u/EagleApprehensive

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I've built a self-hosted AI workspace unlike others.

Features:

- Everything is in git version-control system - Connected subscriptions, secrets, file-system it sees, tools, skills, repositories. Even own dockerfile definition of the sandbox is under version control, so sandbox is a fully predictable environment.

- You save tokens - It comes with baked proven systems that do automatic rebasing to prevent conflicts, semantic codebase indexing and search, removes bloat ("use pronouns they/them" etc.) from system prompts. Extra systems prevent port collisions and various conflicts that happen in standard IDE's when 20 agents do complex tasks in the same container.

- You earn money - For extensions and services, that bridge the gap between intent and execution for users of this AI workspace. When doing complex tasks agents will suggest to save tokens and instead pay credits to specialized service.

- Deployable and shared - You can host 10 such workspaces using docker-compose for your entire company and invite various employees to work in various sandboxes - help each other tinker and tweak AI brain together.

- Has decent UX - I do my best effort to keep things smooth, performant and make everything possible with least amount of clicks. Although - I don't yet provide cloud hosting service, you have to "Bring Your Cloud" or self-host.

↗️ More info: https://intentic.dev

↗️ GitHub: https://github.com/intentic/intentic

P.S. There is much more: agents can do - connect to physical machines and execute there, sign up on websites and run accounts, draft actions to execute on platforms waiting for your approval, you can run custom workflows side by side (i.e. GPT+Claude side-by-side and then synthesis of their findings) or run GPT with Claude Code harness or PI (text, mix and match).

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I believe there is short window of opportunity now for a new platform. This time not for influencers, but for builders and service providers - recently opened by OpenClaw and followed by Hermes.

Agents become more capable, but complex flows need curated data access, reliable outcome and eventually to deliver lower costs due to scaling effects and specialization. That's the game I bet on.

So I'm creating a space, where we all can build, bring our audiences, market and earn together.

Unlike Claude, OpenClaw or Hermes plugins, system I've built allows:

1. Almost unlimited capabilities of extensions, which you can bring to the AI workspace of a user (they go through automated security checking pipeline).
2. You can offer in-chat services, which may be selected by user's Agent as cheaper, more efficient and higher quality option for a complicated task instead of burning billions of tokens to reinvent the wheel.
3. Builders get paid, from a shared revenue pool of premium users subscriptions, quite like X.

90% of platform revenue is going to creators of extensions and paid services providers, with an end goal of 100%.

Plan is simple, but not easy - if we could gather few dozens of builders to trust each other, group our audiences into one product - open-source AI workspace - boost our SEO by backlinking each other, maybe even crowdfund marketing expenses together to get through the marketing and audience wall - maybe we could spin up a platform to challenge the giants.

Github: https://github.com/intentic/intentic (free and open-source, contributions are welcome)

Website: https://intentic.dev/earn/

Hey, I'm creator of a unique AI workspace where creators of extensions, skills, tools and API service providers - earn money.

Pretty much anyone who is paying for subscription, is directly funding creators of everything that makes AI in that workspace get further with it's job - and execute complex, e2e tasks, much cheaper, faster and safer.

Buying airplane ticket? Translating 1000 pages of documents to 20 languages? Users will just ask their AI to do it, credits will be deducted from user and providers of services will earn money.

With other builders we can bridge the gap between intent and outcome - to a bare minimum, requiring as little from user as it's only possible, while not locking him in a captured ecosystem.

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I'm a professional (not a vibe-coding amateur), but TikTok, YouTube and social media have never been my world.

Writing here in hope to find a professional like me, but on that marketing angle (or influencer), that would be interested in taking look at the platform, evaluating if they would believe in it's success.

Year ago I wouldn't accept LLMs code quality. But since Opus 4.6, given you follow best practices, you can produce manageable codebases.

I code intensively with LLMs (over 10b tokens in last 7 days), but at the same time I want the code to be good and under control.

To achieve that, I needed better observability, understanding and control on work of agent.

So I have built an Agentic IDE, where your agents can code in parallel, while you stay in control:

- Each sandbox (you can run many per machine) is a separate docker container, allowing agent to know exactly what tools it has. You can connect into sandbox many model provider accounts.

- Each sandbox can run listener engines and spin up agentic session on event - discord tag, CI/CD events, schedule etc.

- Each agent (you can run many per sandbox) works in separate worktree.

- Entire state inside a sandbox is git-reviewable.

- Agents can extend their own sandbox (submit new dockerfile for approval) - resulting in predictable, understandable and replicable development environment.

- It all comes with a extension-based UI with content derived from file-system inside a sandbox. You see everything that agent sees - in a nicer UI.

Feel free to tinker with it (help me find bugs!) or be the first to create extension.

https://intentic.dev/ - You can see a live demo of UI you get to operate your sandbox.

For some time I've been trying to replace myself with LLMs and reduce my role to approvements on actions and accountability.

For context, I'm doing coding and DevOps tasks and I'm working on multiple projects at once. Each project is different, separate, needs different VPNs, access, tools and contexts.

The simplest thing I could do was to spin up few VSCode's with Claude Code in proper directories, each with proper context, tools and access and keep my PC 24/7 on - and on top of that add daemon listening to triggers (tagging on discord, incoming emails and so on).

The were few problems with that:

- 24/7 would not be too reliable when run on my personal workstation,

- Possible conflicts between agents doing unrelated stuff, while sharing environment without any separation,

- CPU/memory intensive,

- I could not invite anybody easily to check the setup of agents or cowork with them in my context, nor share the solution or scale it so that my coworkers could copy it,

- Messaging such agent from mobile was not granted,

- Lack of good visibility tooling for entire setup (that one could be solved by VSCode extensions though).

I decided to go all in and built an entire IDE around that. IDE primarily for agent (to improve it's work, token efficiency and so on) - but with great UI for human to check out on him, inspect and debug. I've picked following trade-offs:

1. To separate each agent and be able to easily and in replicable way prepare their environments I used docker - cheap, lightweight, familiar. Far from "perfect secure AI environment", but good enough.
2. Inside each docker I needed something like VSCode - IDE that would let me drop there files, skills, grant access, install tools, connect AI subscriptions etc. and have some visibility on what agent sees and what's happening inside his docker world for debuggability. VSCode Server would be an overkill and at the same time miss few bits, so instead I developed API for management of files and all that stuff and packaged it into the image.
3. Finally, I needed UI, so I made a website with UI allowing me to connect to sandboxed and switch between them.

At this point, the result is essentially a docker sandbox that agent lives inside with API for it's management and supervision.

I am curious if there are existing tools that already solve most of this problem and that I may have overlooked?

For some time I've been trying to replace myself with LLMs and reduce my role to approvements on actions and accountability.

For context, I'm doing coding and DevOps tasks and I'm working on multiple projects at once. Each project is different, separate, needs different VPNs, access, tools and contexts.

The simplest thing I could do was to spin up few VSCode's with Claude Code in proper directories, each with proper context, tools and access and keep my PC 24/7 on - and on top of that add daemon listening to triggers (tagging on discord, incoming emails and so on).

The were few problems with that:

- 24/7 would not be too reliable when run on my personal workstation,

- Possible conflicts between agents doing unrelated stuff, while sharing environment without any separation,

- CPU/memory intensive,

- I could not invite anybody easily to check the setup of agents or cowork with them in my context, nor share the solution or scale it so that my coworkers could copy it,

- Messaging such agent from mobile was not granted,

- Lack of good visibility tooling for entire setup (that one could be solved by VSCode extensions though).

I decided to go all in and built an entire IDE around that. IDE primarily for agent (to improve it's work, token efficiency and so on) - but with great UI for human to check out on him, inspect and debug. I've picked following trade-offs:

1. To separate each agent and be able to easily and in replicable way prepare their environments I used docker - cheap, lightweight, familiar. Far from "perfect secure AI environment", but good enough.

2. Inside each docker I needed something like VSCode - IDE that would let me drop there files, skills, grant access, install tools, connect AI subscriptions etc. and have some visibility on what agent sees and what's happening inside his docker world for debuggability. VSCode Server would be an overkill and at the same time miss few bits, so instead I developed API for management of files and all that stuff and packaged it into the image.

3. Finally, I needed UI, so I made a website with UI allowing me to connect to sandboxed and switch between them.

At this point, the result is essentially a docker sandbox that agent lives inside with API for it's management and supervision.

I am curious if there are existing tools that already solve most of this problem and that I may have overlooked?

I'm a devoted builder, seeking perfection in whatever I chose to build. My focus is on that and that only.

But when I finish building, there is a wall. I'd like to share my work, even for free. I'd like somebody to tell me that it's trash. Or that the problem I "solved" is not real and I was hallucinating all the time. Any-fucking-thing.

Instead - there is always silence, 0 comments, sometimes ban or downvotes. And almost always on reddit, 1s after I post I get like automatic downvote (wtf?).

On X nobody "downvotes", but nobody responds either. For last few months I've been eagerly responding to popular people posts in related topics within minutes and managed to earn 8 followers.

I'm not using bot automation to post and reply everywhere as this seems quite unfair and defeats the purpose of social media - but I'm starting to think that this and paid marketing is the only way.

Did you also go through such experience? Did anyone, who genuinely in heart hates marketing, actually broken such wall without help from outside?

I wanted to move off of VSCode for quite some time. It's great for coding, but not for supervising army of agents.

What matters to me now is architecture, dependencies, scripts I need to run. Managing multiple sessions efficiently. And I want my IDE to run when I sleep and respond to my co-workers on chats.

Meanwhile, most of Agentic IDE's just give you left sidebar with sessions and message-box - VOILA. And ofc. connectors to give LLM access to systems.

Where are the logs when something goes wrong? How can I inspect if during my agentic session LLM faced some serious issues related to missing tools? What it installed on the way?

The "message box" model falls apart to me because it’s a black box. So black, that as you progress, you loose understanding of a project on any other level than UI you see.

So I built a white-box IDE designed specifically to fix the observability gap in agentic coding.

Instead of hiding the execution environment, I built it to expose what matters:

• Live Terminal Streams: You can watch the agent's exact terminal executions in real-time.
• Process & Port Monitoring: You can see exactly what processes the agent has spun up and what ports are bound in its environment.
• Tool Call Diagnostics: Total visibility into why a specific agent action failed so you can intervene, instead of letting it guess and break things further.
• And much, much more (pretty much everything VSCode has that's relevant nowadays).

It’s built for developers who want the efficiency of AI, but refuse to give up control and state visibility. And those, who want to eventually connect their solid workspace to slack/discord and allow co-workers to interact with it as well - while you're still supervising what agent acts on.

I'm looking for builders who would like to give it a shot.

I'm also curious what would make you switch from VSCode, T3Code, Cursor or whatever you're using now to another IDE?

BTC solved one problem cleanly: agreeing on who owns the value without a trusted third party. That's the main web3 achievement to this day.

Everything else quietly brings trust through the side door - and does it poorly.

We can prove a transaction was signed and included in a block, cool, but we cannot prove that anything happened off-chain. That makes solution useless for anything that is expected to cause any effect outside of blockchain.

Lack of meaning and even more importantly - lack of consequences for how out-of-blockchain interactions end, turns web3 into casino and scam-center (outside of strong proofs of history, timestamping etc.).

Some solutions try to incentive people by staking tokens to perform certain operations, but trust and money are not the same. Trust system optimizes for trustworthiness over iterated interactions. A pure economic incentive system filters for whoever extracts value fastest by whatever means the rules permit.

Web3 solutions too often reject identity & trust as their central point, effectively rejecting to bring a neutral playing field. That's a replacement of the "lack of trust" to governments, with "let's interact fully anonymously", where each interaction outside of chain is a "will I be scammed or actually get what I paid for" question.

BTC works because it never tried to be anything else than a provable store of data.

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What are we to make out of this? Admit that the central problem is trust - how, across many different interactions with people, platforms, services and posts on the internet, could we trust information and outcomes from specific identities.

And this is not simple in era, where for each legitimate, unique human, you might have hundreds of bots and almost undistinguishable AI actors.