OpenAI Acquires Python Tooling Team Codex

OpenAI's recent acquisition of Astral marks a major shift in the Python ecosystem. By integrating these tools into Codex, we are going to see some incredible improvements in AI assisted development. It is fascinating to watch the space evolve so rapidly.

The bottleneck in AI-assisted coding isn't the model or your prompts. When an agent can't see your notebook state, it guesses. You're relaying error messages and stuck in the (endless) loop at every step. With marimo-pair, coding agents get a live view of your notebook. Variables, errors, UI elements - if you can interact with it, the agent can too. PS: you're also not paying per token to analyze your own CSV files. https://lnkd.in/gcBjKijm #python #AI #datascience #openSource #mlops

Recently, I’ve been building backend systems using Python (FastAPI) where I integrate LLMs into real-world workflows. Some practical challenges I’ve worked through: Designing APIs that can handle LLM latency Managing async requests efficiently in FastAPI Structuring prompts so responses are consistent (not just “good once”) Handling streaming / event-driven flows (Kafka) Making the system reliable beyond just a demo One key takeaway: 👉 A working demo is easy. A production-ready system is a completely different problem. Right now, I’m focusing on building scalable AI-backed systems and improving how they behave in real environments. Curious — what’s been the hardest part for you when working with LLMs? #AI #Python #FastAPI #BackendDevelopment #LLM #SoftwareEngineering

Big models aren’t the only way to get better results. Introducing Inferscale 0.1.1—a lightweight Python package that improves LLM outputs using inference-time scaling techniques. No retraining. No massive infrastructure. Just smarter generation. If you're experimenting with LLM quality improvements or trying to reduce costs while maintaining performance, this is worth checking out. GitHub: https://lnkd.in/giq8KJ5g Would love to hear your thoughts and use cases! #LLM #AI #PromptEngineering #MachineLearning #OpenSource #Python #AIDevelopers

Open-source LLMs are powerful—but often need refinement. That’s where InferScale documentation comes in. It provides a lightweight framework to enhance outputs using inference-time scaling approaches like ensembling and selection . The documentation gives you everything you need to start improving results today. If you care about quality and cost, this is a must-read. https://lnkd.in/gRmY5Gc8 #OpenSourceAI #LLM #AIEngineering #Python #GenAI #MLOps #AIProducts #Tech

🚀 Day 24 of My Generative & Agentic AI Journey! Today’s focus was on Generators in Python and how they help in handling data efficiently. Here’s what I learned: ⚡ Generators in Python: • Generators are used to produce values one at a time instead of storing everything in memory • More memory-efficient compared to lists 🔁 yield Keyword: • yield is used instead of return in generator functions • It returns a value and pauses the function, allowing it to resume later 👉 Example use case: Generating a sequence of values (like numbers or data) step by step without storing the entire list. 🧠 Why use Generators? • Handle large datasets efficiently • Save memory • Improve performance in certain cases 💡 Key takeaway: Generators allow writing efficient and scalable code by producing values only when needed. Understanding this concept takes Python skills to the next level 🚀 #Day24 #Python #GenerativeAI #AgenticAI #LearningJourney #BuildInPublic

Day 26/∞: Learning GenAI – Getting Started with Pydantic Today I explored Pydantic, a Python library that makes data validation and settings management much more reliable. One thing that stood out to me is how useful it is for GenAI development, where structured and predictable data matters a lot. Using BaseModel, I learned how to define clear data types, add constraints like character limits or value ranges, and handle optional fields in a clean way. I also saw how Pydantic supports nested models, lists, and reusable validators, which makes it a strong fit for building well-organised applications. For me, the biggest takeaway was that Pydantic helps bring more consistency and safety into Python projects. It feels especially valuable when building with frameworks like LangChain and LangGraph, where structured inputs and outputs can make the whole system more dependable. #Python #Pydantic #GenAI #LangChain #LangGraph #AIEngineering #Day26 #BuildingInPublic

Python is the face of modern tech intuitive and user-friendly. But C++ is the engine powerful, efficient, and blazing fast. The relationship is simple but vital: Python provides the ease of use for developers to prototype and iterate quickly. C++ handles the heavy lifting behind the scenes. Libraries like NumPy, PyTorch, and TensorFlow are written in C++ to ensure that high-performance computations happen in milliseconds, not minutes. In the world of Agentic AI, this synergy is non-negotiable. You use Python to orchestrate the logic, but you rely on C++ to execute the math at scale. One provides the Speed, the other provides the Scale. Together, they are the power couple of the AI revolution. #CPlusPlus #Python #SoftwareEngineering #AIInfrastructure #Performance #CodingFundamentals #TechTrends2026

ChatGPT today: "This library provides a comprehensive toolset rather than your shuffling around dozens of Python scripts that only halfway work." Me: "Excuse me! You've been helping me write those scripts!"

Built a Tic Tac Toe AI from scratch using the Minimax algorithm in Python ♟️ link :- https://lnkd.in/dM7CZhHN What started as a simple game turned into a deep dive into how machines actually “think” and make decisions. I implemented the entire logic from scratch — using recursion and decision trees to simulate every possible move and choose the optimal one. The result? An AI that’s (almost) impossible to beat 😅 Key takeaways from this project: • Understood how Minimax evaluates game states and ensures the best outcome • Learned how recursion can model real decision-making processes • Realized how powerful simple algorithms can be when applied correctly This project wasn’t just about building a game—it was about understanding the logic behind intelligent systems. have a great day guys, stay safe and healthy, grind hard and just do your best everyday. bye 😊 #Python #Algorithms #ArtificialIntelligence #Minimax #GameAI #TicTacToe #SoftwareDevelopment #Coding #BuildInPublic #LearningJourney #ProblemSolving #TechProjects