• "AI Landscape 2025" provides a comprehensive overview of various AI tools and agents, categorizing them into 14 distinct groups such as AI Agent Builders, Coding, and Productivity, among others. It outlines the number of available tools within each category, highlighting the expansive growth and diversification in the AI sector. The document also notes the pricing models for these AI tools, indicating options for free, paid, and hybrid pricing structures.

    Key Points
    - The document categorizes AI tools into 14 different groups including AI Agent Builders, Coding, and Productivity.
    - A total of 138 tools are dedicated to AI Agent Builders, demonstrating a significant focus on developing intelligent agents.
    - There are 94 tools available for coding, showcasing the increasing integration of AI in software development.
    - Productivity tools number 43, indicating a growing market for AI-driven efficiency solutions.
    - Categories like Finance and Marketing have 16 and 22 tools respectively, reflecting AI's penetration into business operations.
    - The document mentions different pricing structures: free, paid, and a combination of both for various tools.
    - A diverse range of applications is identified, from Customer Service (39 tools) to Digital Workers (41 tools), emphasizing the versatile uses of AI technologies.

    https://aiagentslist.com/ai-agents-map
    https://aiagentslist.com/mcp-servers

    #AILandscape2025 #AITools #AIAgents #AIAgentBuilders #AICodingTools #AIProuctivityTools #FinanceAI #MarketingAI #CustomerServiceAI #DigitalWorkers #AIpricing #FreeAI #PaidAI #HybridAI #GPTs #AutoGPT #BabyAGI #AIgrowth #AIadoption
    "AI Landscape 2025" provides a comprehensive overview of various AI tools and agents, categorizing them into 14 distinct groups such as AI Agent Builders, Coding, and Productivity, among others. It outlines the number of available tools within each category, highlighting the expansive growth and diversification in the AI sector. The document also notes the pricing models for these AI tools, indicating options for free, paid, and hybrid pricing structures. Key Points - The document categorizes AI tools into 14 different groups including AI Agent Builders, Coding, and Productivity. - A total of 138 tools are dedicated to AI Agent Builders, demonstrating a significant focus on developing intelligent agents. - There are 94 tools available for coding, showcasing the increasing integration of AI in software development. - Productivity tools number 43, indicating a growing market for AI-driven efficiency solutions. - Categories like Finance and Marketing have 16 and 22 tools respectively, reflecting AI's penetration into business operations. - The document mentions different pricing structures: free, paid, and a combination of both for various tools. - A diverse range of applications is identified, from Customer Service (39 tools) to Digital Workers (41 tools), emphasizing the versatile uses of AI technologies. https://aiagentslist.com/ai-agents-map https://aiagentslist.com/mcp-servers #AILandscape2025 #AITools #AIAgents #AIAgentBuilders #AICodingTools #AIProuctivityTools #FinanceAI #MarketingAI #CustomerServiceAI #DigitalWorkers #AIpricing #FreeAI #PaidAI #HybridAI #GPTs #AutoGPT #BabyAGI #AIgrowth #AIadoption
    AI Technology Landscape 2025 - Interactive Map of AI Tools
    aiagentslist.com
    Navigate the AI ecosystem with our interactive landscape map. Compare 593+ AI tools and agents, discover alternatives, and find the perfect AI solutions for your needs. Updated for 2025.
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  • Source: Post by Rakesh Gohel on Linkedin

    AI Agent trends have drastically changed from 2024 to 2025

    Here are the new trends driving innovation this year....

    The Agentic AI field is constantly moving forward with new innovations and products.

    I'll share with you a few notable trends that are driving the market in 2025.

    Note: I've also included a few Langgraph codebooks if you want to build some of these solutions yourself.

    Agentic RAG
    - AI Agent workflow for reasoning-based real-time data retrieval and generation.
    - Agentic RAG is not limited to one use case but rather used in health care as well.
    - Used by companies like Perplexity, Harvey AI and Glean AI.

    Voice Agents
    - Intelligent agents that interact with users through natural spoken language utlizing a wide range of TTS and STTS embedding and Retrieval.
    - Used by companies like ElevenLabs, Cognigy, Vapi and Deepgram.

    AI Agent Protocols
    - Streamlining Multi-Agent Communication that supports communication between Agents built in different frameworks.
    - Used by Companies like Accenture, the top players include A2A, ACP, SLIM and others.

    CUA(Computer Using Agents)
    - AI agents that can interact with a computer the way a human does utilizing tools like a browser, CLI and even a mouse's cursor.
    - Used by Companies like OpenAI for their Operator, Claude's Computer Use, Runner H by H-Company and Manus AI.

    Coding Agents
    - Multi-Agents for building and debugging applications 10x faster with the help of clever tool use and LLM-based code gen.
    - Used by companies like Windsurf, Cursor and GitHub Copilot.

    Deepresearch Agents
    - Collaborative Multi-Agent system to build extensively researched reports from a large number of sources.
    - Popular products include Gemini DR, OpenAI DR and You(.)com DR.

    Few Langgraph Codebooks to build some of the trending solutions

    1. Agentic RAG: https://lnkd.in/gdqWyP3r
    2. CUA: https://lnkd.in/gCdxpUBi
    3. Deepresearch: https://lnkd.in/gexsW5qh
    4. Code Gen Agents using RAG: https://lnkd.in/gDnsBFuM

    After months of feedback and iteration, we are finally releasing our first technical cohort, "AI Agent Engineering"

    Enrol here: https://lnkd.in/gDEPcXBB

    If you are a business leader, we've developed frameworks that cut through the hype, including our five-level Agentic AI Progression Framework to evaluate any agent's capabilities in my latest book.

    Book info: https://amzn.to/4irx6nI

    Save โžž React โžž Share

    & follow for everything related to AI Agents

    https://www.linkedin.com/posts/rakeshgohel01_ai-agent-trends-have-drastically-changed-activity-7343981787842297858-PJkS

    #agenticrag #voiceagents #aiagentprotocols #cua #codingagents #deepresearchagents #langgraph #elevenlabs #cognigy #perplexity #harveyai #gleanai #openai #cursor #githubcopilot #geminidr #youcom #windsurf #a2a #acp #slim #tts #sts #rag #multiagent #aiagents #llm #browserautomation #aicoding
    Source: Post by Rakesh Gohel on Linkedin AI Agent trends have drastically changed from 2024 to 2025 Here are the new trends driving innovation this year.... The Agentic AI field is constantly moving forward with new innovations and products. I'll share with you a few notable trends that are driving the market in 2025. Note: I've also included a few Langgraph codebooks if you want to build some of these solutions yourself. ๐Ÿ“Œ Agentic RAG - AI Agent workflow for reasoning-based real-time data retrieval and generation. - Agentic RAG is not limited to one use case but rather used in health care as well. - Used by companies like Perplexity, Harvey AI and Glean AI. ๐Ÿ“Œ Voice Agents - Intelligent agents that interact with users through natural spoken language utlizing a wide range of TTS and STTS embedding and Retrieval. - Used by companies like ElevenLabs, Cognigy, Vapi and Deepgram. ๐Ÿ“Œ AI Agent Protocols - Streamlining Multi-Agent Communication that supports communication between Agents built in different frameworks. - Used by Companies like Accenture, the top players include A2A, ACP, SLIM and others. ๐Ÿ“Œ CUA(Computer Using Agents) - AI agents that can interact with a computer the way a human does utilizing tools like a browser, CLI and even a mouse's cursor. - Used by Companies like OpenAI for their Operator, Claude's Computer Use, Runner H by H-Company and Manus AI. ๐Ÿ“Œ Coding Agents - Multi-Agents for building and debugging applications 10x faster with the help of clever tool use and LLM-based code gen. - Used by companies like Windsurf, Cursor and GitHub Copilot. ๐Ÿ“Œ Deepresearch Agents - Collaborative Multi-Agent system to build extensively researched reports from a large number of sources. - Popular products include Gemini DR, OpenAI DR and You(.)com DR. ๐Ÿ”— Few Langgraph Codebooks to build some of the trending solutions 1. Agentic RAG: https://lnkd.in/gdqWyP3r 2. CUA: https://lnkd.in/gCdxpUBi 3. Deepresearch: https://lnkd.in/gexsW5qh 4. Code Gen Agents using RAG: https://lnkd.in/gDnsBFuM ๐Ÿ“Œ After months of feedback and iteration, we are finally releasing our first technical cohort, "AI Agent Engineering" ๐Ÿ”— Enrol here: https://lnkd.in/gDEPcXBB If you are a business leader, we've developed frameworks that cut through the hype, including our five-level Agentic AI Progression Framework to evaluate any agent's capabilities in my latest book. ๐Ÿ”— Book info: https://amzn.to/4irx6nI Save ๐Ÿ’พ โžž React ๐Ÿ‘ โžž Share โ™ป๏ธ & follow for everything related to AI Agents https://www.linkedin.com/posts/rakeshgohel01_ai-agent-trends-have-drastically-changed-activity-7343981787842297858-PJkS #agenticrag #voiceagents #aiagentprotocols #cua #codingagents #deepresearchagents #langgraph #elevenlabs #cognigy #perplexity #harveyai #gleanai #openai #cursor #githubcopilot #geminidr #youcom #windsurf #a2a #acp #slim #tts #sts #rag #multiagent #aiagents #llm #browserautomation #aicoding
    AI Agent trends have drastically changed from 2024 to 2025 | Rakesh Gohel
    www.linkedin.com
    AI Agent trends have drastically changed from 2024 to 2025 Here are the new trends driving innovation this year.... The Agentic AI field is constantly moving forward with new innovations and products. I'll share with you a few notable trends that are driving the market in 2025. Note: I've also included a few Langgraph codebooks if you want to build some of these solutions yourself. ๐Ÿ“Œ Agentic RAG - AI Agent workflow for reasoning-based real-time data retrieval and generation. - Agentic RAG is not limited to one use case but rather used in health care as well. - Used by companies like Perplexity, Harvey AI and Glean AI. ๐Ÿ“Œ Voice Agents - Intelligent agents that interact with users through natural spoken language utlizing a wide range of TTS and STTS embedding and Retrieval. - Used by companies like ElevenLabs, Cognigy, Vapi and Deepgram. ๐Ÿ“Œ AI Agent Protocols - Streamlining Multi-Agent Communication that supports communication between Agents built in different frameworks. - Used by Companies like Accenture, the top players include A2A, ACP, SLIM and others. ๐Ÿ“Œ CUA(Computer Using Agents) - AI agents that can interact with a computer the way a human does utilizing tools like a browser, CLI and even a mouse's cursor. - Used by Companies like OpenAI for their Operator, Claude's Computer Use, Runner H by H-Company and Manus AI. ๐Ÿ“Œ Coding Agents - Multi-Agents for building and debugging applications 10x faster with the help of clever tool use and LLM-based code gen. - Used by companies like Windsurf, Cursor and GitHub Copilot. ๐Ÿ“Œ Deepresearch Agents - Collaborative Multi-Agent system to build extensively researched reports from a large number of sources. - Popular products include Gemini DR, OpenAI DR and You(.)com DR. ๐Ÿ”— Few Langgraph Codebooks to build some of the trending solutions 1. Agentic RAG: https://lnkd.in/gdqWyP3r 2. CUA: https://lnkd.in/gCdxpUBi 3. Deepresearch: https://lnkd.in/gexsW5qh 4. Code Gen Agents using RAG: https://lnkd.in/gDnsBFuM ๐Ÿ“Œ After months of feedback and iteration, we are finally releasing our first technical cohort, "AI Agent Engineering" ๐Ÿ”— Enrol here: https://lnkd.in/gDEPcXBB If you are a business leader, we've developed frameworks that cut through the hype, including our five-level Agentic AI Progression Framework to evaluate any agent's capabilities in my latest book. ๐Ÿ”— Book info: https://amzn.to/4irx6nI Save ๐Ÿ’พ โžž React ๐Ÿ‘ โžž Share โ™ป๏ธ & follow for everything related to AI Agents | 134 comments on LinkedIn
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  • Amazon's cloud unit introduced Kiro, an AI-assisted coding program, aiming to transform software development. This comes shortly after Google announced hiring staff from AI coding startup Windsurf under a $2.4 billion deal and plans to enhance its Gemini AI for developers. Both Amazon and Google are advancing "vibe coding," while Microsoft updated Visual Studio Code for automated development. Kiro helps manage complexity in vibe coding by defining requirements and tasks before coding, and can create flow diagrams and task lists. Currently, Kiro supports only English, with more languages to come. There will be free and premium options post-preview, with strict privacy for paying users.

    https://kiro.dev/

    #Kiro #AWS #GeminiAI #Windsurf #VisualStudioCode #AICoding #VibeCoding #LowCode #NoCode #SoftwareDevelopment #AIDevelopment #AI #CloudComputing #AmazonAI #GoogleAI #Microsoft #FlowDiagram #TaskManagement #EnglishLanguage #PrivacyFocused #Programming #CodingTools
    Amazon's cloud unit introduced Kiro, an AI-assisted coding program, aiming to transform software development. This comes shortly after Google announced hiring staff from AI coding startup Windsurf under a $2.4 billion deal and plans to enhance its Gemini AI for developers. Both Amazon and Google are advancing "vibe coding," while Microsoft updated Visual Studio Code for automated development. Kiro helps manage complexity in vibe coding by defining requirements and tasks before coding, and can create flow diagrams and task lists. Currently, Kiro supports only English, with more languages to come. There will be free and premium options post-preview, with strict privacy for paying users. https://kiro.dev/ #Kiro #AWS #GeminiAI #Windsurf #VisualStudioCode #AICoding #VibeCoding #LowCode #NoCode #SoftwareDevelopment #AIDevelopment #AI #CloudComputing #AmazonAI #GoogleAI #Microsoft #FlowDiagram #TaskManagement #EnglishLanguage #PrivacyFocused #Programming #CodingTools
    Kiro
    kiro.dev
    The AI IDE for prototype to production
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  • Claims are awash on X about how the latest Kimi Model K2 beats Grok 4. My verdict ... try it for yourself ! l also noticed that some models are better in certain contexts than others but fail in other context where others excel. So my take is to know which is which for yourself .. don' t just rely on Benchmarks, social media posters and such ...

    Now back to Kimi AI the chinese controversial release:

    Kimi K2 is a state-of-the-art mixture-of-experts (MoE) language model with 32 billion activated parameters and 1 trillion total parameters. Trained with the Muon optimizer, Kimi K2 achieves exceptional performance across frontier knowledge, reasoning, and coding tasks while being meticulously optimized for agentic capabilities.

    Key Features
    Large-Scale Training: Pre-trained a 1T parameter MoE model on 15.5T tokens with zero training instability.
    MuonClip Optimizer: We apply the Muon optimizer to an unprecedented scale, and develop novel optimization techniques to resolve instabilities while scaling up.
    Agentic Intelligence: Specifically designed for tool use, reasoning, and autonomous problem-solving.
    Model Variants
    Kimi-K2-Base: The foundation model, a strong start for researchers and builders who want full control for fine-tuning and custom solutions.
    Kimi-K2-Instruct: The post-trained model best for drop-in, general-purpose chat and agentic experiences. It is a reflex-grade model without long thinking.

    https://github.com/MoonshotAI/Kimi-K2
    https://www.moonshot.ai/
    https://platform.moonshot.ai/docs/introduction#text-generation-model
    https://github.com/MoonshotAI/Kimi-K2/blob/main/docs/deploy_guidance.md(Deployment Guide)

    #KimiK2 #KimiAI #MoonshotAI #Grok4 #LLM #LargeLanguageModel #MoE #MixtureOfExperts #AI #AgenticAI #MuonOptimizer #AICoding #Chatbot #KimiK2Base #KimiK2Instruct #TextGeneration #FrontierKnowledge #Reasoning #AutonomousProblemSolving #TransformerModel #Claude #Gemini #GPT4 #OpenAI #Llama3 #AIModels #GitHub #X #SocialMedia #Benchmarks #ControversialRelease #ChineseAI #AIInnovation #DeepLearning #NaturalLanguageProcessing #NLP #AIResearch #AIML #MachineLearning #DataScience #ArtificialIntelligence #BigData #Technology #Innovation #Tech #AISolutions #DigitalTransformation #AICommunity #AINews #EmergingTech #TechTrends
    Claims are awash on X about how the latest Kimi Model K2 beats Grok 4. My verdict ... try it for yourself ! l also noticed that some models are better in certain contexts than others but fail in other context where others excel. So my take is to know which is which for yourself .. don' t just rely on Benchmarks, social media posters and such ... Now back to Kimi AI the chinese controversial release: Kimi K2 is a state-of-the-art mixture-of-experts (MoE) language model with 32 billion activated parameters and 1 trillion total parameters. Trained with the Muon optimizer, Kimi K2 achieves exceptional performance across frontier knowledge, reasoning, and coding tasks while being meticulously optimized for agentic capabilities. Key Features Large-Scale Training: Pre-trained a 1T parameter MoE model on 15.5T tokens with zero training instability. MuonClip Optimizer: We apply the Muon optimizer to an unprecedented scale, and develop novel optimization techniques to resolve instabilities while scaling up. Agentic Intelligence: Specifically designed for tool use, reasoning, and autonomous problem-solving. Model Variants Kimi-K2-Base: The foundation model, a strong start for researchers and builders who want full control for fine-tuning and custom solutions. Kimi-K2-Instruct: The post-trained model best for drop-in, general-purpose chat and agentic experiences. It is a reflex-grade model without long thinking. https://github.com/MoonshotAI/Kimi-K2 https://www.moonshot.ai/ https://platform.moonshot.ai/docs/introduction#text-generation-model https://github.com/MoonshotAI/Kimi-K2/blob/main/docs/deploy_guidance.md(Deployment Guide) #KimiK2 #KimiAI #MoonshotAI #Grok4 #LLM #LargeLanguageModel #MoE #MixtureOfExperts #AI #AgenticAI #MuonOptimizer #AICoding #Chatbot #KimiK2Base #KimiK2Instruct #TextGeneration #FrontierKnowledge #Reasoning #AutonomousProblemSolving #TransformerModel #Claude #Gemini #GPT4 #OpenAI #Llama3 #AIModels #GitHub #X #SocialMedia #Benchmarks #ControversialRelease #ChineseAI #AIInnovation #DeepLearning #NaturalLanguageProcessing #NLP #AIResearch #AIML #MachineLearning #DataScience #ArtificialIntelligence #BigData #Technology #Innovation #Tech #AISolutions #DigitalTransformation #AICommunity #AINews #EmergingTech #TechTrends
    GitHub - MoonshotAI/Kimi-K2: Kimi K2 is the large language model series developed by Moonshot AI team
    github.com
    Kimi K2 is the large language model series developed by Moonshot AI team - MoonshotAI/Kimi-K2
    0 Comments ยท0 Shares ยท721 Views
  • On July 1st Replit announced three new capabilities that bring Dynamic Intelligence to Replit Agent. With this advancement, the Agent gains enhanced context awareness, iterative reasoning, and autonomous, goal-driven behavior—enabling it to adapt in real time, navigate complex tasks, and deliver complete solutions with minimal guidance.

    These three new capabilities are:

    Extended thinking: Instructs the Agent to slow down and think more deeply, producing more thorough solutions—while showing parts of its step-by-step reasoning before giving the final result.
    High power model: Increases the Agent’s accuracy by using a more capable AI model
    Web Search: Enables the Agent to perform intelligent web searches based on your request to fill knowledge gaps

    https://youtu.be/1JPvi48oVY8?si=4quo0BKQ762UBiYQ

    #ReplitAgent #Replit #DynamicIntelligence #AI #AIModel #WebSearch #ExtendedThinking #AICoding #AIDevelopment #AutonomousAgent #CodingAssistant #GitHubCopilot #CursorAI
    On July 1st Replit announced three new capabilities that bring Dynamic Intelligence to Replit Agent. With this advancement, the Agent gains enhanced context awareness, iterative reasoning, and autonomous, goal-driven behavior—enabling it to adapt in real time, navigate complex tasks, and deliver complete solutions with minimal guidance. These three new capabilities are: Extended thinking: Instructs the Agent to slow down and think more deeply, producing more thorough solutions—while showing parts of its step-by-step reasoning before giving the final result. High power model: Increases the Agent’s accuracy by using a more capable AI model Web Search: Enables the Agent to perform intelligent web searches based on your request to fill knowledge gaps https://youtu.be/1JPvi48oVY8?si=4quo0BKQ762UBiYQ #ReplitAgent #Replit #DynamicIntelligence #AI #AIModel #WebSearch #ExtendedThinking #AICoding #AIDevelopment #AutonomousAgent #CodingAssistant #GitHubCopilot #CursorAI
    0 Comments ยท0 Shares ยท405 Views
  • Am sure you thinking of cost saving/cutting costs when using Claude Code here is a tool to consider (thanks @sciencedegen):
    Zen MCP is a Model Context Protocol server that orchestrates multiple AI models as a development team, allowing Claude to seamlessly collaborate with different models like Gemini, O3, and others to enhance code analysis, problem-solving, and collaborative development. It provides guided workflows, multiple AI perspectives, automatic model selection, and advanced features like context revival, large prompt handling, and web search integration.

    https://github.com/BeehiveInnovations/zen-mcp-server

    #zenmcp #claude #gemini #o3 #modelcontextprotocol #aimodelcollaboration #aicoding #aiteam #codedevelopment #promptengineering #costsavings #github #codeanalysis #problem solving
    Am sure you thinking of cost saving/cutting costs when using Claude Code here is a tool to consider (thanks @sciencedegen): Zen MCP is a Model Context Protocol server that orchestrates multiple AI models as a development team, allowing Claude to seamlessly collaborate with different models like Gemini, O3, and others to enhance code analysis, problem-solving, and collaborative development. It provides guided workflows, multiple AI perspectives, automatic model selection, and advanced features like context revival, large prompt handling, and web search integration. https://github.com/BeehiveInnovations/zen-mcp-server #zenmcp #claude #gemini #o3 #modelcontextprotocol #aimodelcollaboration #aicoding #aiteam #codedevelopment #promptengineering #costsavings #github #codeanalysis #problem solving
    0 Comments ยท0 Shares ยท374 Views
  • What is Claudia UI and what can it do for your Vibe Coding ?
    Claudia is a powerful desktop application that transforms how you interact with Claude Code. It provides a beautiful GUI for managing your Claude Code sessions, creating custom agents, tracking usage, and much more. Claudia serves as a command center for Claude Code, bridging the gap between the command-line tool and a visual experience that makes AI-assisted development more intuitive and productive.

    Main Function Points
    - Visual Project Browser: Navigate through all your Claude Code projects
    - Session History: View and resume past coding sessions with full context
    - Custom AI Agents: Create specialized agents with custom system prompts and behaviors
    - Usage Analytics Dashboard: Monitor your Claude API usage and costs in real-time
    - MCP Server Management: Manage Model Context Protocol servers from a central UI
    - Timeline & Checkpoints: Create checkpoints at any point in your coding session and navigate through your session history
    - CLAUDE.md Management: Edit CLAUDE.md files directly within the app with live preview and syntax highlighting

    https://github.com/getAsterisk/claudia

    #ClaudiaUI #ClaudeCode #GUI #DesktopApp #AIAssistant #AICoding #VisualIDE #SessionManagement #UsageAnalytics #CustomAIagents #MCPserver #TimelineCheckpoints #CLAUDEmdfiles #OpenAI #CursorAI #GitHubCopilot #AIdevelopment #ProductivityTools
    What is Claudia UI and what can it do for your Vibe Coding ? Claudia is a powerful desktop application that transforms how you interact with Claude Code. It provides a beautiful GUI for managing your Claude Code sessions, creating custom agents, tracking usage, and much more. Claudia serves as a command center for Claude Code, bridging the gap between the command-line tool and a visual experience that makes AI-assisted development more intuitive and productive. Main Function Points - Visual Project Browser: Navigate through all your Claude Code projects - Session History: View and resume past coding sessions with full context - Custom AI Agents: Create specialized agents with custom system prompts and behaviors - Usage Analytics Dashboard: Monitor your Claude API usage and costs in real-time - MCP Server Management: Manage Model Context Protocol servers from a central UI - Timeline & Checkpoints: Create checkpoints at any point in your coding session and navigate through your session history - CLAUDE.md Management: Edit CLAUDE.md files directly within the app with live preview and syntax highlighting https://github.com/getAsterisk/claudia #ClaudiaUI #ClaudeCode #GUI #DesktopApp #AIAssistant #AICoding #VisualIDE #SessionManagement #UsageAnalytics #CustomAIagents #MCPserver #TimelineCheckpoints #CLAUDEmdfiles #OpenAI #CursorAI #GitHubCopilot #AIdevelopment #ProductivityTools
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  • How to use Gemini Code CLI

    The Gemini CLI is an open-source AI agent that brings the power of Google's Gemini models directly into your terminal. It allows you to interact with Gemini for various tasks, including code understanding, editing, and even automating operational tasks. The CLI uses a "reason and act" (ReAct) loop, leveraging built-in tools and external servers to complete complex requests.

    To use Gemini Code CLI in VS Code, first install the Gemini Code Assist extension from the VS Code Marketplace. Then, you can interact with it by opening the command palette (Ctrl/Cmd + Shift + P) and typing Gemini: Start Chat to begin a chat session, or using the /generate command in a code file to generate code based on your prompts.

    https://blog.google/technology/developers/introducing-gemini-cli-open-source-ai-agent/

    #GeminiCLI #GeminiCodeAssist #AIagent #opensource #googleai #vscode #codegeneration #ReAct #terminal #commandline #codeunderstanding #codeediting #automation #codepilot #githubcopilot #amazoncodewhisperer #aicoding #googlecloud #developers #codingtools
    How to use Gemini Code CLI The Gemini CLI is an open-source AI agent that brings the power of Google's Gemini models directly into your terminal. It allows you to interact with Gemini for various tasks, including code understanding, editing, and even automating operational tasks. The CLI uses a "reason and act" (ReAct) loop, leveraging built-in tools and external servers to complete complex requests. To use Gemini Code CLI in VS Code, first install the Gemini Code Assist extension from the VS Code Marketplace. Then, you can interact with it by opening the command palette (Ctrl/Cmd + Shift + P) and typing Gemini: Start Chat to begin a chat session, or using the /generate command in a code file to generate code based on your prompts. https://blog.google/technology/developers/introducing-gemini-cli-open-source-ai-agent/ #GeminiCLI #GeminiCodeAssist #AIagent #opensource #googleai #vscode #codegeneration #ReAct #terminal #commandline #codeunderstanding #codeediting #automation #codepilot #githubcopilot #amazoncodewhisperer #aicoding #googlecloud #developers #codingtools
    Gemini CLI: your open-source AI agent
    blog.google
    Free and open source, Gemini CLI brings Gemini directly into developers’ terminals — with unmatched access for individuals.
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  • Abacus.AI has ChatLLM and AppLLM. ChatLLM is an AI assistant for various tasks like chatting, coding, and image generation, while AppLLM is a no-code platform that builds websites and apps from text prompts using a concept called "vibe coding". Essentially, ChatLLM is for conversational AI and general tasks, and AppLLM is for building applications with AI.

    Here's a breakdown:
    ChatLLM: Aims to be a comprehensive AI assistant, integrating various AI models for tasks like chatting, coding, and image generation.
    Features include voice mode, text-to-image generation, document summarization, and code debugging.
    Can be used for tasks like brainstorming, writing, research, and more.
    AppLLM: Focuses on building websites and applications from simple text prompts using "vibe coding".
    Allows users to create functional apps without coding or server setup.
    Integrates with tools like ChatLLM and CodeLLM for a streamlined AI development workflow.
    Can build various types of applications, including websites, chatbots, and more complex AI-powered applications.

    In short, ChatLLM is about interacting with and leveraging AI for diverse tasks, while AppLLM is about using AI to build applications, particularly websites, without traditional coding.

    https://appllm.abacus.ai/login

    #AbacusAI #ChatLLM #AppLLM #NoCode #AICoding #VibeCoding #WebsiteBuilder #AppBuilder #AIAssistant #Chatbot #TextToImage #OpenAI #Bubbleio #Adalo
    Abacus.AI has ChatLLM and AppLLM. ChatLLM is an AI assistant for various tasks like chatting, coding, and image generation, while AppLLM is a no-code platform that builds websites and apps from text prompts using a concept called "vibe coding". Essentially, ChatLLM is for conversational AI and general tasks, and AppLLM is for building applications with AI. Here's a breakdown: ChatLLM: Aims to be a comprehensive AI assistant, integrating various AI models for tasks like chatting, coding, and image generation. Features include voice mode, text-to-image generation, document summarization, and code debugging. Can be used for tasks like brainstorming, writing, research, and more. AppLLM: Focuses on building websites and applications from simple text prompts using "vibe coding". Allows users to create functional apps without coding or server setup. Integrates with tools like ChatLLM and CodeLLM for a streamlined AI development workflow. Can build various types of applications, including websites, chatbots, and more complex AI-powered applications. In short, ChatLLM is about interacting with and leveraging AI for diverse tasks, while AppLLM is about using AI to build applications, particularly websites, without traditional coding. https://appllm.abacus.ai/login #AbacusAI #ChatLLM #AppLLM #NoCode #AICoding #VibeCoding #WebsiteBuilder #AppBuilder #AIAssistant #Chatbot #TextToImage #OpenAI #Bubbleio #Adalo
    Abacus.AI - AppLLM
    appllm.abacus.ai
    Prompt, run, edit, and deploy full-stack websites. Use AI to build amazing websites.
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  • Google Code Assist, powered by Gemini, provides AI-driven support for software development. It is available in both free and paid versions and aids developers in building, deploying, and operating applications. The Google Cloud Shell Editor includes Gemini Code Assist pre-installed, offering a no-cost development environment.

    https://codeassist.google/

    #googlecodeassist #gemini #ai #aicoding #googlecloudshell #cloudshell #clouddevelopment #softwaredevelopment #pairprogramming #codegeneration #codecompletion #codereview #codingtools #githubcopilot #amazoncodewhisperer #codeium #jetbrainsai #vscodeai
    Google Code Assist, powered by Gemini, provides AI-driven support for software development. It is available in both free and paid versions and aids developers in building, deploying, and operating applications. The Google Cloud Shell Editor includes Gemini Code Assist pre-installed, offering a no-cost development environment. https://codeassist.google/ #googlecodeassist #gemini #ai #aicoding #googlecloudshell #cloudshell #clouddevelopment #softwaredevelopment #pairprogramming #codegeneration #codecompletion #codereview #codingtools #githubcopilot #amazoncodewhisperer #codeium #jetbrainsai #vscodeai
    Gemini Code Assist | AI coding assistant
    codeassist.google
    Get AI coding and programming help no matter the language or platform with Gemini Code Assist from Google.
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  • So Augment offers a Context Engine, MCP integrations, Persistent Memory and more ... Try it here its free (for about 50 messages a month ...now where have l heard of that huh Cursor and Windsurf ???)

    https://www.augmentcode.com/

    And the announcmeent made in April this year is in this article here:
    https://www.augmentcode.com/blog/meet-augment-agent

    #augment #augmentcode #contextengine #mcp #persistentmemory #aicoding #aidevelopment #cursor #windsurf #codecompletion #ai #codingtools #softwaredevelopment #codingassistant #freecodingtools
    So Augment offers a Context Engine, MCP integrations, Persistent Memory and more ... Try it here its free (for about 50 messages a month ...now where have l heard of that huh Cursor and Windsurf ???) https://www.augmentcode.com/ And the announcmeent made in April this year is in this article here: https://www.augmentcode.com/blog/meet-augment-agent #augment #augmentcode #contextengine #mcp #persistentmemory #aicoding #aidevelopment #cursor #windsurf #codecompletion #ai #codingtools #softwaredevelopment #codingassistant #freecodingtools
    Augment Code - AI coding platform for real software.
    www.augmentcode.com
    The most powerful AI software development platform with the industry-leading context engine.
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  • How l switched back to Augment Code from Claude Code !

    Tried new Claude Code ... verdict: Worth every penny love the little to-do lists but hell lot expensive !

    So what do l do l head back home to the loving arms of Augment Code ... still the best and always will be ! (For now ... you know relationships nowadays)

    So this article exaplins why they are nota big fan of Model Pickers ... makes sense though would be great to have the ooption still !). Here is a low done on Augment code and its recent updates:

    Augment Code is considered a top AI coding agent due to its advanced context engine, which enables personalized and efficient code generation, and its seamless integration with popular IDEs. It also boasts features like memory persistence, which allows it to adapt to individual coding styles, and Multi-Context Programming (MCP) for connecting to various tools and systems, enhancing its utility in the development workflow.

    Here's a more detailed breakdown of why Augment Code stands out:

    1. Contextual Awareness and Memory:
    Context Engine:
    Augment's Context Engine is a key differentiator. It analyzes the entire codebase in real-time, providing context-aware suggestions and code completions, leading to more accurate and relevant AI-driven code generation.
    Memory Persistence:
    The platform remembers your coding style and project patterns, ensuring that its suggestions are tailored to your preferences and codebase over time, improving efficiency and reducing errors.
    MCP (Multi-Context Programming):
    Augment Code goes beyond just the code by integrating with various tools and systems, such as Vercel, Cloudflare, and more, allowing it to gather more information, automate tasks, and even fix issues in live systems.

    2. IDE Integration and Workflow:
    Seamless Integration:
    Unlike some AI coding tools that require a separate editor, Augment Code integrates directly with popular IDEs like VS Code, JetBrains, Vim, and GitHub, allowing developers to leverage its AI capabilities within their familiar environment.
    Code Checkpoints:
    Augment Code automatically tracks changes and creates checkpoints, enabling easy rollback and providing peace of mind when the agent tackles complex tasks.
    Remote Agent Functionality:
    Augment Code can operate in a separate container, allowing developers to work on code even when their main machine is off or unavailable, and even run multiple agents in parallel.

    3. Advanced Features and Capabilities:
    Multi-Modal Support:
    Augment Code can handle various inputs, including screenshots and Figma files, making it helpful for implementing UI elements and debugging visual issues.
    Terminal Interaction:
    Beyond code editing, Augment Code can run terminal commands, streamlining tasks like installing dependencies or running dev servers.
    Auto Mode:
    For a more streamlined experience, Augment Code offers an Auto Mode, where it automatically applies suggested changes without requiring explicit confirmation for each action.

    4. Focus on Collaboration and Productivity:
    Developer-Centric:
    Augment Code is designed to work alongside developers, enhancing their existing workflow rather than replacing it, making it a collaborative rather than a replacement tool.
    Time Savings:
    By automating tasks, providing accurate suggestions, and handling repetitive coding tasks, Augment Code frees up developers' time to focus on more complex and creative aspects of their work.
    Continuous Improvement:
    Through feedback loops and learning from user interactions, Augment Code continuously improves its performance and adapts to the evolving needs of developers.

    https://www.augmentcode.com/blog/ai-model-pickers-are-a-design-failure-not-a-feature

    #augmentcode #claude #aicodingagent #aicode #vscode #jetbrains #vim #github #ideintegration #codingtools #productivitytools #memorypersistence #contextengine #multicontextprogramming #vercel #cloudflare #codecheckpoints #remotework #multimodal #figma #terminalinteraction #automode #developercentric #aitools #aidesign #coding #softwaredevelopment #aitool
    How l switched back to Augment Code from Claude Code ! Tried new Claude Code ... verdict: Worth every penny love the little to-do lists but hell lot expensive ! So what do l do l head back home to the loving arms of Augment Code ... still the best and always will be ! (For now ๐Ÿคซ ... you know relationships nowadays) So this article exaplins why they are nota big fan of Model Pickers ... makes sense though would be great to have the ooption still !). Here is a low done on Augment code and its recent updates: Augment Code is considered a top AI coding agent due to its advanced context engine, which enables personalized and efficient code generation, and its seamless integration with popular IDEs. It also boasts features like memory persistence, which allows it to adapt to individual coding styles, and Multi-Context Programming (MCP) for connecting to various tools and systems, enhancing its utility in the development workflow. Here's a more detailed breakdown of why Augment Code stands out: 1. Contextual Awareness and Memory: Context Engine: Augment's Context Engine is a key differentiator. It analyzes the entire codebase in real-time, providing context-aware suggestions and code completions, leading to more accurate and relevant AI-driven code generation. Memory Persistence: The platform remembers your coding style and project patterns, ensuring that its suggestions are tailored to your preferences and codebase over time, improving efficiency and reducing errors. MCP (Multi-Context Programming): Augment Code goes beyond just the code by integrating with various tools and systems, such as Vercel, Cloudflare, and more, allowing it to gather more information, automate tasks, and even fix issues in live systems. 2. IDE Integration and Workflow: Seamless Integration: Unlike some AI coding tools that require a separate editor, Augment Code integrates directly with popular IDEs like VS Code, JetBrains, Vim, and GitHub, allowing developers to leverage its AI capabilities within their familiar environment. Code Checkpoints: Augment Code automatically tracks changes and creates checkpoints, enabling easy rollback and providing peace of mind when the agent tackles complex tasks. Remote Agent Functionality: Augment Code can operate in a separate container, allowing developers to work on code even when their main machine is off or unavailable, and even run multiple agents in parallel. 3. Advanced Features and Capabilities: Multi-Modal Support: Augment Code can handle various inputs, including screenshots and Figma files, making it helpful for implementing UI elements and debugging visual issues. Terminal Interaction: Beyond code editing, Augment Code can run terminal commands, streamlining tasks like installing dependencies or running dev servers. Auto Mode: For a more streamlined experience, Augment Code offers an Auto Mode, where it automatically applies suggested changes without requiring explicit confirmation for each action. 4. Focus on Collaboration and Productivity: Developer-Centric: Augment Code is designed to work alongside developers, enhancing their existing workflow rather than replacing it, making it a collaborative rather than a replacement tool. Time Savings: By automating tasks, providing accurate suggestions, and handling repetitive coding tasks, Augment Code frees up developers' time to focus on more complex and creative aspects of their work. Continuous Improvement: Through feedback loops and learning from user interactions, Augment Code continuously improves its performance and adapts to the evolving needs of developers. https://www.augmentcode.com/blog/ai-model-pickers-are-a-design-failure-not-a-feature #augmentcode #claude #aicodingagent #aicode #vscode #jetbrains #vim #github #ideintegration #codingtools #productivitytools #memorypersistence #contextengine #multicontextprogramming #vercel #cloudflare #codecheckpoints #remotework #multimodal #figma #terminalinteraction #automode #developercentric #aitools #aidesign #coding #softwaredevelopment #aitool
    AI model pickers are a design failure, not a feature
    www.augmentcode.com
    The most powerful AI software development platform with the industry-leading context engine.
    0 Comments ยท0 Shares ยท534 Views
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