It's easy to get excited about AI agents and start building. But the real challenge isn't building the technology—it's solving the right problem. Here are 5 things I consider before starting an automation project: - Identify the problem: What is the business struggling with? - Understand the current process: How is the task handled today? - Choose the right solution: Does it really need AI, or would a simple automation work? - Define success: Will it save time, reduce costs, or generate more leads? - Plan for failures: What happens when the automation doesn't work as expected? The goal isn't to add AI to everything. It's to make business operations more efficient and deliver measurable results. I'm curious to hear from this community: - What's one business process you'd love to automate? - Are you currently using AI agents, traditional automation, or a combination of both? Let's share ideas and learn from each other!

Something I've been thinking about lately is how easy it is to jump straight into building an AI agent without fully understanding the business problem first. I think these three questions can save a lot of wasted time: 1. How is the task handled right now? Understand the existing process before suggesting a new one 2. What actually goes wrong? Is it missed leads, slow responses, repetitive work, or something else? Don't assume the problem 3. What happens when the automation fails? There should be a clear fallback so the business isn't left dealing with a bigger problem Not every workflow needs an AI agent. Sometimes a simple automation or even a small process changeis enough For those building automations for businesses, what's one question you always ask before starting a project?

Hey everyone! 👋 I'm a software developer and Generative AI developer, and lately, I've been thinking a lot about how to turn technical skills into real business opportunities. With AI agents, workflow automation, and custom AI solutions becoming more powerful, I believe there's a huge opportunity to help businesses solve real problems. But here's something I'm curious about: For those of you working in the AI space, what's your biggest focus right now? 🔹 Building AI agents and automation systems? 🔹 Offering AI services to businesses? 🔹 Building your own AI SaaS product? 🔹 Finding clients and growing an agency? 🔹 Looking for partners to collaborate on projects? I'd love to connect with people who are serious about building something meaningful in the AI space. I'm particularly interested in AI agents, business automation, and collaborating on practical projects that create real value for clients. Let's share ideas, experiences, and opportunities. Who knows? We might find some great people to build with! 🚀

I am reaching out to propose a "long-term business partnership focused on the rapidly growing AI industry", with the goal of creating sustainable business opportunities and increasing our mutual profits. As artificial intelligence continues to transform industries worldwide, I believe this is an excellent time for us to collaborate, combine our strengths, and take advantage of emerging opportunities. My idea is to work together on AI-related platforms that I have worked such as [AfterQuery,handshake] My main objectives would be to: - "Build a long-term partnership" based on trust, transparency, and mutual respect. - "Combine our skills, experience, and resources" to achieve results that would be difficult to accomplish individually. - "Explore new AI platforms and projects" to diversify our income sources and expand our business. -"Grow together financially and professionally", with a shared commitment to long-term success. This can be done by individuals who have obtained a master's or bachelor's degree upon graduating from university. I'm a AI Engineer so I have enough experience here. If we believe each other and cooperate well,we can increase our mutual profits. I look forward to hearing your thoughts and hopefully building a successful long-term partnership together. Best regards, Genki

How do you guys handle monitoring and error handling in production AI automations? Something I've been thinking about lately is that building an automation that works perfectly during a demo is one thing, but keeping it reliable once a real client starts using it is a completely different challenge. For example, what happens when an API goes down, an execution fails halfway through, an AI gives an unexpected response, or a client's API credentials expire? I'm curious how experienced automation builders approach this in real-world projects. A few things I'd love to understand: - Do you build error handling, retries, and alerts into every workflow from day one, or only when problems arise? - How do you monitor failed executions in tools like n8n or Make without having to check everything manually? - Do you use Slack, Telegram, or email notifications to alert yourself when something breaks? - How do you prevent retries from accidentally creating duplicate bookings, sending duplicate messages, or processing the same lead twice? - When a workflow fails, do you offer ongoing monitoring and maintenance as part of your monthly retainer, or charge separately? I'd especially appreciate hearing how those of you managing automations for paying clients handle this in practice. I want to understand how to build workflows that aren't just impressive demos but are actually reliable enough for a business to depend on every day.