LemonAI

LemonAI is the world's first Full-stack Open-source General AI Agent.
Please visit to download the application.

[LemonAI @LemonAI_cc]

🍋 Lemon AI Agentic Space V1.0.0 is now live.

Lemon AI has evolved from a General AI Agent to an ALL-IN-ONE Agentic Space.

Why does this matter?
Because working with AI today still means switching tools:
Docs → Slides → Tables → Images → Code.
Context gets lost. Work breaks.

Agentic Space puts everything in one place.

🗂️Upload any knowledge (files, URLs, media).
⚡️One command, infinite outputs: reports, PPTs, tables, images, code, websites.
🧠The Agent learns, accumulates knowledge, and self-evolves.

One Place of Knowledge. Infinite Agentic Possibilities.

👉 Try Lemon AI Agentic Space V1.0.0 : https://t.co/NzTeCExGic

#AI #AgenticAI #KnowledgeWork #ProductLaunch #AIAgents

[LemonAI @LemonAI_cc]

LemonAI Agentic Space V1.1.0 Release Notes
🛍️ 1. New Agents Space Store
Discover · Reuse · Recreate — Build Your Own Agentic Space
Browse team curated and community created Agent Spaces
One-click Remix to quickly clone spaces from others into your own Agentic Space
Freely select or deselect source files to flexibly customize content and accelerate creation -- truly innovate by standing on the shoulders of giants
How to use
Choose an Agent Space you’re interested in from the Store
Click Remix to convert it into your personal space
Select or unselect files to inherit in the Source file list
Start writing prompts and start building immediately—seamlessly create and iterate on top of the new space

🔍 2. New Explore Feature
Discover Creativity · Spark Inspiration · Recreate Instantly
Explore is a creative showcase designed for LemonAI users, bringing together outstanding works from both the community and the Lemon AI team.
Discover a wide range of content created with LemonAI, including webpages, documents, images, and videos
Quickly search for content using keywords
One-click add any work to your Agent Space, automatically converting it into source files so you can continue creating and iterating right away
How to use
Click Explore in the left sidebar
Browse recommended content or search using keywords
Click a content card to view the details
Click Add and choose the target Agent Space
Enter your prompt and begin an efficient, intelligent second round of creation
🧠 3. New MessageV2 Design with an Updated Message Format

Extracted MessagePublisher.js to centrally manage the stream output of messages and the record storage
Fully compatible with rendering and displaying legacy message formats
Unified backend handling for message delivery and interpretation
Refactored frontend parsing, processing, and rendering logic to support the new structure
⚡ 4. Stream Message Output & Display Enhancements
Optimized LLM output parsing, improved XML parsing logic, and enabled real-time parsing during stream output, dynamically render different message types on the frontend based on detected actions

Display code generation progress on the right panel during write_code actions
Display search result summarization in real time during search actions
Stream output task summary content
Enhanced terminal view to display full commands and outputs, support error message displays, and improve overall layout and readability

[LemonAI @LemonAI_cc]

Congrats to Manus and the Meta team.
Manus has long been a benchmark for us.
At Lemon AI, we’re focusing on open, self-evolving agents that learn from your knowledge, grow with your skills, and know you better every day.
Excited to watch this next chapter unfold. 🍋

[Alexandr Wang @alexandr_wang]

Excited to announce that @ManusAI has joined Meta to help us build amazing AI products!

The Manus team in Singapore are world class at exploring the capability overhang of today’s models to scaffold powerful agents.

Looking forward to working with you, @Red_Xiao_!

[LemonAI @LemonAI_cc]

Manus × Meta 🤝
Congrats to Manus on joining Meta. We respect Manus and have learned from them.
Lemon AI is focused on a complementary vision — open, self-evolving AI agents that learn from your knowledge, grow with your skills, and know you better every day.
An AI agent that solves real pain points. That’s how we serve our users better — long term. 🍋

[Manus @ManusAI]

Manus is entering the next chapter: we’re joining forces with Meta to take general agents to the next level.

Full story on our blog: https://t.co/huPrnbITCi

[LemonAI @LemonAI_cc]

Spot on. But the magic really happens when these types converge.

A 'Self-Directed' agent needs to be 'Tool-Augmented' to be useful, and 'Reflective' to grow. We view the future not just as individual agents, but as a collaborative workspace where humans and agents co-evolve.

Stop chatting, start building. 🚀

[Suryansh Tiwari @Suryanshti777]

Most people are still stuck "chatting" with AI.
The top 1%? They are building AI
Agents.

If you don't understand the difference, you are about to become obsolete

Here are the 5 types of AI Agents that will run the world (and how they work): 🧵👇

[LemonAI @LemonAI_cc]

Want to turn scattered information into a beautifully structured blog website — in just minutes?

In this demo, we show how to use Lemon AI Agentic Space to generate a complete blog webpage from simple profile information.
With just one prompt, Lemon AI automatically creates a rich, well-designed blog page including:
✅ Personal Bio & Achievements
✅ Company Ecosystem
✅ Core Products

You can even continue chatting with Lemon AI to refine, expand, and optimize your blog page until it’s exactly how you want it.
👉 Try Lemon AI Agentic Space and build your blog smarter, faster, and better.

[LemonAI @LemonAI_cc]

Christmas mood: ACTIVATED. 🎄🎅

Check this out: generating a fully festive, Christmas-themed webpage in seconds using Lemon AI Agentic Space.
We just gave the official Lemon AI website an instant holiday makeover!

Sprinkle some holiday magic on your workflow this Christmas.
What would you build? 🎁

#Christmas2025 #Christmas #AI #aiagent #NoCode

[LemonAI @LemonAI_cc]

Stop drowning in meeting notes and scattered tabs.
Introducing the all-new Lemon AI Agentic Space — your true intelligent work partner. 🍋✨

In this step-by-step walkthrough, watch how I turn raw meeting history and web sources into polished reports, infographics, and videos in seconds.
Not just a chat, but a complete workflow automation.

✅ Create dedicated Agentic Spaces
✅ One-click source integration
✅ Instant generation of Reports, Pages & Visuals

Experience the new way of knowledge work. 👇https://t.co/NzTeCExGic

[LemonAI @LemonAI_cc]

🍋 LEMON AI AGENTIC SPACE V1.0.0 IS LIVE! 🚀
Say goodbye to tool-switching chaos. We've evolved from a General AI Agent to your ALL-IN-ONE Intelligent Agentic Workspace!

Key Highlights:
✨ Agentic Knowledge Space: Unify all your knowledge (personal + web) in one self-evolving space.
🧠 Automated Agentic RAG: Effortless processing of all file types (audio, video, data) with deep content parsing.
🛠️ Agentic OS Deep Integration: Full toolbox access for infinite output (HTML, PPT, Images, etc.).
🖥️ New Space Interface: Streamlined 3-Column Layout for superior project organization.

Ready to experience the future of intelligent work? 👉 Explore Lemon AI now: https://t.co/NzTeCExGic

#LemonAI #AgenticSpace #AIAgent #RAG #AIWorkspace

[LemonAI @LemonAI_cc]

If your IDE doesn't have an Agent Manager, you're still coding in the past.

Google Antigravity is showing us that the Agent is now the first-class citizen in the development workflow. The Editor and Browser are just tools for the Agent to use.

This is the practical application of the Tiered Context Model we've been discussing. Watch this video.
#AI #DeveloperTools #AgenticWorkflow #LLM

[Google Antigravity @antigravity]

What does an agent first IDE look like?

Our Head of Product Engineering breaks down the unique interaction surfaces that make Antigravity work: the Editor, the Browser, and the Agent Manager.

[LemonAI @LemonAI_cc]

The era of Prompt Engineering is over. Welcome to the age of Context Engineering.

Google's ADK framework reveals the profound truth: scaling multi-agent systems isn't about bigger context windows; it's about treating context as a compiled, stateful system. This diagram breaks down the Tiered Model (Storage, Session, Memory, Artifacts) and the Compiler Pipeline (Flows & Processors).

This is the blueprint for reliable, debuggable, production-grade AI. If you're building Agents, this is your new architecture.

Infographic powered by LemonAI.

[LemonAI @LemonAI_cc]

The future of social media management is already here. This Chinese operation shows what's possible with AI agents at scale. We're pushing the boundaries even further with our next-generation platform that combines automation with genuine engagement strategies.

[Damian Player @damianplayer]

Chinese AI agents are running 50+ social media accounts on autopilot. 24/7.

they’re producing content at a scale you physically cannot match yourself.

this is your competition now.

the games changed and most people HAVEN’T noticed.

adapt or die. no other choice.

[LemonAI @LemonAI_cc]

We gave Lemon AI a challenge: modify a complex t-SNE plot showing mRNA sequences from multiple species.

The result was impressive. Lemon AI added a new data cluster (in orange) and accurately labeled it with its scientific name, Mus musculus.

This is a glimpse into a future where researchers can interact with their data more dynamically than ever before.🔬

#research #AI #AgenticAI

[LemonAI @LemonAI_cc]

Lemon AI must have watched Zootopia 47 times to steal Nick's entire business model for selling pawpsicles. 🍦🦊
Make infographics with Lemon AI today: https://t.co/npYhhQitxv

#Zootopia #Zootopia2 #Disney #imageGeneration #nanobanana

[Akshay 🚀 @akshay_pachaar]

RAG was never the end goal.

Memory in AI agents is where everything is heading. Let me break down this evolution in the simplest way possible.

RAG (2020-2023):

- Retrieve info once, generate response
- No decision-making, just fetch and answer
- Problem: Often retrieves irrelevant context

Agentic RAG:

- Agent decides *if* retrieval is needed
- Agent picks *which* source to query
- Agent validates *if* results are useful
- Problem: Still read-only, can't learn from interactions

AI Memory:

- Read AND write to external knowledge
- Learns from past conversations
- Remembers user preferences, past context
- Enables true personalization

The mental model is simple:

↳ RAG: read-only, one-shot
↳ Agentic RAG: read-only via tool calls
↳ Agent Memory: read-write via tool calls

Here's what makes agent memory powerful:

The agent can now "remember" things - user preferences, past conversations, important dates. All stored and retrievable for future interactions.

This unlocks something bigger: continual learning.

Instead of being frozen at training time, agents can now accumulate knowledge from every interaction. They improve over time without retraining.

Memory is the bridge between static models and truly adaptive AI systems.

But it's not all smooth sailing.

Memory introduces new challenges RAG never had: memory corruption, deciding what to forget, and managing multiple memory types (procedural, episodic, and semantic).

Solving these problems from scratch is hard. If you want to give your agents human-like memory, check out Graphiti - an open-source framework for building real-time knowledge graphs.

You can find the link in the next tweet!

[LemonAI @LemonAI_cc]

Lemon AI got its hands on an HTML game called the "Battle of Cells" and reverse-engineered it.

Just prompt "clone this game" and drop a URL.
The Lemon AI agent planned the entire job -- extracted the source, rebuilt the logic.
Now you have a fully playable game. No coding skills required.

Try recreating your own game at https://t.co/NzTeCExGic.

[LemonAI @LemonAI_cc]

Not sure which stocks to invest in? Let an AI agent find the opportunities for you. ��

Simply tell Lemon AI what you're looking for. It autonomously analyzes market data, screens top stocks, and builds a comprehensive HTML report.

No code. No manual research. Just actionable insights. See how it's done in our new video! https://t.co/EGmqnT6NX7