Dan Palmer

Qualified scaled business ops with 50+ AI Agents 👇🎬 ⭐️ Automated BDR workflows ⭐️ 24/7 output, human-quality emails ⭐️ Agents now used across teams AI GTM Ops Lead, Rich Campbell on the Agents --> “Sometimes better emails than even I could put together.”

👀 Something BIG is coming... #AgentDrop kicks off in 7 days! 🚀 We’ve been working on game-changing features that will transform how you build and deploy AI agents. 5 days. 5 major announcements. Your AI workforce is about to level up. ✨ 👉 Catch a first look in the launch video — @userlastname breaks it all down. And yeah, it’ll be a vibe. 📅 Mark your calendar: Launch Week starts May 6, 2025! #ComingSoon #AgenticAI #AIforBusiness #NoCodeAI #AIInnovation #AIagents #Automation #AIworkforce #AIpoweredTeams #DigitalTransformation

With the news of Anthropic’s latest release, Dan and Lucia sat down to discuss Claude 3.5 Sonnet and 'Computer Use’, a new feature that allows models to navigate desktop apps, move cursors, click buttons, and type text. 👉 Lucia is software engineer on our team, and the brainchild behind our ‘agent cadencing’ feature, which is "a rules engine that limits how an AI agent processes its messages.” Check out the video below, and let us know your thoughts about Computer Use in the comments!

We've just launched a WhatsApp trigger for Teams + plans! 🚀 In this video, Dan Palmer @userlastname walks you through our tips for getting started.

💡Relevance at @sxswsydney It was great to see Daniel Palmer @userlastname speak about the Agentic Revolution. Dan broke down how agentic and generative AI is fundamentally reshaping our ability to automate tasks, and laid out what this will mean for the future of work.

🛠️ We’ve just dropped another Builder Session. Meet Anastasia, an AI Engineer on the Relevance team! In this video, she runs us through her key learnings and insights from performing quality control for AI Agents.

By now, we’ve all seen the news about Open AI’s release of Swarm, an open-source framework for building multi-agent systems. Dan @userlastname and Jason @jasonzhou1993 sat down to discuss what this means for education and experimentation with multi-agent systems. Let us know in the comments what you think the arrival of Swarm means for the AI builder community.

Our Head of Sales had an interesting call last week. During a demo, he created an AI agent with minimal instructions, and gave it two simple tools. What it did next represents a fundamental shift in automation, and gave us the perfect opportunity to break down when should you use AI agents vs. AI tools. 🔧 AI tools: best for repeatable, predictable tasks. 📷 AI agents: ideal for unpredictable, dynamic problems. Click the link in the thread for more insights!

In our latest Builder Session, Charlie Wyatt, an AI Engineer at Relevance AI, shared his thoughts about testing Large Language Models (LLMs). In this video he covers: 🎯 Getting the most from LLM outputs ⚖️ Tools vs. Agents 🐞 Debugging strategies 👉 Click the link in the comments to explore more insights from the team.

💥 With the news of OpenAI's latest bombshell - the o1 model series o1-preview and o1-mini, which represent a leap forward in reasoning capabilities - Daniel Palmer @userlastname sat down with @jasonzhou1993 a.k.a AI Jason to break down what this all means. Here are the key take aways from the chat: 🧠 Enhanced Reasoning: o1 models introduce a sophisticated "thinking process," mimicking human-like reasoning for complex tasks. This approach allows for more nuanced problem-solving and strategic thinking. ⏱️ Performance Trade-offs: While these models demonstrate improved reasoning capabilities, they operate significantly slower than their predecessors. Tasks that once took seconds may now require minutes to complete. 💻 Specialized Excellence: o1 shows particular strength in coding and mathematical reasoning, potentially revolutionizing these fields. Early tests demonstrate impressive results in app development and complex problem-solving. 🚀 Development Implications: This advancement opens new avenues for improving AI accuracy and creating more nuanced systems. It may shift the focus from pre-training to inference-stage computing power. 🔍 Transparency in AI: We may see a shift towards interfaces that reveal the AI's decision-making process, offering greater insight into its operations and allowing for more interactive user experiences. Click the link in the thread to watch!

Discover how to leverage the power of JavaScript and Python code steps within Relevance AI's tool builder. In this tutorial, we cover: 🔗 Accessing step results and user inputs directly by variable names. ❓The differences between JavaScript and Python code steps. 📦 How to import and use Python packages. ⚙️ Accessing advanced settings. 🛠️ Tips for building complex, powerful tools by combining no-code steps with custom code. 👉 Click the link in the thread to watch.

Content creation is one of the most common use cases for generative AI, so we’ve been been experimenting with builds that help you get the most of out LLMs. In our latest video, Dan Palmer @userlastname teaches you how how to create an AI tool using Relevance AI that generates long, content rich blog posts complete with custom thumbnails at scale, and uploads them directly to Webflow. In this tutorial we cover: 🧠 Multi-stage prompting techniques for detailed, structured content generation. 🏆 Maintaining content quality and consistency. 🔍 Seamless integration of Google search results and YouTube video embedding. 🎨 AI image generation and custom thumbnail creation. 🌐 Leveraging the Webflow API for automated content publishing. ⏰ Batch scheduling of AI agents for bulk content creation. 👉 Click the link in the thread to watch the video, and let us know what you want us to build next!

⚡ Unlock the full potential of the Relevance AI tool builder. In this tutorial, you’ll learn the intricacies of using outputs, a crucial aspect of building powerful and efficient tools. We cover: 🔄 How to effectively pass data between steps. 💻 Using JavaScript and Python code steps. 🔍 Leveraging Google search results in your tools. 🛠️ Customizing tool outputs for maximum flexibility. 🧠 Advanced techniques for data manipulation and extraction. 👉  Click the link in the thread to watch.

Learn how to build an AI Tool that automatically transforms your boring Shopify product titles and descriptions into compelling, SEO-friendly content. In this tutorial, we cover: 🛍️ Pulling product data from Shopify API. 👁️ Using LLM vision models to analyze product images. 🔍 Generating SEO-optimized titles and descriptions with AI. 📤 Uploading enhanced content back to Shopify. 🔐 Implementing API authentication and custom secrets. 🔁 Looping through products with for-each functionality. 👉 Click the link in the thread to check out the video.

Learn how to create an AI agent that escalates unknown questions to a human and automatically updates its knowledge base with your answers. In this tutorial, Dan Palmer @userlastname teaches you how to: ❓ Set up an agent to answer FAQs using knowledge retrieval. 📞 Implement an escalation system for unknown questions. 🧠 Send new answers to the knowledge base for future use. 👉 Click the link in the thread to watch.

In our next Relevance Academy video tutorial, Dan Palmer @userlastname teaches you how to create custom integrations in Relevance AI using the API step in the tool builder. In this video we cover: 🌐 API requests 🔒 Handling authentication securely 💻 Data processing with JavaScript 🧠 Prompt engineering for effective summaries 👉  Click the link in the thread to watch.

Ever wondered how to test your AI agents and tools without real data? In this tutorial, Dan Palmer @userlastname teaches you how to create synthetic data using Relevance AI's tool builder. We dive into: ✅ Crafting LLM prompts. ✅ Mastering JSON schema validators. ✅ Nailing knowledge table insertion. 👉 Click the link in the comments to watch!