I just created one of the simplest yet most powerful prompts so far. I set it up in a Perplexity task so it runs every morning and sends me an email when it does. In the task user interface it lets me choose when to run it and how often to run it so I set it to run at 9:30am daily. You can do whatever works best for you. I am sure there are other similar task type scheduler features in other LLMs like Gemini, Claude, and ChatGPT if you use those instead. Here's the prompt. Give it a try and see what you think. All the best! Joe Segal find me some good news today and add some encouraging words for me personally

I think people are sleeping on n8n, especially now that everyone's talking about AI agents doing everything. Here's my honest take on why n8n still wins: 1. Agents need triggers. Something has to start the conversation. A Telegram message, a form submission, a calendar event. n8n is what gives your agent its ears. Without it, the agent just sits there. 2. n8n is the connective tissue. Gmail, Google Sheets, Calendar, Telegram, Notion, none of these talk to each other natively. n8n is the bridge that connects them reliably behind the scenes. 3. Structured pipelines beat pure reasoning when reliability matters. Agents are smart but unpredictable. n8n enforces strict sequences, check availability, then check conflicts, then book. You get intelligence AND reliability together. 4. Error handling and visibility. n8n gives you a full debuggable audit trail. A pure agent just gives you a response. When things break, and they will, you need to know exactly where it went wrong. 5. Cost control. Not every step needs an LLM call. n8n handles the deterministic steps without touching the model at all. Your token costs stay low. 6. Sub-workflows make everything scalable. Each agent in your system stays isolated and independently testable. That's n8n's sub-workflow system doing the heavy lifting quietly in the background. The one-liner I keep coming back to: n8n is the body. AI agents are the brain. You need both. "The builders winning right now aren't choosing between them, they're combining them."🔥

Hello everyone! I’m David, a software developer with a strong interest in the field of AI. I’m passionate about technology and always looking for new opportunities to build innovative solutions and achieve better results.

Anyone else dealing with AI scope creep? Project starts as:“Build us a chatbot.” 3 weeks later: • Can it summarize sales calls? • Can it analyze churn? • Can it automate onboarding?• Can it predict LTV? I’ve started implementing a strict: IN-SCOPE / OUT-OF-SCOPE document before kickoff. It’s reduced chaos massively. Curious: How are you protecting your scope while still being flexible?