testing different ai note takers lately and most are just mid at actual summaries. what are u guys actually using for work that doesn't suck?

okay real talk is anyone making actual money with ai video generators right now? veo, runway, kling, whats everyone actually using that works?

I’m a Senior AI Engineer specializing in production-grade AI systems for real business operations. My expertise includes LLM integration, RAG architectures, agentic workflows, AI automation, prompt and model evaluation, API integration, vector search, backend systems, cloud deployment, observability, and AI security. I build end-to-end solutions from data ingestion and retrieval to agent orchestration, human approval workflows, monitoring, and production deployment. I help companies automate complex processes, modernize existing software, and integrate reliable AI capabilities into their products and internal systems

building cold email sequences with ai but everything's hitting spam folders. copy looks fire but delivery is cooked. how are u guys making this work or did i just fumble?

Every single week, a new chatbot builder, automation template, or "agency-in-a-box" framework drops into our feeds promising to help you sign clients and scale overnight. The hard part isn't discovering them. It’s figuring out which setups actually earn a permanent spot in a client's business instead of constantly breaking the moment real-world edge cases pop up—especially when you're trying to build automations, deploy AI agents, and sell high-value AI services from scratch. Instead of chasing every wrapper of the week, here is the operational stack I rely on to keep client systems stable: - n8n / Make: For wiring up bulletproof backend logic, handling multi-app data flows, and building custom automations that don't fall apart when APIs change. - OpenAI / Custom LLM Integrations: For embedding intelligent chatbots and agent decision-making directly into business workflows. - Apify: My go-to tool for heavy data extraction and web scraping, pulling the clean data needed to feed automation pipelines and prospect for local businesses. - GoLogin: Essential for managing isolated browser profiles securely, keeping multi-account outreach clean, and avoiding friction during client acquisition campaigns. - XAMPP & Local SQL: Where custom databases, backend schemas, and client logic are configured, tested, and fine-tuned locally before going live. - Floment: Useful for organizing community engagement, sharing workflow templates, and keeping operational discussions structured in one place. The bigger lesson here is that pitching AI services just because the tech is trending is a fast track to churned clients and endless support tickets. I’d rather find a real business bottleneck → map out a clean automation system → test the agent logic → and make sure it actually saves the client time before scaling the offer. That’s a much better way to build a sustainable AI agency than chasing every shiny object on the internet. Hey everyone! I’m Emily Harper from the US, joining the community here at KVK AI.