Nitor Infotech, an Ascendion Company

We spent $40,000 building an "AI Assistant" that nobody used. The UI was flawless. The code was clean. The RAG pipeline was technically perfect. But the churn rate didn't budge. I remember the look on the founder’s face during our month-end review. It wasn't anger. It was worse. It was disappointment. We had built a Ferrari that had nowhere to go. I realized then that most "AI features" are just expensive distractions. Business owners are being told they "need AI" but aren't being told why. The hard lesson? Technology is a liability until it becomes a solution. If your AI adds more clicks instead of removing them, you’ve failed. If your frontend is beautiful but slow, users will leave before the AI even loads. Since that failure, I’ve changed my entire approach. I stopped being just a "coder" and started being a product partner. I now follow a strict framework for every SaaS I work with: - Friction First: We only automate the parts of the workflow users actually hate. - The 100ms Rule: If the UI doesn't feel instant, the AI feels broken. - Outcome over Output: We measure success by time saved, not tokens used. This shifts the focus from "adding AI" to increasing ARR and user engagement. You don't need more features. You need a smarter bridge between your users and your data. If you're building a product and want to integrate AI the right way, let's talk. #SaaS #StartupFounder #ProductLedGrowth #AIBusiness #SaaSGrowth #TechStrategy #DigitalTransformation #ProductManagement #Founders #BusinessGrowth #Entrepreneurship #SaaSSolutions #AIConsulting #CustomerExperience #UXStrategy #TechROI #ProductDevelopment #SaaSMarketing #VentureCapital #ScalingBusiness #AIFounders #ProductDesign #BusinessOptimization #SaaSStartup #Innovation #ChiefProductOfficer #CTO #CEOInsights #UserEngagement #ConversionRateOptimization #SoftwareDevelopment #ModernBusiness #TechLeadership #AIPipeline #BusinessStrategy #GrowthHacking #DigitalProduct #SaaSProduct #UserRetention #AIFirst #SmartProduct #HighGrowth #StartupLife #BusinessValue #LeanStartup #TechInnovation #SaaSExecutive #ProductStrategy #MarketFit #Efficiency

My Vercel bill was projected at ~$61/month, and builds were secretly consuming 11 hours of CPU time. 🤕 I thought it was normal... until I checked what was actually driving the costs. Turns out Vercel was charging me for things my app didn't even need: -> Turbo build machines (30 vCPUs) -> On-demand concurrent builds -> Observability Plus events Everything was silently enabled by default on the Pro plan. Another big issue: Vercel bills "Build CPU Minutes", not wall-clock time. A simple 2.5-minute deploy multiplied by 30 vCPUs meant I was paying for 75 CPU minutes every single time. So I decided to clean things up: -> Switched from Turbo -> Standard build machines -> Disabled On-Demand Concurrent Builds -> Excluded the project from Observability Plus Results 🚀 📦 Before: • Billed for 11 hrs of build time • 1.18M paid observability events • ~$61/month total cost ⚡ After: • $0 for Build CPU Minutes (builds are only 16s slower) • $0 for Observability Events • ~$34/month total cost (65% saved) Same application. Not a single line of code changed. Takeaway: Cost optimization is not always about rewriting architecture. Sometimes it's just unchecking two default settings. #Vercel #WebDevelopment #CloudComputing #infiniteresume

I watched a brilliant founder burn $150,000 on an AI feature that exactly zero users wanted to pay for. We had it all: the latest LLMs, a sophisticated RAG pipeline, and a codebase that was technically 'perfect.' But as the launch date passed, the silence from the market was deafening. The struggle was exhausting. We spent months chasing the 'shiny object,' believing that adding AI would magically fix our conversion rates. Instead, we ended up with a bloated, slow interface that confused our customers and drained the runway. I felt the weight of that failure every time I looked at the burn rate—realizing that 'cutting-edge' means nothing if it doesn't solve a human problem. That failure taught me a harsh, expensive lesson: AI-washing doesn’t save products; invisible intelligence does. Great technology shouldn't feel like 'tech' to the user—it should feel like a shortcut to their goal. A fast, intuitive React frontend isn't just about 'performance'—it's about building trust. I stopped being just a 'developer' and started being a product partner who thinks about your bottom line before the first line of code is written. Today, I use a high-velocity framework to help founders ship smarter: 1. Performance First: Using Next.js to ensure the UI is so fast that the AI feels instant. 2. Purposeful AI: Integrating RAG and agents only where they reduce friction and drive user retention. 3. Rapid Execution: Shipping lean, scalable versions in weeks, not months, to test market fit early. The goal isn't just to 'build an app'—it's to build a business asset that converts. If you're building a product and want to integrate AI the right way, let's talk. #SaaS #Founders #StartupStrategy #ProductManagement #BusinessGrowth #AIforBusiness #DigitalTransformation #Innovation #TechStrategy #Entrepreneurship #VentureCapital #SaaSFounders #CustomerExperience #ROI #ProductDesign #Scaleup #USStartups #EuropeTech #TechConsultant #BusinessValue #ModernSoftware #LeanStartup #ProductMarketFit #UserRetention #SmartTech #DecisionMakers #CEO #CTO #ProductOwner #DigitalProduct #GrowthHacking #BusinessEfficiency #SaaSSuccess #AIPowered #FrontendStrategy #TechLeadership #StrategicGrowth #StartupLife #VentureScale #MarketReady #UserExperience #BusinessInnovation #PerformanceOptimization #AIAgents #RAG #NextJS #HighGrowth #Profitability #TechInvestment #SoftwareSolutions

Thrilled to announce that I’ve started a new chapter with Icertis as a Senior Software Engineer 🚀 This opportunity means a lot to me, and I’m excited to take on new challenges, learn, and grow alongside an amazing team. A big thank you to everyone who supported me throughout my journey 🙏 #NewJourney #TechCareer #Icertis #Gratitude

I finally got tired of "log-hunting." There is nothing more frustrating than seeing a red Failed status in Azure Data Factory, only to realize you’ve spent the last 20 minutes digging through a massive Databricks stack trace for a "silent" error. Usually, it’s something trivial—an upstream system changed txn_date to transaction_date without a heads-up. It’s a 10-second code fix, but finding it feels like finding a needle in a haystack of Java/PySpark errors. It’s a waste of engineering focus and a waste of cluster compute. I decided to stop doing it the manual way. I started piping raw telemetry from the Databricks CLI directly into Claude Code. The result? Instead of me reading logs, the AI agent parses the JSON haystack and hands me the corrected PySpark code in seconds. We went from a 15-minute triage to a 60-second recovery. To me, this is what "Agentic" engineering is actually about. It's not about the AI replacing us ,it's about the AI replacing the tedious, low-value work we all hate doing so we can get back to building. I’ve written a breakdown of how I set up this workflow, including the CLI commands and the screenshots of the fix in action. Read the full story here: https://lnkd.in/d_7QGzDm #DataEngineering #Databricks #AzureDataFactory #Claude #AI #DataOps #PySpark