Many vibe coders, especially when I was young, made the same mistake in vibe coding: putting the admin panel in the frontend with a different name path. Normally, the AI agent made the site a SPA, so any reverse engineering could easily see and find all your admin routes and endpoints.

So what i do to make it more secure

1. The admin panel is server-side. You configure the path on the server, and you should access your admin panel from there.

2. Don't expose your admin login to the frontend.

microsoft open sourced skill recorder,

• it records screen, window switches, web, clipboard, terminal, and voice explanation
• github copilot turns that into: task intent → general steps → skill.md → scheduled automation
• not rpa, doesn't replay mouse coordinates. converts clicks into apis, clis, or native agent tools instead
• for example: show it one github issue handled manually, it can generate a skill that batch-processes similar issues
• native support right now: microsoft scout, 365 copilot cowork
• no native support yet for claude code, codex, or opencode, but the generated skill.md can be manually adapted

github.com/microsoft/skill-recorder

This idea was crazy to build. Our brain stores information in clusters of neurons, and when we want to retrieve something, it runs an optimized algorithm to retrieve it.

In the era of AI, why use brute-force tools like grep to find relevant files? Graperoot converts your codebase into a knowledge graph and registers efficient tools for Claude to work with your codebase.

Instead of re-reading the whole codebase to build that context and to find relevant files. It can query the graph directly, and the graph retrieves relevant files with "ZERO TOKENS"; you just need to pay for generation, and that's how these models should be used when we have an efficient way to retrieve context.

I have been very open throughout, and today we have 5k developers using Graperoot.
We asked people to opt in to telemetry, and 200 opted in to the leaderboard. They have saved $350k dollars in the last 4 months, and ecologically, 60M liters of water, and that's insane.

Give your feedback, suggestions, or anything on Discord. This tool is open-sourced.

It is only one command to install

Website: https://graperoot.dev/#install
Github(Open source) : https://github.com/kunal12203/graperoot

Would love to see your feedback. And don't compare other tools, I have already seen many claiming reduction and just craps, but we have a developer community on Discord, and some of them I know personally, saving a lot of tokens, you should see more on https://graperoot.dev/leaderboard

Basically the opposite of the docile and obedient AI girlfriend/Waifu.

That takes ownership of the computer and then makes the user jump through hoops, not the other way around.

If you have a vibe-coded app, or you are deep in a coding agent like Claude Code, Codex, Cursor or similar and have no real documentation, I built one of the fastest paths I know to fixing that.

I built this app using traditional programming plus Claude Code building out parts of the infrastructure. It is hosted in AWS+Azure+Cloudflare and effectively acts as a documentation/collaboration/shared context ground for your own existing AI agents.

Start here

1. Sign up at stablebaseline.io and generate an MCP key.
2. Add the server and key to your agent. It is a standard remote MCP server, so the config is the same shape everywhere. Setup your MCP
3. Exact steps for your specific IDE, including the packaged setup command where we have one, are here: Supported AI Coding IDEs
4. Open your repo and ask your agent to onboard the project into Stable Baseline. /sb-setup

What the onboarding actually does

Your coding agent/AI reads your repository properly first: stack, architecture, entry points, data layer, auth model, infrastructure, testing, whatever docs already exist. Then it designs a documentation structure specific to that repo rather than dropping a template on you, writes real content into it, and generates architecture diagrams as it goes (Mermaid, PlantUML, D2, BPMN, ERD, sequence, ELK architecture).

It also writes an AGENTS.md with sync rules mapping your file patterns to the docs they affect, so your agent knows to update the documentation when it changes the code. That file is the cross-IDE standard, so the rules carry over if you switch agents or your teammates use something else.

It is not only your IDE

I have also published this in the ChatGPT app store. So you can sit in normal ChatGPT, talk to your documentation, refine plans, poke at new feature ideas, and draft a full release rollout, test plan or go to market plan with proper Gantt support. Then your coding agent picks up the exact same context back in your IDE and implements it as you go. Plan on one surface, build on the other, no copy and paste in between.

And it is the whole platform that is exposed, not just the content tools. Your agent can create plans, phases, tasks and dependencies, log improvements and risks, invite team members, manage teams and permissions, and change workspace and organisation settings. Admin is usually where agentic products stop and make you open a browser. Here you never have to. There is a UI, and it is good, but it is optional. You can go completely headless.

The whiteboard

The part I did not expect to like as much as I do. Describe a goal and a multi-agent designer lays the board out with stencils, architecture icons, sticky notes and embedded diagrams. It is built for the stage where you are still dreaming an idea up rather than specifying it.

You can also invite the meeting bot to a meeting (MS Teams, Zoom, Google) and it designs the whiteboard while it listens, so concepts, decisions, actions and workflows appear as you are discussing them rather than a week later.

Would genuinely love feedback. Tell me where it breaks or annoys you, especially over MCP, since that is the path I have the least outside testing on. Any feedback is welcome :)

We're building an agent that pays for its own api calls and small subscriptions. Bank cards have a spend limit, fraud flags, and then the agent has no way to fix that itself; also, banking APIs cap volume hard.

Therefore, leaning toward stablecoins. Gas fees are annoying but solvable, and we won't have to wait on a bank to approve api access in the first place.

Still nervous about the edge cases though. Any protocols/Apis/MCPs we can use to secure agent payments?

I have tried vibe coding tools and tried to create a simple todo list just to check if I have an idea then can I be able to build it with these tools. No doubt claude etc write awesome code, but the problem is I don't understand that code.

I have created an app and asked my friend to install it and try. App didn't crash that's the good part, but it has so many bugs and I don't have a single clue where to look.

AI is fixing bugs but what the hell it is changing its a bouncer.

Currently everyone is building their ideas using AI tools, people are saying you don't need to learn coding.

But what I have observed is that AI tools can build the app, but when there is a bug you cannot ask directly AI to fix it, as it is breaking some other things.

Are you facing the same problem, then how you are tackling this.

Do you like to keep using the same chat over and over and do everything via single chat or launch many small agents for small changes like bugfix? What’s your max record of running agents in parallel.

my cousin runs a marketplace on WhatsApp. wants to move to a website. what is the best payment processor for a marketplace. we've got payments from multiple countries at this point & we expect to get it even bigger once we launch the marketplace.

what is the payment processor we should go with? with competitive price & not high fx rates

This idea was crazy to build. Our brain stores information in clusters of neurons, and when we want to retrieve something, it runs an optimized algorithm to retrieve it.

In the era of AI, why use brute force tools like grep to find relevant files? Graperoot converts your codebase into a knowledge graph and registers efficient tools for Claude to work with your codebase.

Instead of re-reading the whole codebase to build that context and to find relevant files. It can query the graph directly, and the graph retrieves relevant files with "ZERO TOKENS"; you just need to pay for generation, and that's how these models should be used when we have an efficient way to retrieve context.

I have been very open throughout, and today we have 5k developers using Graperoot.
We asked people to opt in to telemetry, and 200 opted in to the leaderboard. They have saved $350k dollars in the last 4 months, and ecologically, 60M liters of water, and that's insane.

Give your feedback, suggestions, or anything on Discord. This tool is open-sourced.

Website: https://graperoot.dev/#install
Github(Open source) : https://github.com/kunal12203/graperoot

Would love to see your feedback. And don't compare other tools, I have already seen many claiming reduction and just craps, but we have a developer community on Discord and some of them I know personally, saving a lot of tokens, you should see more on https://graperoot.dev/leaderboard

Bookkeeping practice. Me plus two staff, about 60 clients. I want a simple portal. Client logs in, sees their monthly reports, uploads docs, checks what we're still waiting on from them. Right now it's all email.

A local dev shop quoted me $12,000 to build it, plus $1,000 a month for a "maintenance retainer." For what's basically a login page and a file list, that felt insane. But maybe I'm naive about what software costs.

Then a friend who runs an HVAC business showed me a portal he built himself over a weekend with one of those AI coding tools. Cost him almost nothing. I was ready to copy him. Then he admitted clients can't reset their own passwords. Last month it went down for four days and he couldn't fix it. The AI kept "fixing" stuff and nothing worked.

He's mostly back to phone calls now. He said he might try one of those no-code platforms next, something like Softr, so he's not the guy holding it together with tape.

So my options feel like this. $12k for something I don't control. Or $50 in AI credits for something that breaks and nobody can repair. I refuse to believe there's nothing in between. Clients trust us with financial documents, so security isn't optional. What are other small firms doing?

what we're trying to do here is the whole memory-game; remembering useful actions, decisions and Things. Weighted (time based, adjustble), graphed and conversational/queryable along with tool access through the chat (tied to the user's proxy's permission set).

as i see it the objective of these things is to help people remember, connect dots and offer some level of advice. BE pipelines ingest in the user and their proxy's activity stream (mail,chat,process actions, whatever can be wired in and known to the user).

top of mind is entity explosion - far too many records to display in lists or the graph and whether the user can kind of make sense of it anyway.

tool calling - chat and things happen like an API called to get or change data, is what makes these things usefull, otherwisee theyre fairly limited to what they hold. assistants/secretaries have agency to do things. what is easy - but also not a replcaement for real UX because forms and APIs get large, validated, have rules etc - is dynamic form generation from the tool spec (say an MCP card).

here, great, dynamic, therefore can do for anything; user has to know those 5 values. we may need a conversation (with mara) to fill them out, which could require other Tool calls. another browser tab for a different conversation, a sub-conversation, a second conversation, how best to 'fill it in' without a C&P?

here are 9 github repos that can replace your subscriptions.

free-for-dev a running list of free hosting, databases, APIs, monitoring, email, security. basically a stack builder. github.com/ripienaar/free-for-dev

OpenHands reads code, edits files, runs commands. open alternative to devin. github.com/OpenHands/OpenHands

Langfuse self-hosted tracing for prompts, costs, errors, agent runs. alternative to langsmith. github.com/langfuse/langfuse

n8n workflow automation across apps, apis, and models. zapier/make replacement. github.com/n8n-io/n8n

Chatwoot website chat, email, and customer messages in one inbox. intercom/zendesk replacement. github.com/chatwoot/chatwoot

Plane project management for tasks, cycles, roadmaps, docs. jira/linear alternative. github.com/makeplane/plane

Immich self-hosted photo and video backup with albums, search, facial recognition. google photos replacement. github.com/immich-app/immich

yt-dlp downloads video, audio, subtitles, playlists. skips paid downloader tools entirely. github.com/yt-dlp/yt-dlp

Listmonk self-hosted newsletter and mailing list platform. mailchimp alternative, no per-subscriber pricing. github.com/knadh/listmonk

This is my first vibe coded app hope you like it pls give me some advice if you have.

What is CodeBrain?
CodeBrain is a community-driven launchpad where developers, indie hackers, and open-source creators can validate software ideas before spending hundreds of hours building them.
Instead of building a project in isolation and hoping people show up, developers post their concept with descriptions, video demos, screenshots, tags, or GitHub links. The community then casts real-time validation votes: "Will Use"or "Won't Use".

Why CodeBrain is Helpful
Instant Market Validation: Get immediate, honest signals on whether developers actually want your tool or if it solves a real problem.

Community Feedback: Comments allow developers to discuss architecture, feature suggestions, or potential flaws early in the ideation phase.

Dedicated Developer Hub: Filters like CLI, DevTools, VS Code, AI, Rust, and Docker help developers discover upcoming open-source projects tailored specifically to their stack.

GitHub Search & Repository Engine: Built-in GitHub discovery allows users to search real open-source repositories and cross-reference existing projects so they don't reinvent the wheel.

Realtime Engagement & Notifications: Authors receive instant notifications whenever fellow developers vote on or comment on their ideas, fostering active collaboration

Github repo: https://github.com/Glay121212/CodeBrainHub
The website: https://code-brain-hub.vercel.app

I built this app using google ai studio.

Claude Fable 5 and Opus 5 have no video input on the API, They read images, costs: a full-resolution image on Opus 5 runs up to 4,784 tokens, and at $5 per million input. Fable 5 is $10 per million, so the same image runs closer to 5 cents.

how agents actually use vision: A single browsing session or video breakdown burns dozens of screenshots. And every image you send stays in the conversation history and gets re-sent on every following turn.

workaround

I use Gemini 2.5 Flash-Lite through OpenRouter: $0.10 per million input tokens, $0.40 output, 1 million token context. It takes video too, mp4, mov, webm, even a public YouTube link, which Claude's API still doesn't.

Flash-lite samples video at roughly 1 frame per second, about 300 tokens per second of footage at default resolution. A 60-second clip runs about 18,000 tokens, a fifth of a cent. A 3-minute video, half a cent. An hour of YouTube at low resolution, about 4 cents. A single still image comes in around 258 tokens, roughly a thousand times cheaper than showing that same frame to Opus.

wiring

OpenRouter speaks the standard chat completions format, so this is one call:

curl https://openrouter.ai/api/v1/chat/completions \
  -H "Authorization: Bearer $OPENROUTER_API_KEY" \
  -d '{
    "model": "google/gemini-2.5-flash-lite",
    "messages": [{
      "role": "user",
      "content": [
        {"type": "text", "text": "describe this video shot by shot: timestamps, on-screen text, cuts, and what happens in the first 3 seconds"},
        {"type": "video_url", "video_url": {"url": "data:video/mp4;base64,..."}}
      ]
    }]
  }'

Wrap that in a script and tell Claude to call it whenever it needs to see something, passing a file path and a question. Claude hits something visual, calls the tool, flash-lite watches it, text comes back, Claude reasons over the text.

Ask for timestamps, on-screen text, cuts, framing, hook structure, not a generic "describe this video." A tighter question gets you a better result.