Tech Insights
Lessons from shipping automation
Playbooks and postmortems on launching automation-first products—from marketplaces and AI agents to design-to-dev pipelines.
Building a Universal AI Chatbot Platform: From Concept to Production
## Introduction In 2026, AI chatbots are everywhere, but most are tied to a single application or platform, making them difficult to reuse across projects. I recently built a Universal AI Chatbot Platform, a scalable, context-aware, API-driven chatbot that developers can integrate into any web application. From SaaS dashboards to e-commerce stores, this platform is designed for maximum flexibility, token efficiency, and production readiness. You can try the live demo here: [Universal AI Chatbot](https://universal-chatbot-psi.vercel.app/).
3 min read →The Future of AI Assistants in Engineering Workflows
AI assistants are moving from code completion tools to autonomous engineering agents. Here's my view on where this is headed and what it means for how we build software.
8 min →Fine-tuning Mistral-7B for Domain-Specific Engineering Tasks
A deep dive into how I fine-tuned Mistral-7B using LoRA adapters to power domain-specific code assistance inside JarvisX — without expensive cloud inference.
12 min →Building Scalable Cloud SaaS with Next.js, TypeScript, and PostgreSQL
A practical guide to architecting a production-ready SaaS platform — the full stack decisions, patterns, and trade-offs I've refined across multiple SaaS projects.
11 min →Building a Multi-Mode AI Assistant: Architecture and Lessons Learned
How I architected JarvisX V2 — a multi-mode AI assistant that switches between cloud and local inference, maintains persistent memory, and integrates directly into the development workflow.
14 min →Building a Full-Stack SaaS from Scratch with Next.js and PostgreSQL
A complete end-to-end tutorial: building a production-ready SaaS application from zero — project setup, authentication, database, subscriptions, and deployment.
18 min →Building a Desktop App to Control Pixel LED Matrices
How I built J-Tech Pixel LED Upload Bridge — a cross-platform desktop app that translates image data into LED matrix control signals over serial communication.
11 min →Automating Business Lead Extraction with AI and SaaS Platforms
How I built a Google Maps data scraper that extracts, enriches, and qualifies business leads automatically — cutting manual prospecting from hours to minutes.
9 min →AI-Powered Classified Ads: How AI Improves User Engagement
How I used AI to transform a traditional classified ads platform — from smart listing generation to personalized recommendations and fraud detection.
9 min →Offline AI Development with VS Code Extension and Local Inference
Building a fully offline AI-powered development environment using a custom VS Code extension, Ollama, and locally quantized models — zero cloud dependency, full privacy.
10 min →SaaS Architecture Patterns That Scale in 2026
The SaaS architecture patterns I've learned across multiple products — what actually scales, what's over-engineered, and what's changed in the last two years.
10 min →Why Local AI Deployment Is the Next Big Trend
Cloud AI APIs are convenient but come with real costs — latency, pricing, privacy risk, and dependency. Local AI deployment is maturing fast. Here's why it will become dominant.
9 min →Simulation vs Real Hardware: Designing LED Visualization Tools
Building a software simulator for LED hardware taught me more about good software design than the hardware itself did. Here's how I built a pixel-accurate LED preview tool.
8 min →Smart LMS SaaS: Lessons in Multi-Tenant Course Management
A full case study of Smart LMS — the problem, architecture decisions, multi-tenancy design, the challenges we hit, and what I'd do differently building a SaaS learning management system.
13 min →Step-by-Step Guide to LoRA Fine-Tuning on Mistral Models
A complete, practical guide to fine-tuning Mistral-7B using LoRA adapters — from environment setup through dataset preparation, training, and running your fine-tuned model locally.
15 min →Designing Multi-Tenant SaaS Architecture for Learning Management Systems
How I designed and built a multi-tenant SaaS LMS — covering tenant isolation strategies, authentication flows, role-based access, and the architectural decisions that shaped Smart LMS.
13 min →Lessons from Deploying Real-Time Task Management Systems
Building TaskNest pushed me into the real-time web — WebSockets, conflict resolution, presence indicators, and optimistic UI. Here are the hard lessons I learned.
10 min →Lessons in Building Scalable AI SaaS Platforms
Key architectural and product lessons from building AutomateLanka — an all-in-one automation SaaS platform built on n8n workflow foundations with multi-tenant isolation and AI search.
10 min →JarvisX V2: From Fine-Tuning to Cloud + Local Deployment — A Full Case Study
A complete engineering case study: the problem, the architecture, the fine-tuning process, the VS Code extension, and hard lessons learned building JarvisX V2 — my personal AI development assistant.
16 min →Integrating Cloud Backend with Embedded Systems
The hardest part of hardware-software integration isn't the hardware. It's making cloud and embedded systems speak the same language reliably. Here's what I learned.
10 min →Integrating AI in VS Code for Productivity Boost
A practical guide to supercharging your VS Code setup with AI — from extensions and keybindings to building your own AI-powered commands.
8 min →Shipping Production LLM Ops Without Surprises
Patterns for observability, evaluation, and fallbacks that kept JarvisX compliant and trustworthy for enterprise analysts.
6 min read →Automating 2,000+ Workflows With n8n & Temporal
How we scaled AutomateLanka’s managed automation marketplace with tight SLAs, billing, and governance baked in.
7 min read →Design Handoff to Code: Building the Specs Extractor
A look at generating production-ready specs from Figma and Adobe UXP with automated QA and CI pipelines.
5 min read →