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you should spend an afternoon building a second brain with jev... here's how i'd set it up: > create one inbox for saved posts, articles, meeting notes and ideas... give your agent access to it > give jev your active projects and interests so it can sort incoming material... into categories that mean something to you > have your agent find similar notes, then use jev to flag duplicates and spot which ones add something new > save everything with its original link and date so you can always check where it came from > whenever you start a task, have your agent search the archive and let jev score which notes are relevant > feed those into your writing agent before it starts working... your customer conversations, examples and previous decisions are already there writing a proposal? bring back what the customer said on the call and the case study that answers their objection. working on a post? pull up the idea you saved three weeks ago alongside your own notes on the topic. start with one project and the material you've already collected for it. ask your coding agent to build that workflow, then check what it brings back on your next real task.show more

J.B.

37,941 subscribers

13,429 Aufrufe • vor 9 Tagen •via X (Twitter)

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13 Kommentare

Profilbild von josh 🏔️

josh 🏔️vor 9 Tagen

here's another way to use Jev to set up a second brain! It is a step change on something I've been daily driving for 2 years.

Profilbild von Josip

Josipvor 8 Tagen

ermm how about no

Profilbild von J.B.

J.B.vor 8 Tagen

all g lil bro

Profilbild von maxx

maxxvor 9 Tagen

1/ are we over obsidian now? 2/ do you have jev invites

Profilbild von Mehdi Djabri

Mehdi Djabrivor 8 Tagen

combine with long-term agent memory

Profilbild von Dassi AI

Dassi AIvor 8 Tagen

The biggest drop-off in second-brain setups is capture friction—manually clipping across 10 open tabs into an inbox breaks the habit fast. Hooking an agent to snapshot page context and URL metadata directly from active sessions keeps the ingestion completely frictionless.

Profilbild von Tobi

Tobivor 9 Tagen

the missing layer is time. an archive can retrieve the right fact and still surface the wrong priority. keep provenance, freshness, and the decision that changed it.the missing layer is time. an archive can retrieve the right fact and still surface the wrong priority. keep provenance, freshness, and the decision that changed it.

Profilbild von Wei Pan

Wei Panvor 8 Tagen

This is the shape that sticks for me: one inbox + explicit project context + the agent only proposes. My morning X scan runs that way – surface opportunities, draft replies, wait for my yes. Memory without a human gate just becomes a louder feed.

Profilbild von Henry "Coop" Jackson

Henry "Coop" Jacksonvor 8 Tagen

nice, my second brain is 400 open tabs and a notes app I forgot the password to

Profilbild von Kevin

Kevinvor 9 Tagen

I just did a version of this with my @Pebble index ring. Time to run it for my whole brain

Profilbild von Kevinllll

Kevinllllvor 8 Tagen

i like the original link/date rule. otherwise the second brain becomes a very confident junk drawer.

Profilbild von Felipe Chaves

Felipe Chavesvor 7 Tagen

A useful first test: write 10 questions you actually need the archive to answer, and note the source each should retrieve. Include a few where the answer isn't there. Then check whether it finds evidence or just returns plausible-looking notes.

Profilbild von Uttam

Uttamvor 8 Tagen

The useful part isn't the archive. It's the decision trail. A second brain that only stores links becomes another inbox. The agent should surface the prior decision, its source, and what changed since then.

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you let your agent keep notes, because the alternative was explaining yourself every morning it stopped asking, and it started repeating things that had stopped being true every guide on this covers what to save and where to put it, private for one agent, shared for the team not one of them covers how a fact leaves the agent writes its own memory while it works, so a guess it made on a tired tuesday gets stored in the same shape as something you told it, and after that the two are indistinguishable i counted mine this morning: forty files, six of them about decisions we reversed months ago, all forty read into every session since you did not give it a memory you gave it a record with no way to be corrected

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Akshay 🚀

116,880 Aufrufe • vor 5 Tagen

We’re entering the 10x speed of research publication workflow with AI. SciSpace (SciSpace), the first AI Agent built exclusively for the scientific community, is releasing so many inredibly useful features. 🎯 This is the AI Agent that can use 150+ tools, 59 databases, and 280M+ papers A few weeks back they launched BioMed Agent - It can design entire molecular biology workflows and even create publication-ready illustrations in a single prompt. This is its new domain-specialized AI co-scientist that sits on top of the existing SciSpace Agent and automates full biomedical workflows, from raw data and papers to analysis, decisions, and the final production-grade illustrations. You just need to give it 1 prompt. And today the added the following - Library Search, so it can search and analyze the PDFs already sitting in My Library, letting people ask questions across their own paper pile while keeping it private. - Now connects directly to Zotero, so the Agent can pull and work with the papers you already saved there without manual uploads. - For bigger prompts, it auto-triggers a Report Writing Sub-Agent that turns the chat into a structured research-style report, which is way cleaner for literature reviews and long summaries. - And when you get something worth keeping, Save to Notebook lets you store the output as .md notes with citations in My notebooks, so the work becomes reusable research notes instead of disappearing into chat. Behind the scenes, it indexes the PDF text, pulls a few relevant chunks for the question, then writes an answer grounded on those chunks.

We’re entering the 10x speed of research publication workflow with AI. SciSpace (SciSpace), the first AI Agent built exclusively for the scientific community, is releasing so many inredibly useful features. 🎯 This is the AI Agent that can use 150+ tools, 59 databases, and 280M+ papers A few weeks back they launched BioMed Agent - It can design entire molecular biology workflows and even create publication-ready illustrations in a single prompt. This is its new domain-specialized AI co-scientist that sits on top of the existing SciSpace Agent and automates full biomedical workflows, from raw data and papers to analysis, decisions, and the final production-grade illustrations. You just need to give it 1 prompt. And today the added the following - Library Search, so it can search and analyze the PDFs already sitting in My Library, letting people ask questions across their own paper pile while keeping it private. - Now connects directly to Zotero, so the Agent can pull and work with the papers you already saved there without manual uploads. - For bigger prompts, it auto-triggers a Report Writing Sub-Agent that turns the chat into a structured research-style report, which is way cleaner for literature reviews and long summaries. - And when you get something worth keeping, Save to Notebook lets you store the output as .md notes with citations in My notebooks, so the work becomes reusable research notes instead of disappearing into chat. Behind the scenes, it indexes the PDF text, pulls a few relevant chunks for the question, then writes an answer grounded on those chunks.

Rohan Paul

11,574 Aufrufe • vor 8 Monaten

Introducing RAGs, a Streamlit app that allows you to create and customize your own RAG agent and then use it over your own data, all with natural language 🔥 Directly inspired by OpenAI GPTs, you can converse with an agent to help you do search/retrieval over any data you specify. The app contains three main pages: 🏠 Home Page : Have a “builder agent” build your RAG agent through natural language (you specify the data). ⚙️ RAG Config: Look at configured parameters 🤖 Use your RAG agent! Check out details below 👇 Blog: Repo:

Introducing RAGs, a Streamlit app that allows you to create and customize your own RAG agent and then use it over your own data, all with natural language 🔥 Directly inspired by OpenAI GPTs, you can converse with an agent to help you do search/retrieval over any data you specify. The app contains three main pages: 🏠 Home Page : Have a “builder agent” build your RAG agent through natural language (you specify the data). ⚙️ RAG Config: Look at configured parameters 🤖 Use your RAG agent! Check out details below 👇 Blog: Repo:

LlamaIndex 🦙

475,732 Aufrufe • vor 2 Jahren

Now you can use your favorite AI agent to control your Coinbase account (or a sub-account), with Coinbase for Agents. Here’s a quick demo on how to set it up and some of the cool things you can get your agent to do.

Now you can use your favorite AI agent to control your Coinbase account (or a sub-account), with Coinbase for Agents. Here’s a quick demo on how to set it up and some of the cool things you can get your agent to do.

Brian Armstrong

213,812 Aufrufe • vor 3 Monaten

Agents are now your customers. Here are 9 startup ideas for that customer: - An agency that makes agents cite you. - A system that gives an agent an identity and permissions. - Receipts and audit trails for the work an agent does. - A generator that makes your documents ready for agents. - Security for the agent that reads your inbox. - A service that makes your pricing page readable to an agent. - MCP servers for franchises. - A support desk that agents call. - A sandbox where agents test your software. Pick one and build it.

Agents are now your customers. Here are 9 startup ideas for that customer: - An agency that makes agents cite you. - A system that gives an agent an identity and permissions. - Receipts and audit trails for the work an agent does. - A generator that makes your documents ready for agents. - Security for the agent that reads your inbox. - A service that makes your pricing page readable to an agent. - MCP servers for franchises. - A support desk that agents call. - A sandbox where agents test your software. Pick one and build it.

The Startup Ideas Podcast (SIP) 🧃

14,148 Aufrufe • vor 1 Monat

Voice is now available in your existing Codex threads. Talk through a PR with the agent that wrote it, debate the architecture, or work out what comes next. You can jump into voice whenever something needs a back-and-forth, then let the agent keep working once you’ve figured it out together.

Voice is now available in your existing Codex threads. Talk through a PR with the agent that wrote it, debate the architecture, or work out what comes next. You can jump into voice whenever something needs a back-and-forth, then let the agent keep working once you’ve figured it out together.

Guinness Chen

182,241 Aufrufe • vor 24 Tagen