcho, Supermemory
SaaS tools: Composio, Nango
Knowledge: Ragie
Social media: monid. ai
Observability: AgentOps, Langfuse, Portkey
Vector DB: Pinecone, Qdrant, ChromaDB

The full stack to give an agent its own email, phone, browser, memory, and tools now exists.

The infra layer is ready. The question is who builds the best agents on top.

No hype, just facts.

[Kevin Gu @kevingu]

https://t.co/DBaiIhnhLQ

[Ihtesham Ali @ihteshamali]

🚨 Holy shit...A developer on GitHub just built a full development methodology for AI coding agents and it has 40.9K stars on GitHub.

It's called Superpowers, and it completely changes how your AI agent writes code.

Right now, most people fire up Claude Code or Codex and just… let it go. The agent guesses what you want, writes code before understanding the problem, skips tests, and produces spaghetti you have to babysit.

Superpowers fixes all of that.

Here's what happens when you install it:

→ Before writing a single line, the agent stops and brainstorms with you. It asks what you're actually trying to build, refines the spec through questions, and shows it to you in chunks short enough to read.

→ Once you approve the design, it creates an implementation plan so detailed that "an enthusiastic junior engineer with poor taste and no judgement" could follow it.

→ Then it launches subagent-driven development. Fresh subagents per task. Two-stage code review after each one (spec compliance, then code quality). The agent can run autonomously for hours without deviating from your plan.

→ It enforces true test-driven development. Write failing test → watch it fail → write minimal code → watch it pass → commit. It literally deletes code written before tests.

→ When tasks are done, it verifies everything, presents options (merge, PR, keep, discard), and cleans up.

The philosophy is brutal: systematic over ad-hoc. Evidence over claims. Complexity reduction. Verify before declaring success.

Works with Claude Code (plugin install), Codex, and OpenCode.

This isn't a prompt template. It's an entire operating system for how AI agents should build software.

100% Opensource. MIT License.

[Garry Tan @garrytan]

I've been having such an amazing time with Claude Code I wanted you to be able to have my *exact* skill setup:

Introducing gstack, which you can install just by pasting a short piece of text into your Claude code

[Olivia Moore @omooretweets]

🚨 The @a16z consumer AI Top 100 is back!

For the sixth time, we ranked consumer AI websites and mobile apps by usage (monthly unique visits and MAUs).

This edition, we changed the rules. Here's why - and what the new list says about where consumer AI is heading 👇

[Rimsha Bhardwaj @heyrimsha]

I accidentally discovered how to compress a month of research into 3 hours.

A founder at a YC company showed me his Claude setup. I thought he was just fast. Then I watched him build an entire go-to-market strategy for a market he'd never worked in before.

Here's exactly what he did:

First: he didn't ask Claude to "research the market."

He fed it 8 competitor landing pages, 3 earnings call transcripts, 12 customer reviews, and a Reddit thread of complaints.

Then he asked one question:

"What does every successful player in this market understand that their customers never say out loud?"

Not "summarize these." Not "analyze the competition."
The unspoken insight. The thing that takes founders 2 years of customer calls to figure out.

But the next part is what broke my brain.

He followed up with:

"Now show me the 3 assumptions this entire market is built on, and what would have to be true for each one to be wrong."

In 15 minutes he had the attack surface of an entire industry.
The blind spots. The fragile consensus. The opening nobody was talking about.

Most founders spend 6 months doing customer discovery just to find one of those.

Then he did something I've never seen before.

He asked:

"Write 5 questions a world-class investor would ask to destroy this business idea, then answer each one using only the evidence in these documents."

He spent the next 2 hours stress-testing every assumption. Every weak answer triggered a follow-up:

"What's the strongest version of this argument and where does it still break?"

By hour 3, he had a strategy deck that felt like it came from someone who'd spent a decade in the space.

The tool didn't change. The questions did.

Most people treat Claude like a faster Google.

These founders are using it like a thinking partner who has read everything and has no ego about being wrong.

The difference between 3 hours and 3 months isn't the amount of information.

It's knowing which questions actually matter.

[Ejaaz @cryptopunk7213]

wow Anthropic just published a crazy report on AI replacing your job and er... you might want to look at this:

- #1 most at-risk jobs are computer programmers, financial analysts (rip excel bros) and customer service

- most at-risk workers are female, white, older and higher paid.

- BUT high-risk jobs *aren't* firing employees... they've STOPPED HIRING. biggest victims: college graduates (4X more likely to be fucked)

- entry-level hiring has dropped 14% since chatgpt launched (for highest risk jobs)

- SAFEST jobs are... bartenders, dishwashers and lifeguards - any manual labour that AI can't automate (yet) this accounts for 30% of the job market.

- this was the scariest part: AI models are capable of automating most work TODAY but are prevented because of law and slow company adoption. so its not even a fucking skill issue its an ADOPTION issue.

- now its important to understand that the study is based on real world data but also 'theoretical' intelligence. so take it with a pinch of salt. some jobs (manual labor) didn't even meet min. data reqs

i applaud anthropic on being so damn transparent - they're literally the company behind claude who will be responsible for these impacts

studies like this will help us figure it the hell out. LOT of change coming this year.

[Alex Veremeyenko @alex_verem]

This is AMAZING.. someone just built an App Store for Claude Code.

It's called SkillsMP and there are 200,000+ agent skills that teach your AI exactly how to write PPTX files, review PRs, deploy to cloud, analyze data, and more.

100% Opensource.

(Link is in the comments)

[Ramya Chinnadurai 🚀 @code_rams]

https://t.co/ey663Xlmt7

[Sahil @sahill_og]

- Claude for coding.
- Supabase for backend.
- Vercel for deploying.
- Namecheap for domain.
- Stripe for payments.
- GitHub for version control.
- Resend for emails.
- Clerk for auth.
- Cloudflare for DNS.
- PostHog for analytics.
- Sentry for error tracking.
- Upstash for Redis.
- Pinecone for vector DB.

You can literally ship a startup from your bedroom now.

It’s not that deep bro.

[Cathryn @cathrynlavery]

https://t.co/chkzFELSmG