A few days ago I applied to a job on Upwork. I sent over a Loom video of my profile, what I've done and just some proof that I can deliver. They came back a few hours later and booked a meeting. Before the call I received an 18-page PDF on what they wanted. That document scared me to the point where I was second-guessing my skills. But then on the call itself, they revealed that they're looking for an AI agent to reply to customers. Lol. A lot easier than I thought. So here's where things go wrong. I do not diagnose the problem at all. I assume that the problem they present is the problem to solve. So when I agree to the job and that I can deliver the agent, we're basing the entire project on: "what they think the problem is." So I sent over an offer for $1207.75. They try to negotiate it down to $800. I revert back that this covers the entire project. And they counter with adding in more things and accept the deal. A few minutes later I receive the contract. At this point I've locked down the contract and I believe I can complete the job. I have a week to deliver an MVP and I have enough cash to hire help if I can't deliver. But then I receive an invitation to their customer service platform. I start looking around and setting up everything. This is when I start to realize that they're using zero internal automations. And when I start going through their emails I realize that 97% of all tickets use templated replies. The last 3%? Refund/cancellation issues or standard customer service questions. Those 3% are the perfect place to use AI because of the nuances. But the 97%? A simple set of rules and automation handles that. They don't need AI, they need automations that runs based on rules. That will clear all cases within a day. And that's without using AI. Looking at this, I could have figured this out if I had asked them about their setup in the call. I would have offered a simpler solution instead of a complex one without even thinking about it. The lesson is: ask more questions, dig for the problem.

Hi everyone 👋I’m building a SaaS where users currently upload an Excel file that is manually created from daily worker timecard PDFs. I’ve attached: - A sample timecard PDF (hard to read, scanned, inconsistent field names) - The final Excel output I need Goal Allow users to upload the PDF directly and automatically extract, per worker: - Date, Name - Time In - Lunch In / Out - Dinner In / Out - Wrap Time - Position - Department Challenges - Poor OCR quality - Field names vary across PDFs - Semi-structured tables - High accuracy required (payroll data) Plan - Use n8n for orchestration - Use PDFVector for PDF parsing / structured extraction - Add post-processing to normalize fields Questions 1. Is PDFVector reliable for row-level timecard extraction, or better as a helper only? 2. Best OCR + extraction approach for scanned timecards? 3. How would you design this pipeline for reliability at scale? Appreciate any guidance or real-world experience 🙏