How to build a chatbot with n8n without coding

Accelerate engineering by blending AI tools with proven habits: use automation for code comprehension, refactoring, and performance tuning; boost test coverage and velocity with smart prompts; and capture unfinished work to maintain flow. Structure requests well and leverage persistent context files to help AI deliver real impact. Use a Best-of-N approach to uncover optimal solutions. #SoftwareEngineering #AItools #Productivity #BestPractices

Throwback to AI-fokus 2025 🎥 Generative AI can be a powerful force multiplier for developers — but at scale, it comes with real challenges. How do we design tools that stay reliable, avoid runaway behavior, and reduce the need for constant human intervention? Trusting AI to Modernize Software at Scale by Tim te Beek Watch the full talk here 👉 https://lnkd.in/gBhdYWxX #AIfokus #GenerativeAI #DeveloperTools #Jfokus

When Chatbots Amplify Misinformation Recent data shows that the rate of false or misleading responses from AI chatbots nearly doubled—from 18% to 35%—as systems grew more willing to answer and integrated real-time web access. As I've said it before: the value of GenAI isn't just what it can say, but how reliably—and auditably—it conveys truth. If your system can cite sources but doesn't validate or contextualize them, you’ve just built automation theater with a trust problem. For real impact, build: Truth layers: fact-checking pipelines before response delivery. Confidence signals: threshold guards on when to respond at all. Version control: traceable logs for every claim made. Generative power needs governance—especially in regulated contexts.

The AI Agent ecosystem is expanding with tools like Vercel AI SDK simplifying development. Combining goal-oriented prompts with Storyblok's MCP server creates autonomous content agents that significantly accelerate workflows. Learn how to implement it: https://okt.to/RDhvGV

The AI Agent ecosystem is expanding with tools like Vercel AI SDK simplifying development. Combining goal-oriented prompts with Storyblok's MCP server creates autonomous content agents that significantly accelerate workflows. Learn how to implement it: https://okt.to/IFujWE

n8n just released a workflow builder in beta, and it's about to kill off half most AI agencies. Well not really... but it will make automation more accessible to the masses. The real opportunity with learning these different tools that help facilitate AI implementation is to understand business pain points and how you can actually provide or productize a service. Not so much learning the ins and outs of what each node does, how it flows, and just spending day and night in N8n to create some sort of workflow that honestly doesn't really drive impactful results. If you're looking to learn anything, just learn the overall AI Architecture and how you can implement the proper tools to provide a solution. Everyone is going to have access to AI just the way that everyone has had access to the internet for the past 20 or so plus years. The real question is, what do you do with that access in order to provide value to others? How are you currently implementing AI into your business? 

Introducing Agent-C: a remarkable ultra-lightweight AI agent that fits into just 4KB yet packs a punch! Designed to facilitate seamless communication with the OpenRouter API, it can execute shell commands effortlessly. Whether you’re a developer looking for an efficient tool to enhance your workflow or curious about lightweight AI implementations, Agent-C can streamline your tasks. With features like conversation memory for efficient operations and cross-platform support, it's a go-to for optimizing your command line interactions. Explore its capabilities and see how it can benefit you! Learn more at https://lnkd.in/dmKzKn_6

Assistant builders, the toolset just leveled up. With Vercel’s AI Gateway, assistants can switch between models seamlessly, handling failover automatically—so conversations don’t break when a provider goes offline. EmbeddingGemma means assistants can run offline semantic search, file retrieval, and domain-specific knowledge directly on-device—faster, private, and multilingual. Pair that with Next.js 15.5 improvements, and you’ve got faster build cycles and stronger server-side logic for deploying your AI assistant at scale. The assistant stack is evolving: smarter pipelines, more resilient infrastructure, and deeper personalization.

🤖 Building an AI Agent? Here’s the framework comparison you need 👇 🔹 LangGraph – Stateful, multi-actor LLM apps 🔹 LangChain – Developer-first with chains, tools & memory 🔹 AutoGen – Multi-agent collaboration via conversations 🔹 CrewAI – Role-based orchestration for LLM agents 🔹 Make.com – No-code drag & drop workflow automation 🔹 n8n – Low-code AI workflow + API integrations The future is all about AI + automation — and the right tool can transform how you work. 👉 If you’d like help choosing the right framework or building a custom AI agent, let’s connect! #AI #Automation #LangChain #LangGraph #AutoGen #CrewAI #Make #n8n #ArtificialIntelligence #WorkflowAutomation

𝗢𝗹𝗱 𝘁𝗼𝗼𝗹𝘀, 𝗻𝗲𝘄 𝗽𝗼𝘄𝗲𝗿. Before chasing the next protocol, don’t forget what’s already in your hands. OpenAPI, originally built for REST documentation, is surprisingly effective for AI agents. With over a decade of mature tooling, it allows you to instantly expose your existing APIs to AI agents without reinventing your tech stack. 𝗥𝗲𝗮𝗱 𝗼𝘂𝗿 𝗹𝗮𝘁𝗲𝘀𝘁 𝗯𝗹𝗼𝗴 𝗽𝗼𝘀𝘁: https://lnkd.in/dr4Ayt-V 🔗 Follow-us on our ekona.ai LinkedIn page for more content like this in the future. 𝗦𝗼 𝘄𝗵𝗮𝘁 𝗱𝗼𝗲𝘀 𝘁𝗵𝗶𝘀 𝗲𝗻𝗮𝗯𝗹𝗲 𝗶𝗻 𝗽𝗿𝗮𝗰𝘁𝗶𝗰𝗲? You can expose any public or internal API to your AI agents and interact with your data using natural language: How many tickets are currently open in Zendesk? What’s the latest number of GLP-1 publications on PubMed this month? Show me the average revenue per client for August, in graph form. Display a dashboard of sales per quarter, focused on the top five countries in Europe. etc... This is how we break the barrier between data and decisions, using 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝗔𝗜 𝗮𝗴𝗲𝗻𝘁𝘀 𝘁𝗵𝗮𝘁 𝗰𝗮𝗻 𝗿𝗲𝗮𝘀𝗼𝗻, 𝘂𝘀𝗲 𝘁𝗼𝗼𝗹𝘀, 𝗮𝗻𝗱 𝗲𝘃𝗲𝗻 𝘄𝗿𝗶𝘁𝗲 𝗰𝗼𝗱𝗲 𝘁𝗼 𝗴𝗲𝘁 𝗮𝗻𝘀𝘄𝗲𝗿𝘀, making complex information easy to access across your entire organization. ⚠️ 𝗢𝗻𝗲 𝗻𝗼𝘁𝗲 𝗼𝗳 𝗰𝗮𝘂𝘁𝗶𝗼𝗻: This kind of AI-enabled API access doesn’t work by magic. It requires discipline. Your OpenAPI specs need to be real, current, and clean, not just documentation after the fact. Too often, teams treat specs as a formality, while production, mock servers, and SDKs quietly drift apart. The result? Confusion, mistrust, and wasted time. To truly unlock the power of multi-agent AI, agents that can reason, call tools, and even write code, you need a single, trustworthy source of truth for your APIs. That’s what OpenAPI was always meant to be. It’s time we start treating it that way. #AI #OpenAPI #LangChain #MCP #AgenticAI