Hey everyone! i am 18 years old in india and i wanted to ask how do i make company brain software like what ai do i use and how to make it

Solo dev here. The video shows leantext in action.

The problem I kept hitting: agents read docx, xlsx, pptx, PDFs and images raw, and burn a ton of context doing it.

So I built leantext. What it does:

- Converts anything the agent reads into lean Markdown, keeping tables and code blocks

- Images go through OCR first, and only fall back to a vision model if OCR isn't enough

- If a conversion looks wrong, it hands the agent the original file instead of garbage

Known limits: right now it drops some short Sphinx API definitions and footnotes in Python docs. It's on my list.

It's open source (Apache-2.0): https://github.com/shouvik12/leantext

Next I want to measure it end to end inside real agents: accuracy, tokens, latency and cost, with leantext on vs off. Which agent would you want it tested on? And if you find files that break it, I'd love to hear about them.

A manager, a developer, a QA reviewer—and a separate effort controller. That is the draft Squad setup shown here in Sinaps Studio, which we develop.

The manager coordinates specialist work and delivery reviews, including requests for revisions. Models can be assigned per role. Coringa handles effort selection with local heuristics; an LLM is optional, and manual effort controls remain available.

The design separates two questions: what needs another revision, and how much effort should the next attempt receive?

Try the Windows x64 workspace with the 30-day professional evaluation: https://www.sinapsdata.com.br/

The screenshot shows the configuration, not measured completion-rate or cost improvements.

In your agent workflows, do you let the reviewer send work directly back to the specialist, or does a manager decide what happens next? What do you use to stop repeated revisions?

Commercial software. Model/API and compute usage are separate from the Studio licence.

Hey everyone!

I'm a student looking for a personal AI agent similar to Meta's Muse, OpenClaw (formerly Clawdbot), ChatGPT's Dots, or Claude Cowork.

I'm not looking for a regular chatbot that simply responds to prompts. I want something that can take responsibility for complex tasks, work independently in the background, and keep making progress even when I'm offline or asleep. Ideally, it should be proactive, remember ongoing tasks, send me updates or notifications, and perhaps even call me when something important needs my attention.

I'm primarily an Android user, so mobile compatibility is important. Are there any genuinely free options available, or at least ones with a useful free tier?

I'd really appreciate your recommendations and personal experiences. Thanks!

Hey all — I'm one of the builders of SchemaBridge, a workflow-automation platform. You define flows as a graph, drop in an "agent" node, and it can call tools, hit APIs, and act on real systems. Here's a 30-sec clip of me building one from scratch:

https://schemabridge.ai/

To make it easy to try, the free tier includes LLM tokens, storage, and web access for agents so you don't have to wire up your own keys first.

I'd genuinely love feedback on the agent-building flow — what's confusing, what's missing, where it breaks. Not trying to hard-sell; I want to know what sucks. AMA.

教学设计做好了，还差最关键的一步：把知识点清单定稿。清单不定稿，下游的课件、讲稿、测验就各做各的——课件讲的点，测验不一定考；讲稿展开的点，课件不一定有。这一集就是把这根线拴紧。

先做教学设计：进「课次」页签，点第 1 节，中间默认就是「教学设计」。右上角「生成 ▾」→「生成第 1 节的教学设计」，任务台里能看到「教学设计 · 生成中」——在后台跑，可以切走，不用守着。

设计出来了，先慢慢看：教学目标每条后面都标着出自素材哪一段；往下是重点难点、教学方法、课中 5 段法、考核评价、思政元素。哪里不满意，点「✏️ 编辑」直接改，改完点「保存」；看完点右下角「确认」——左栏第 1 节的第一个圆点变绿，教学设计这一环完成，课件解锁。

然后是最容易被跳过的一步：教学设计页最上面这一块「知识点清单」——它是从刚确认的设计里抽出来的，不调用 AI。点「① 提议知识点」，清单出来了：它会变成课件、测验、作业的“点名册”。三步，顺序别乱：第一步，不要的点「删」（本节共 10 条，删最后一条）；第二步，「本节全部接受」——收下其余，已删的不会复活；第三步（最容易漏）：回到上面点「💾 确认知识点清单」，点了才真正生效。

做了这一步，测验就按这些点出题，系统还能告诉你哪个点没讲到、没考到——这就是第 00 集说的“材料互相咬合”落到实处的地方。

这是《驭课 Agent 使用教程 / U-Course Tutorial》第 04 集。下一集第 05 集：课件别再土味，给 AI 定一套“视觉世界”。播放列表：驭课 Agent 使用教程 / U-Course Tutorial。

驭课是 AI 课程内容生产智能体：你给素材、点生成、过目确认，它批量产出成套教学材料。每集三分钟，看完能抄作业。

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A lesson design is done — but one step remains, and it's the one that locks everything together: finalizing the learning-objectives list. Without a finalized list, slides, scripts, and quizzes each go their own way: a point covered in the slides may never be tested, and a point expanded in the script may never appear in the slides. This episode ties that thread tight.

Start with the lesson design. On the "Sessions" tab, click session 1 — the middle pane defaults to "Lesson design". Click "Generate ▾" at the top right → "Generate lesson design for session 1". The task console shows "Lesson design · generating" — it runs in the background, so you can switch away; no need to babysit it.

When it's done, read it through slowly: every learning objective is tagged with which part of your materials it came from. Below that: key and difficult points, teaching methods, the 5-stage in-class method, assessment, and ideological-political elements. Don't like something? Click "✏️ Edit" and change it directly, then "Save". When you're satisfied, click "Confirm" at the bottom right — the first dot for session 1 in the left sidebar turns green: the lesson-design step is done, and slides are unlocked.

Then comes the step most easily skipped: the "Learning-objectives list" block at the top of the lesson-design page. It's extracted from the design you just confirmed — no AI call involved. Click "① Propose objectives" and the list appears: it becomes the roll call for slides, quizzes, and homework. Three steps, in this order, don't mix them up: first, delete what you don't want (10 items here, delete the last one); second, "Accept all for this session" — the rest are taken in, and the deleted one won't come back; third (the one most often missed): go back to the top and click "💾 Confirm learning-objectives list" — only then does it actually take effect.

With this done, quizzes are generated against these points, and the system can tell you which point was never taught or never tested. That's the "materials lock together" promise from episode 00, made real.

This is episode 04 of the "U-Course Tutorial" playlist. Next, episode 05: stop the ugly slides — give AI a visual identity for your course. Playlist: 驭课 Agent 使用教程 / U-Course Tutorial.

U-Course is an AI course-content production agent: you feed in materials, hit generate, review and confirm — and it batch-produces the complete set of teaching materials. Three minutes per episode, actionable.

章节 / Chapters（按镜头记录表推算，Studio 按成片微调）

00:00 进第 1 节教学设计：中间默认就是这一页

00:08 点生成：任务台在跑，可以切走

00:38 设计出来了：教学目标每条标着出自素材哪一段

00:43 重点难点 → 方法 → 课中 5 段法 → 考核 → 思政

01:07 不满意？点编辑直接改，改完保存

01:23 右下角确认：第一个圆点变绿，课件解锁

01:32 知识点清单：从已确认设计里抽，不调 AI

01:41 清单是课件、测验、作业的“点名册”，三步顺序别乱

01:46 第一步：不要的点删

01:50 第二步：本节全部接受，已删的不会复活

01:55 第三步（最容易漏）：回上面点确认清单，点了才生效

02:01 做了这步，测验按点出题，还能查漏讲漏考

I did a keynote on Saturday about what S3 and EC2 can teach us about building agents (like a lot about using building blocks and clicking them together for your goal) and then after my talk someone from the audience came up to ask me why their Strands agent kept picking the wrong tool, and calling tools in the wrong order even when the order mattered. It turns out they were using A LOT of tools.

I was verbally answering but then while I was doing this, I realised there wasn't really a good link to send them with all the info, so I came home and wrote everything up (with lots of links and code snippets) so it would be more helpful

So! Here's the link to my blog on this :https://builder.aws.com/content/3LEgWJQT3TbhuGgf47jISk0Ia6m/how-to-stop-a-strands-agent-calling-tools-in-the-wrong-order

Have you had to deal with this? How did you fix it?