An Sheng

🚀 Excited to announce the launch of Shamsi Calendar API! 🎉 After weeks of development, I'm proud to release a comprehensive RESTful API for the Afghan Shamsi (Solar Hijri) calendar - now live at https://lnkd.in/g7TNWXys Why I built this: As Afghan developers, we've long struggled with the lack of reliable tools for our calendar system. This API changes that. 🌟 Key Features: ✅ Accurate Shamsi ↔ Gregorian date conversion ✅ Full calendar views (day, week, month, year) ✅ Complete holiday management system ✅ Trilingual support: Dari, Pashto & English ✅ Interactive Swagger documentation ✅ 151 tests with 85.6% code coverage ✅ Free and open-source 🛠️ Built with: TypeScript, Express.js, tested with Jest, and deployed with enterprise-grade security (rate limiting, CORS, Helmet) 📊 What you can do: Build Afghan calendar apps without reinventing the wheel Integrate Shamsi dates into your existing applications Access accurate holiday information Use it in any language: TypeScript, Python, Java, etc. 🎯 Perfect for: Afghan tech startups, government systems, educational platforms, mobile apps, and anyone serving the Afghan community worldwide. Try it out at the interactive documentation and let me know what you think! Contributions and feedback are welcome. #OpenSource #API #AfghanTech #ShamsiCalendar #WebDevelopment #TypeScript #SoftwareEngineering #Afghanistan

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I use Claude Code to ship my engineering tasks in weekdays, but its potential goes far beyond just refactoring or debugging code. I recently built a workflow where I can publish a complete song to YouTube using Claude Code from the CLI. The entire pipeline, lyrics composition, local AI music generation, cover art design, video assembly, and YouTube publishing,  runs from a terminal with a prompt and minimal human interaction.  What used to require coordinating across multiple tools, multiple skill sets, and multiple hours now takes minutes from a single interface.  But here's the bigger picture: this pattern applies everywhere. The same approach of chaining AI capabilities into end to end workflows is transforming content creation, marketing, research, design, and operations across industries.  We're entering an era where the competitive advantage isn't just knowing how to use individual tools. It's knowing how to orchestrate them into workflows that collapse entire pipelines into simple interactions.  What workflows in your industry are ready for this kind of transformation?  https://lnkd.in/gN_tR6tz PS: This post was generated using AI, and the quality of song could be better using models with more parameters, and better prompting maybe? but I used distilled model due to resource constrains.  #AI #FutureOfWork #Automation #ClaudeCode #MusicGeneration #Innovation #Productivity

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🚘💡 Edge AI is reshaping industries—and redefining the talent we need to build the future. Our EVP & President of Software, Advanced Safety, and User Experience, Javed Khan, shares how Edge AI is transforming real-time decision-making across autonomous vehicles, aerospace systems, robotics, and beyond. 🔗 Read the article here: https://bit.ly/40AM3hc #ImpactEveryJourney #FutureofMobility #Innovation #EdgeAI

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Based on the provided articles, here are 3 promising AI startups with recent funding news: 1. Flint - Raised $5 million in seed funding (October 14, 2025) - Led by Accel with participation from Sheryl Sandberg's fund and Neo - Building an AI platform that autonomously builds and updates websites - Source: https://lnkd.in/dYMYVyWu 2. Leonardo.ai - Acquired by Canva (announced July 29, 2024) - Had previously raised over $38.8 million from investors including Smash Capital, Blackbird, Side Stage Ventures and others - Specializes in generative AI content creation with over 19 million registered users - Source: https://lnkd.in/d3J5DAMA 3. Coco Robotics - While specific funding isn't mentioned, the company announced launching a new physical AI research lab (October 14, 2025) - Partnering with OpenAI and led by UCLA professor Bolei Zhou - Focuses on autonomous last-mile delivery robots - Source: https://lnkd.in/dUbYZDCf

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In this video, we will build a local AI agent using Ollama's gpt-oss model (from OpenAI), LangChain, and Streamlit. This agent will connect to the internet using LangChain MCP adapters and Tavily, allowing it to search the web and give accurate answers to your questions. This way, you can have a local ChatGPT on your personal computer without paying for any subscription. I’ll guide you step by step through the process of creating a LangGraph agent that uses the gpt-oss model as the LLM, integrating the agent with MCP tools, and building a simple but clean UI using Streamlit. If you’re curious about the new gpt-oss model, or you want to know how you can connect local LLM agents with MCP servers, this video is for you. You can watch it here: https://lnkd.in/dh9SVkht #chatgpt #langchain #langgraph #ollama #streamlit

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Today is a huge day for ClosedLoop/Healthy! We have officially started our pilot program with select doctors' offices. This means we are an actual (this first?) doctor recommended generative AI Health Coach! These Doctors are recommending Healthy to their patients, and helping them download and onboard into the app. Each doctor has a unique referral code that links the patient to them within Healthy. We're so excited for this next step in our journey to improve the health care system! And Healthy is still available for free in the App and Play Stores.

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Built a demo - a "try-on" feature for clothing sites where you upload your photo and see how clothes look on you This can help reduce return rates for apparel sites by a huge margin. One of the biggest issues apparel owners face is customers ordering clothes that don't look how they expected. From customers end as well, they get to see exactly how they'd look before buying - saves everyone time and money. It can be integrated to site with a simple "Try it on" button next to each product. https://lnkd.in/dgNdgR8z #buildinpublic

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Whom do I reach out to for AWS credits for startups? All the TAMs I worked with are all over now. :)

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It's almost criminal that some topics are never extensively taught in a CS degree when they pertain so much to the real production systems at scale. One of those crucial topics is System Design. It's even harder to find structured, hands-on learning opportunities catered to folks in our local Pakistani community. It was a breath of fresh air when I found that Umer Farooq has taken the initiative to teach those topics that belong in every CS curriculum. During his 4-week masterclass, I was introduced to topics that could warrant a whole CS degree if I had to do it again 😁 We took a holistic view of scalable systems, starting off with familiarity with architectural building blocks, moving over to read-intensive systems, then write-intensive and finishing off with some data engineering topics. Below are some of the topics we covered in our 4 week journey: - Building blocks (HTTP, Load balancers, CDN, DNS, Cloud, Queues, Latency) - Storage distribution (Sharding, Partitioning, Consistent hashing) - Replication models (Async vs Sync replication, Leader-follower replication, Leader-Leader replication, Leaderless replication) - Indexing (Query optimization, B/B+ Trees, Clustered vs Non-clustered index) - Traffic estimation & Cost (QPS, MAU, DAU, Growth rate, Safety factor) - Caching (Redis, TTL, Cache invalidation, Cache-aside pattern) - Transactions (Shared locks, Exclusive locks, 2-phase locking, Optimistic locks, WAL, MVCC) - Concurrency challenges (Dirty read, Read skew, Dirty write, Lost updates, Race conditions) - Isolation levels (Read committed vs Read uncommitted, Repeatable read, Serializable) - Data engineering (OLTP vs OLAP, ETL pipelines, Batch processing, Data warehouses, Data aggregation) We took case studies of real systems including booking(.)com, tinyurl, AirBnB & more. All interactive, conversation driven, whiteboard & no slides. Absolutely love this way of learning. #SystemDesign

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Spoke with an engineer in a 1:1 today. He shared an idea to improve our team's velocity. He proposed that since we had multiple services we should split the team for each microservice to make people more productive. I explained to him we don't have microservices but we do have a micromanager so there is no need to split the team. #leadership 🤗

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