6-day current streak·13-day longest streak
Ajinkya Gokhale (Andy) IoT Product Creator • Cloud Solutions Architect • Serial Builder --- Building Real Products I don't just write code—I ship real IoT products that solve actual problems.…
Ajinkya Gokhale (Andy)
IoT Product Creator • Cloud Solutions Architect • Serial Builder



---
Building Real Products
I don't just write code—I ship real IoT products that solve actual problems. From smart energy monitoring to privacy-focused email solutions, I turn ideas into products people use every day.
typescript
const andy = {
mindset: "Ship fast, iterate faster",
currentFocus: ["Master's Thesis"],
availability: "Full-time roles from October 2026",
philosophy: "Build products that matter, not just code that works"
};
---
Products I've Built
🔌 Stromleser - Smart Energy Monitor
bash
# Real-time energy monitoring IoT device
• WiFi-enabled IR reader for smart meters
• Plug & Play installation - no electrician needed
• Tasmota-powered with Home Assistant integration
• Shipping across Germany with 0% VAT for solar users
Tech Stack: IoT Hardware Tasmota Home Assistant MQTT Real-time Analytics
📧 SwapMails - Email Privacy Redefined *(Live)*
bash
# Privacy-first serverless email platform
• 1,000+ active users • 99.9% uptime • GDPR-compliant
• Chrome Extension with 500+ installs — one-click temp address
• AES-256 encryption, zero tracking, zero data collection
• Handles 1000x traffic spikes via event-driven Lambda + SES
Tech Stack: React AWS CDK v2 Lambda SES DynamoDB Chrome Extension GDPR
---
Tech Arsenal
🔧 Product Development
javascript
// From idea to market
const productCycle = {
ideation: "Market research + user pain points",
mvp: "React + Vite + AWS CDK",
hardware: "IoT + embedded systems",
scale: "Serverless + global distribution"
};
- Frontend: React, Vite, TypeScript, Modern CSS
- Backend: AWS Lambda, DynamoDB, API Gateway
- Infrastructure: AWS CDK, CloudFormation, Terraform
- IoT: Tasmota, MQTT, Home Assistant, ESP32
☁️ Cloud Architecture
python
# Serverless-first approach
import aws_cdk as cdk
from constructs import Construct
class ProductStack(Stack):
def __init__(self, scope, id, **kwargs):
# Build scalable, cost-effective solutions
super().__init__(scope, id, **kwargs)
- Compute: Lambda, Edge Functions, Containers
- Storage: S3, DynamoDB, RDS Serverless
- Integration: API Gateway, EventBridge, SQS
- Monitoring: CloudWatch, X-Ray, Real User Monitoring
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Certifications
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Current Focus
| Product | Stage | Tech Stack | Launch |
|---------|-------|------------|--------|
| Stromleser | ✅ Live & Shipping | IoT + Tasmota + Home Assistant | Launched |
| SwapMails | ✅ Live & Growing | React + AWS CDK v2 + Lambda + SES | Launched |
| Next IoT Project | 💡 Ideation | TBD | TBD |
---
Development Activity
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My Development Philosophy
> "Perfect is the enemy of shipped"
bash
# My product development approach
1. Research actual user problems (not imaginary ones)
2. Build MVP with modern stack (React + Vite + AWS CDK)
3. Ship early, get feedback, iterate fast
4. Scale with serverless architecture
5. Focus on user experience over flashy features
---
What I'm Building Next
- 🔐 Privacy-focused tools that actually protect user data
- 🏠 Smart home solutions that don't require a PhD to install
- ☁️ Serverless products that scale without breaking the bank
- 📱 Mobile-first experiences built with modern web tech
Let's Collaborate
I'm always interested in:
- Building real products that solve genuine problems
- IoT hardware projects with practical applications
- Privacy-tech initiatives that respect users
- Serverless architectures that actually make sense
---
"Code is just the tool. Products are what matter."
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esp-flasher-java
Flash ESP32 firmware without command line. Auto-installs esptool, factory mode for batch flashing.
Java ★ 18 14d agoExplain → -
Gesture-Recognition
This project aims to recognize hand gestures using Python and OpenCV, without the use of any datasets.
Jupyter Notebook ★ 2 1mo agoExplain → -
apimyresume
A perfect Resume for any Job - Update resume over API using n8n or AI Agent for specific Job Description
TypeScript ★ 1 2h agoExplain → -
ajinkyagokhale.com
No description.
JavaScript ★ 0 3d agoExplain → -
home-assistant-core ⑂
:house_with_garden: Open source home automation that puts local control and privacy first.
Python ★ 0 3d agoExplain → -
home-assistant.io ⑂
:blue_book: Home Assistant User documentation
★ 0 12h agoExplain → -
home-assistant-brands ⑂
🎨 Brands for Home Assistant
Shell ★ 0 22d agoExplain → -
mps-transformation-terraform ⑂
JetBrains MPS project for transforming Terraform deployment models to EDMM
★ 0 10mo agoExplain → -
evcc ⑂
solar charging ☀️🚘
Go ★ 0 16d agoExplain → -
AjinkyaGokhale
Config files for my GitHub profile.
★ 0 2mo agoExplain → -
personalsit.es ⑂
📇 A little directory of people's personal sites
Nunjucks ★ 0 1mo agoExplain → -
react-portfolio-template
Free developer portfolio template built with React 19, TypeScript & Tailwind CSS. One file to customize. Dark theme, animations, GitHub Pages ready.
TypeScript ★ 0 5d agoExplain → -
terraform-mps-plugin ⑂
Terraform plugin using JetBrains MPS for technology-agnostic deployments
★ 0 1mo agoExplain → -
deployment-config ⑂
Deployment model for deploying the DeMAF.
★ 0 10mo agoExplain → -
iot-reference-esp32 ⑂
No description.
★ 0 11mo agoExplain → -
esp-ci-check
No description.
Assembly ★ 0 1y agoExplain → -
esp_idf_sample ⑂
Sample projects for esp idf
Assembly ★ 0 1y agoExplain → -
udemy_esp32 ⑂
Udemy IoT Application Development with the ESP32 Using the ESP-IDF Course Repository
C ★ 0 1y agoExplain → -
Flutter_Bluetooth
Task 1 Flutter app
Dart ★ 0 2y agoExplain → -
ImagePro-Python
ImagePro-Python: Advanced Image Processing and Analysis with OpenCV
Jupyter Notebook ★ 0 3y agoExplain → -
awesome-github-profile-readme ⑂
😎 A curated list of awesome GitHub Profile READMEs 📝
★ 0 3y agoExplain → -
ML-Env-Mac-M1 ⑂
Code for testing various M1 Chip benchmarks with TensorFlow.
★ 0 3y agoExplain → -
Digit-Classifier
The Digit Classifier is a machine learning model that is able to classify handwritten digits with high accuracy. The model is trained using the MNIST dataset, which consists of 60,000 training images and 10,000 test images of handwritten digits from 0 to 9.
Jupyter Notebook ★ 0 3y agoExplain → -
RealTimeObjectDetection ⑂
Object Detection
★ 0 3y agoExplain → -
Radial-Basis-neural-network ⑂
No description.
★ 0 4y agoExplain →
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