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I vibecoded an app in 2 days. Adding one new feature now takes me a week and a pile of tokens. Fix login, streaks break. Fix streaks, login breaks. The AI just goes in circles. Has this happened to you? It's not you. Every new chat starts with zero... memory of your app. So the agent re-reads 40 files, rebuilds helpers that already exist, and misses what your change touches. Repowise indexes your codebase and keeps it updated on every commit. Even a brand new chat window knows: > what's already built > what's connected to what > what breaks if you change it Your agent reads the map instead of guessing. 27x fewer tokens to load context. 89% fewer file reads. Save the hours, the tokens, and your sanity. Connect your repo:show more

NAYAK

21,551 subscribers

39,547 Aufrufe • vor 2 Tagen •via X (Twitter)

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4 Kommentare

Profilbild von Aryan SMM

Aryan SMMvor 2 Tagen

this is relatable,context loss is one of the biggest problems when building with AI agents

Profilbild von Artists Voyage 🔶

Artists Voyage 🔶vor 2 Tagen

the codebase map is the interesting part. knowing what connects to what can prevent a lot of unnecessary file reading

Profilbild von Geb AI

Geb AIvor 2 Tagen

Been there. What helps: a short living spec (architecture, conventions, what not to touch) that every session reads first, then small scoped changes with a test each. Persistent memory beats a bigger prompt every time.

Profilbild von Tanvir

Tanvirvor 2 Tagen

Persistent codebase context could make AI coding far smoother.

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Sarah Chieng

26,679 Aufrufe • vor 6 Monaten

This guy took a brand‑new app to #1 overall in the App Store and 1,000,000 downloads in under 3 days. For the FIRST TIME, he breaks down exactly how he did it, and we’re posting the full, RAW conversation right here on X To be clear, this is his first and only podcast on this playbook... And a little more context: this wasn’t luck. Jibran has taken 4 different apps to #1 in the App Store, including one that did $1.5M in 3 days and outranked ChatGPT He did it with a handful of creators, zero paid ads, and a product philosophy that blew my mind Here’s the core of what he taught me: > Your product and your marketing are not two separate things; they're the same thing. > What goes viral on TikTok is product validation. > What you learn from a hit video should change your UI, your App Store screenshots, your icon He ran that loop obsessively.. For his 2025 Wrapped app, he spent hundreds of hours in Figma asking one question: > “How does this look on TikTok?” Then he tracked: 1. What users screenshotted 2. What they shared to Snapchat 3. What slide they dropped off on The result was a #1 overall app in the App Store. Above EVERYTHING. Now he’s building because he realized he was spending hours every day doom‑scrolling TikTok looking for hooks and formats that worked So he built an AI to do it for him: > You tell it your app. > It tells you what to post, what’s trending in your niche, and what’s wrong with your existing videos. We go deep on all of it in this conversation. If you run a consumer app, this is the most useful 49 minutes you’ll spend this week

Alex Olim

106,690 Aufrufe • vor 5 Monaten

Run your coding agent on a local model, with QVAC. OpenCode now plugs into a model on your own machine through our official plugin. That changes two things. Privacy by default. Your repo, your prompts, and every command the agent runs stay on your device. No third-party model ever sees your code. For an agent that reads your codebase and runs commands, that is the point, not a nice-to-have. New workflows. With no meter and no rate limit, the agent does not have to stop. Let it loop on a task, refactor a whole repo overnight, or run a watch-build-fix loop that keeps going. Setup takes a few minutes: one line in opencode.json and OpenCode runs on a local QVAC model. In the video demo, it handles three real developer tasks back to back, fully offline.

Run your coding agent on a local model, with QVAC. OpenCode now plugs into a model on your own machine through our official plugin. That changes two things. Privacy by default. Your repo, your prompts, and every command the agent runs stay on your device. No third-party model ever sees your code. For an agent that reads your codebase and runs commands, that is the point, not a nice-to-have. New workflows. With no meter and no rate limit, the agent does not have to stop. Let it loop on a task, refactor a whole repo overnight, or run a watch-build-fix loop that keeps going. Setup takes a few minutes: one line in opencode.json and OpenCode runs on a local QVAC model. In the video demo, it handles three real developer tasks back to back, fully offline.

QVAC

11,382,936 Aufrufe • vor 3 Monaten

What is a software factory? It is your workflow, your skills, and your domain knowledge, saved in files that the agent reads so the whole process is productized Think about the last app you built. You typed what you wanted, and the agent built it. You did not like it, so you made changes. You shipped it to Vercel, or you kept going. A factory puts structure on each of those steps. At each step you ask how to get the most from the model, and how to move faster. That is the conveyor belt. You ship quickly, and the quality stays the same. Mine is 5 md files. It works in Codex, Claude Code, and Cursor, because it does not depend on the model or the tool. Build your own.

What is a software factory? It is your workflow, your skills, and your domain knowledge, saved in files that the agent reads so the whole process is productized Think about the last app you built. You typed what you wanted, and the agent built it. You did not like it, so you made changes. You shipped it to Vercel, or you kept going. A factory puts structure on each of those steps. At each step you ask how to get the most from the model, and how to move faster. That is the conveyor belt. You ship quickly, and the quality stays the same. Mine is 5 md files. It works in Codex, Claude Code, and Cursor, because it does not depend on the model or the tool. Build your own.

The Startup Ideas Podcast (SIP) 🧃

17,326 Aufrufe • vor 16 Tagen

A GUY MAKING $100K/MONTH WITH AI JUST SHOWED HIS ENTIRE SETUP. IT'S ONE FOLDER OF NOTES AND NOTHING ELSE no framework. no $500 course. he opens his screen and it's just obsidian - a plain notes app - wired into claude here's what he did: -> he pulled claude's memory files out of their default folder and dumped them into one vault -> had claude rename and merge them: 107 messy files collapsed into 17 clean ones -> every folder gets one master note that links to all the others that last part is the whole trick the agent reads the master note, follows the links and by the time it's done it has read every file in the folder. one instruction, full context here's the part most people miss: everyone's trying to make the AI smarter. he made the AI's memory smaller fewer files, better organized, all linked. the agent isn't scanning hundreds of notes anymore - it walks a path you built that's why his agent actually finishes jobs instead of forgetting what it was doing halfway through then he goes one step further: at the end of every session, the agent writes its own daily note. what it did, when, indexed at the top so it can find it again in seconds so he never re-explains anything. the agent looks up what it already did now he types "create a campaign for this offer" and walks away. it reads the product notes, reads the process notes, and comes back with the campaign done you don't need any of the complicated agent tools people are selling you. you need structure and instructions save this. the people winning with AI aren't using better models. they're just the only ones who bothered to organize what it remembers

A GUY MAKING $100K/MONTH WITH AI JUST SHOWED HIS ENTIRE SETUP. IT'S ONE FOLDER OF NOTES AND NOTHING ELSE no framework. no $500 course. he opens his screen and it's just obsidian - a plain notes app - wired into claude here's what he did: -> he pulled claude's memory files out of their default folder and dumped them into one vault -> had claude rename and merge them: 107 messy files collapsed into 17 clean ones -> every folder gets one master note that links to all the others that last part is the whole trick the agent reads the master note, follows the links and by the time it's done it has read every file in the folder. one instruction, full context here's the part most people miss: everyone's trying to make the AI smarter. he made the AI's memory smaller fewer files, better organized, all linked. the agent isn't scanning hundreds of notes anymore - it walks a path you built that's why his agent actually finishes jobs instead of forgetting what it was doing halfway through then he goes one step further: at the end of every session, the agent writes its own daily note. what it did, when, indexed at the top so it can find it again in seconds so he never re-explains anything. the agent looks up what it already did now he types "create a campaign for this offer" and walks away. it reads the product notes, reads the process notes, and comes back with the campaign done you don't need any of the complicated agent tools people are selling you. you need structure and instructions save this. the people winning with AI aren't using better models. they're just the only ones who bothered to organize what it remembers

Paone

23,833 Aufrufe • vor 2 Monaten

One of my favorite upgrades to Claude Cowork right now: Projects Here's the problem it solves: By default, every new thread starts blank Claude has no memory of what you were working on, what other threads figured out, or what your instructions were So you'd re-explain yourself at the start of every session Or your agents would overlap, contradict each other, or miss context that another thread already had If you've been following my Cowork setup guides, you've already solved part of this — local files and a CLAUDE.md get you most of the way there Projects takes it the rest of the way Shared memory across every thread in the project Permanent instructions that apply everywhere — set once, always on Scheduled tasks that prep your work before you open the app One project HQ to launch every agent from The day-one prompt I paste into every new project: "I just created this project. Read every file in the folder. Then summarize what you know about this workspace — what's here, what I probably use it for, and what instructions you'll follow. If anything is unclear, ask me some questions." Run that once and Claude builds its own understanding of your project workspace from scratch Full video with my live build, including my 4 tips for getting Projects right, and where projects still lack. Send to someone whose ready to Do More with AI, or bookmark to implement this weekend!

One of my favorite upgrades to Claude Cowork right now: Projects Here's the problem it solves: By default, every new thread starts blank Claude has no memory of what you were working on, what other threads figured out, or what your instructions were So you'd re-explain yourself at the start of every session Or your agents would overlap, contradict each other, or miss context that another thread already had If you've been following my Cowork setup guides, you've already solved part of this — local files and a CLAUDE.md get you most of the way there Projects takes it the rest of the way Shared memory across every thread in the project Permanent instructions that apply everywhere — set once, always on Scheduled tasks that prep your work before you open the app One project HQ to launch every agent from The day-one prompt I paste into every new project: "I just created this project. Read every file in the folder. Then summarize what you know about this workspace — what's here, what I probably use it for, and what instructions you'll follow. If anything is unclear, ask me some questions." Run that once and Claude builds its own understanding of your project workspace from scratch Full video with my live build, including my 4 tips for getting Projects right, and where projects still lack. Send to someone whose ready to Do More with AI, or bookmark to implement this weekend!

JJ Englert

29,809 Aufrufe • vor 6 Monaten

On Day 3 of 12 Days of Agent Two: The Agent has eyes. Agent Two reads and understands ANYTHING you upload into the chat. Videos, images, scripts, PDFs, YouTube links, Drive files, brand books, rough cuts, whatever you give it. And it doesn't just read your files. It checks them against your project's context and understands what the uploaded video means and where it would be relevant and useful. Agent Two is frontier intelligence for creative work. 4x faster, at half the price.

Invideo

3,233,809 Aufrufe • vor 2 Monaten

Agent Zero crushed Codex by 2.6× on token efficiency! We gave both agents the same task on the same local model (Qwen3.6 27B): build a retro Q*bert arcade game. Each agent wrote and rewrote it across iterations, adding enemies and a HUD. Outputs: • Agent Zero: 239K tokens, 53 min • Codex: 627K tokens, 51 min Both agents built a working Q*bert, but Gitlawb 's Agent Zero is the cleaner build, with crisper textures and hops that land where they should. Codex refills the context window with its whole history every turn, so the model loses the thread and hallucinates code it never wrote. Agent Zero sends only what's new, so it keeps more of the window open and makes fewer mistakes. Run agents on local AI models in Atomic Chat!

Agent Zero crushed Codex by 2.6× on token efficiency! We gave both agents the same task on the same local model (Qwen3.6 27B): build a retro Qbert arcade game. Each agent wrote and rewrote it across iterations, adding enemies and a HUD. Outputs: • Agent Zero: 239K tokens, 53 min • Codex: 627K tokens, 51 min Both agents built a working Qbert, but Gitlawb 's Agent Zero is the cleaner build, with crisper textures and hops that land where they should. Codex refills the context window with its whole history every turn, so the model loses the thread and hallucinates code it never wrote. Agent Zero sends only what's new, so it keeps more of the window open and makes fewer mistakes. Run agents on local AI models in Atomic Chat!

atomic.chat

320,472 Aufrufe • vor 2 Monaten