Exp10rer

Explorer forever

[Andrew Ng @AndrewYNg]

Fifteen years ago, @Coursera and online courses changed education. It worked better than almost anyone expected, expanding access by opening up where you can learn. But how you learn remains largely the same as it has for centuries: it is still one-size-fits-all, taught the same way to each person who shows up.

We now have an opportunity to change how learning happens. With advances in AI, we can now build a custom learning guide for each person. We will turn learning from one‑to‑many to one‑to‑one. I'm starting LearnVector to invent this next generation of learning. We are starting with a $100M investment from Coursera, and plan to collaborate closely with Coursera and Udemy.

Good learning needs much more than just a chatbot. Research shows that chatbots without guardrails harm learning. They help complete tasks and enable students to do better on homework. But cognitive offloading to a chatbot results in them being less skilled. And, you cannot always trust what a chatbot tells you.

In contrast, LearnVector will plan a path with you, adapt to how you learn, and patiently stay with you until you’ve mastered new skills.

One thing has not changed in all this time. People want learning they can trust: material that is accurate, relevant, and worth the effort you put into it. Anything less wastes the most valuable thing a learner has: time. Coursera has a trusted library of materials from authoritative sources. LearnVector plans to work with Coursera to bring this trustworthy learning to everyone. I'm grateful to Greg Hart and the entire Coursera team for supporting LearnVector.

I look forward to working with our talented team to change how we learn, and accelerate human development.

https://t.co/TqFUDFd1hb

[Thariq @trq212]

We removed ~80% of the Claude Code system prompt for our newest models, this is what we've learned about writing system prompts, skills and Claude.MDs for them. https://t.co/6DZwSrZjE9

[Codez @0xCodez]

IBM just released a 1-hour course on building agentic knowledge graphs from scratch:

• 00:00 - Introduction to knowledge graphs
• 05:35 - Building your first agentic graph
• 19:59 - Agentic memory powered by graphs
• 30:39 - Graphs for multi-agent orchestration

This 1-hour watch will replace 10 paid courses on agentic engineering.

Watch it today, then learn how to become a knowledge graph engineer in the article below.

[Anatoli Kopadze @AnatoliKopadze]

https://t.co/fyBGWQbsvn

[codila @0xCodila]

https://t.co/Kg6X4rXvpc

[Andrew Ng @AndrewYNg]

Announcing OpenWorker! An open-source agent that doesn't just chat with you, but delivers finished work -- like hand you a polished document, send a slack message, or update a calendar entry.

Ask it to prepare a customer brief, untangle your calendar, draft a report, or triage a Slack alert. It works across your files and everyday tools, produces the deliverable, and checks in before doing anything consequential.

OpenWorker runs on your Mac, with Windows support coming soon. It does not lock you into any one model. Bring your own API key and run it with GPT 5.6 Sol, Claude Fable, Gemini 3.6, an open weight model (like Kimi, GLM, DeepSeek, Inkling), or Ollama to keep your data local. Your data does not leave your machine except through an LLM provider and integrations that you choose.

@rohitcprasad and I are building OpenWorker because AI coworkers are an important way to get work done, and we want there to be an open, privacy-preserving, model-independent option. Check it out and let us know what you think!

Try it out: https://t.co/P0mGnI1o31 (requires your own API key)
Source code: https://t.co/NYCiTD6hSq

[ai maxxer @agentsmaxxing]

This guy makes complex agent concepts surprisingly easy to understand.

If you're serious about agentic engineering,

Bookmark this.

[Rahul @sairahul1]

This is nuts.

Mark Cuban just said something every young person should hear.

AI agents are going to run through every small and mid-size business in the country.

Not a single one of those owners will know how to build them.

His advice: learn Claude. Learn agentic workflows. Just learn AI and how it works.

Then go to these businesses and help them — because they won't know how to do any of this.

They have money to spend. They have deep problems.

They don't have you.

But first you need to know how to build agents.

This is the complete course ↓

Bookmark this. This is the opportunity.

[Movez @0xMovez]

Andrew Ng:

“Agents are the most important trend in AI right now - 100% of my tasks already done by agents.

in 3-6 months, we’ll all be building Graphs to orchestrate self-improving agents. No more prompting.”

in a 20-minute talk, Andrew Ng explains how to build self-improving agentic systems from scratch.

Worth more than a $500 agentic course.

Watch this talk, then read how to become an agent orchestrator with graph engineering below.

[Roan @RohOnChain]

My friend applied to 250 tech jobs in two years. No MIT. No Stanford.

Last month Anthropic offered him $750,000.

I asked him how he broke in from zero.

He sent me the exact video that got him in. Anthropic's 2-hour course on how to become an AI engineer in 2026.

Thariq Shihipar shows you exactly how to build AI agents from scratch.

I watched it last night.

Halfway through, I realized I could break into an AI lab in months, not years.

Bookmark this and read the article below.

• 00:00 - AI agent harness
• 23:44 - building AI agent loops
• 56:39 - AI agent context engineering
• 1:33:34 - AI agent deterministic hooks
• 1:50:31 - Anthropic SWE interview process

[Movez @0xMovez]

Andrew Ng:

“AI agents are doing almost 100% of my tasks now - the hype has exceeded my expectations.

in 4-6 months, we’ll all be building graphs to orchestrate self-improving agents. No more prompting.”

In a 20-minute talk, Andrew Ng explains how to build self-improving agentic systems from scratch.

Worth more than a $500 agentic course.

Watch this video, then read the article below on how to become a graph architect.

[Reads with Ravi @readswithravi]

“You escape competition through authenticity.”

— Naval Ravikant

[流氓兔🐰 @LiumangtuCrypto]

建议兄弟们都去看这部Netflix高分纪录片

《聪明生活经济学》

看完彻底刷新金钱认知。

[Granite @Granite0x]

Met a guy making $1.1 million a year as an agents engineer at Google Cloud.

Asked him how he gets agents 20x better without changing the model.

He sent me the exact thing he uses himself. A repo he open-sourced 2 days ago.

You won't find anything better about harness engineering, in the open.

Cloned it and pointed my agent at it last night.

Ryan Lopopolo. Google Cloud engineer.

'harness-engineering' - anthology + field guide + agent context bundle. You reference his docs from your CLAUDE.md.

633 stars. 48 hours old. MIT.

-> https://t.co/AOykHplNNX

bookmark this before it gets lost.

[GREG ISENBERG @gregisenberg]

So let me get this straight....

1. Agents are about to outnumber humans on the internet, so most of the traffic, transactions, and conversations online will soon be machines talking to other machines while we sleep.

2. Superintelligence exists now, and for $20/mo you pretty much get it all.

3. Cloud agents allow you to run a business 24/7 and from literally a phone while you're waiting to order a latte.

4. Voice AI is wide open. This industry has barely changed since the 90s. Infinite opportunities. Voice AI is finally getting good enough.

5. Mobile apps are interesting again for the first time in 10 years, because an AI-first app that thinks and acts on its own is a different species than the passive ones in the store today. There are kids doing $100k/MRR.

6. It's the golden age of open source. The models you download off Hugging Face for free and own forever are landing within months of the ones behind paywalls, so the smartest thing on earth can't be throttled, priced up, or shut off by a company having a bad quarter.

7. The keyboard is on its way out. We spent 40 years learning to type fast, and it's about to feel like handwriting, because soon you just talk and the computer goes and does it.

8. Every company is about to hire agents with their own logins, their own inboxes, their own track records, and a shadow economy is forming where agents pay, hire, and vouch for other agents.

9. Software stopped being something you buy and became something you rent by the hour. The whole industry is repricing from $50 a seat to thousands per outcome. Tons of opportunity.

10. Robots are about to have the moment software agents just had. The intelligence got solved. Now it's dropping into machines with arms and legs, and the people who can wire AI into hardware are about to be the most fought-over hires on earth.

11. The 10-person startup can now out-ship the 500-person company, and everyone can feel it happening.

12. Every white-collar task is getting a "do it for me" button, and most people haven't pressed it yet.

13. Data you've been sitting on for years is suddenly worth something, because now an agent can actually use it.

14. Language stopped being a barrier. Real-time translation that actually works means the next huge consumer app might get built for a market you can't even read, by someone you'll never meet.

15. Every SOP is turning into a product. The way a business does one thing, written down as a markdown file an agent can run, is now something you can sell. Knowledge that used to live in someone's head became downloadable.

16. The moat moved from what you know to how well your business is written down. The company an agent can actually run wins, so being legible beats being big.

17. Since agents will get scammed by other agents, a whole trust layer has to get built. The Yelp for agents. The escrow for machines. Wide open.

18. You keep the whole thing now. A business that needed 50 people to hit $10M needs 3 and some agents, so instead of splitting it 200 ways with investors, it's just yours.

19. Search engines minted a generation of millionaires and billionaires. LLM search is about to do it all over again. Billions of eyeballs are moving off Google and onto ChatGPT, so being the answer inside the models is the new front page.

20. The margins are stupid. You charge someone what they'd pay a human, and it costs you a few bucks in tokens. That gap used to go to payroll. Now it goes to you.

Any one of these would DEFINE a decade on its own.

We got ALL of them at once, stacked on top of each other in the same 18 months.

It's a magical time to be building.

You don't need to overthink it.

Build.

[Boris Cherny @bcherny]

I talk to engineers at other companies every day and hear the same thing: one person is 10x'ing their output with Claude but the rest of the org hasn't caught up.

Watching teams adopt AI, I keep seeing the same 4 steps.

I mapped them out here: Steps of AI Adoption https://t.co/kQnRAUMKpP

[GREG ISENBERG @gregisenberg]

i keep a running doc called “things i’m not doing anymore” and look at it monthly

really simple way to live a happier & more productive life

[chewa. @chewadot]

THE CEO OF OBSIDIAN JUST OPEN-SOURCED THE CLAUDE CODE SKILLS HE WAS USING PRIVATELY IN HIS OWN VAULT. 40,000 STARS IN A FEW WEEKS

5 skills. 1 MIT license. 0 pitches

kepano - the founder who wrote the "File over app" essay - dropped a set of Agent Skills that teach Claude Code to read and write Obsidian files the way a human expert would. Markdown that respects wikilinks. Bases queries Claude actually writes correctly

JSON Canvas edits that don't corrupt the file. A defuddle skill that strips ads and boilerplate off any URL and drops a clean note into your vault. He built them for himself, tested them in his own workflow, then pushed the folder to GitHub

every skill is one SKILL.md file. Drop the repo into .claude/skills/ and Claude Code picks them up automatically. No plugin store. No account. No cloud. Same idea that made Obsidian: your notes are files on your disk, the app is disposable, and the AI just learned to speak the format

the essay was called "File over app". The workflow is now file over agent

MIT-licensed. Shipped in his own name

no vendor lock. no subscription. no cloud memory. no walled garden. no pitch to raise a round

you're reading this on a device that could clone the repo, drop it into your vault, and have Claude Code editing your notes correctly before your next standup

[ericosiu @ericosiu]

Every team is going to need a Single Brain.

-Your CRM knows the deal history.
-Gong knows the customer language.
-Slack knows what the team is actually doing.

But none of it compounds if it lives in separate tabs.

You wouldn't let your team work with no shared memory, so why are your tools still doing it?

This is the idea behind Single Brain: one shared memory layer for market intel, strategy, content, campaigns, measurement, and client context.

[Mr. Buzzoni @polydao]

THE ANATOMY OF A LOOP RUNNING WHILE YOU SLEEP

an anthropic engineer runs autonomous code cycles on a closed laptop using a five-file folder

this loop architecture opens pull requests and runs tests without a single chat prompt:

> contract.md - defines the shift rules and operational boundaries
> schedule.yml - triggers the cron events to launch the next cycle
> rubrics/ - stores the graders to evaluate output quality before staging
> state/ - logs active checkpoints to recover from system crashes

the window to run Fable 5 reasoning loops under the $20 subscription closes on July 12th

build your autonomous pipelines now before it shifts to expensive API billing

grab the full folder blueprint below 👇