The hottest Development Substack posts right now

And their main takeaways
Category
Top Technology Topics

Making Sense of Environments

realkinetic • 0 implied HN points • 18 Feb 19
🕹 Technology Development Security Reliability Cost management
  1. When structuring environments, consider the trade-offs between shared and team-specific environments based on costs, benefits, and complexities.
  2. Different environment types (like playground, development, staging, and production) serve distinct purposes in ensuring developer efficiency, code validation, security, and reliability.
  3. Minimize the number of environments to reduce costs, improve integration practices, and optimize developer efficiency, while balancing factors like data sensitivity and operational costs.

How to Level up Dev Teams

realkinetic • 0 implied HN points • 03 Jan 19
🕹 Technology Development Teams Tools Practices Code Reviews
  1. Training may not be the most effective way to level up development teams; it can be costly and the impact on team readiness is uncertain.
  2. Tools alone are not sufficient to level up teams; they often just cover up broken practices and policies.
  3. Code reviews are the most effective method to quickly improve team proficiency; they promote a culture of constructive feedback and knowledge sharing.

From Pain in the Ass to People Leader

Notes in the Margins • 0 implied HN points • 27 Jun 24
💼 Business Leadership Development Career growth Coaching Team Dynamics
  1. Leadership skills can be learned and grown over time with self-reflection, learning, and caring for others.
  2. Transitioning from being a difficult manager to a people leader requires personal growth, understanding team dynamics, and a passion for supporting others.
  3. Building high-performing teams and loving humans can become a powerful ability and source of joy in a leadership role.
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Iteration vs Planning

Tribal Knowledge • 0 implied HN points • 22 Jan 23
🕹 Technology Development Product Management Startups Software Engineering
  1. Agile methodology focuses on iteration and adapting to changes, while Waterfall emphasizes on planning everything upfront. Both have their tradeoffs and can work well for different reasons.
  2. The iterative approach involves delivering incrementally, receiving constant feedback, and adjusting along the way. It allows for flexibility but can lead to bugs and customer frustration initially.
  3. The planning approach involves detailed upfront planning, building according to the plan, and announcing the product only after completion. It provides a structured process but may lead to delayed reactions to customer feedback and potential rework.

Leave the REST to GraphQL

Tribal Knowledge • 0 implied HN points • 05 May 22
🕹 Technology APIs Development Backend Rest
  1. GraphQL provides an intuitive and flexible way to describe data requirements and interactions for client applications, simplifying development by having a defined schema and aiding with debugging.
  2. While REST is a standard widely taught in software engineering, GraphQL offers a more elegant approach by simplifying data contracts, debugging, and allowing for a more complex backend and simpler frontend development.
  3. Using GraphQL can help divide tasks among team members more effectively, with senior engineers focusing on backend problem-solving and junior engineers concentrating on frontend tasks like data mapping, ultimately making APIs more discoverable and user-friendly.

Quality Engineering Basics: Types of Testing

QUALITY BOSS • 0 implied HN points • 19 Feb 24
🕹 Technology Software Testing Quality Engineering Automation Development
  1. There are two main types of testing: functional and non-functional. Functional testing checks if the software meets its intended requirements, while non-functional testing looks at things like performance and security.
  2. Testing can also be categorized by the level, such as unit, integration, system, and acceptance testing. Each level focuses on different parts of the software and helps ensure everything works together smoothly.
  3. Finally, there are different ways to test, including manual and automated testing. Manual testing involves humans checking software directly, while automated testing uses tools to run tests automatically. Both are important for delivering a quality product.

Meet Bug, the QUALITY BOSS Mascot

QUALITY BOSS • 0 implied HN points • 06 Nov 23
🕹 Technology Software Quality Assurance Development Leadership Women in Tech
  1. The mascot is a firefly named Bug, symbolizing the journey towards achieving high quality. Bug is meant to guide and inspire everyone to reach excellence.
  2. The term 'bug' usually refers to problems in software, but here it's reimagined as a positive force for growth. Each bug is seen as a chance to improve and learn.
  3. Bug not only represents quality but also highlights unique experiences in the tech industry, especially for women. This fosters a community focused on exploration and learning.

How to write beautiful Java

Tecnica • 0 implied HN points • 28 Jul 24
🕹 Technology Programming Software Development Java Coding
  1. Using streams in Java can make your code cleaner and easier to read. It helps you focus on what you want to do instead of how to do it.
  2. Instead of checking for null values with messy if statements, use Optionals for a more elegant solution. This can make your code safer and cleaner.
  3. Refactoring your code with these techniques can greatly improve its quality. Small changes can lead to a more enjoyable coding experience.

Google Search Reloaded 🔍✨

Sector 6 | The Newsletter of AIM • 0 implied HN points • 17 May 24
🕹 Technology AI Search Software Innovation Development
  1. Google is changing how its search works, aiming to provide a better experience for users. They want to compete with other tech companies, especially OpenAI.
  2. New products like text-to-video and AI tools show that Google is focusing on improving their technology and staying relevant.
  3. Experts are noting that competition from OpenAI has pushed Google to enhance its services and rethink its approach to search.

Is RAG Dead? ☠️

Sector 6 | The Newsletter of AIM • 0 implied HN points • 07 May 24
🕹 Technology AI Software Development Engineering Innovation
  1. RAG is still relevant and has the potential to improve, even with long context windows in large language models (LLMs).
  2. Many developers are actively working with RAG, creating new applications and tools to enhance its use in various settings.
  3. Even as technology advances, RAG will likely remain necessary due to cost considerations; it's not going away anytime soon.

Grok Delivers Open AI Promise?

Sector 6 | The Newsletter of AIM • 0 implied HN points • 18 Mar 24
🕹 Technology AI Open Source Software Development Data Transparency
  1. Elon Musk released the Grok model as open-source, but it has mixed reactions from developers. People are unsure about why it was shared and what it actually includes.
  2. The Grok model is currently just a base model and isn't fine-tuned for specific tasks. It was completed in October 2023, so it might need more work to be really useful.
  3. Although the model's weights are available, there's no clear information about the training data used. Some feel this makes it less transparent and more like just open-weight models instead of fully open-source.

Devin’s in the Details 🤖

Sector 6 | The Newsletter of AIM • 0 implied HN points • 13 Mar 24
🕹 Technology AI Software Engineering Development User Experience
  1. Devin is the first AI software engineer created by Cognition Lab, and it has stirred up a lot of different feelings online.
  2. Many coders are worried about what this could mean for their jobs, while others are excited about the technology.
  3. The focus on user experience and the surrounding infrastructure makes Devin stand out, not just the AI itself.

LLM Made by the Indians, for the Indians

Sector 6 | The Newsletter of AIM • 0 implied HN points • 24 Jan 24
🕹 Technology AI Open Source Software Development Innovation
  1. India has launched its own language model called BharatGPT, which aims to compete with LLMs from other countries. This is significant because India had been missing from the global LLM market.
  2. BharatGPT will be open source, allowing developers to contribute and improve the model. This means that as more people use it, it can get better over time.
  3. The creators are sharing their work on a platform called Decile, which is like a collaborative space similar to GitHub for developers. This will help foster a community around BharatGPT.

Multimodal Race Begins

Sector 6 | The Newsletter of AIM • 0 implied HN points • 25 Sep 23
🕹 Technology AI Software Models Development Innovation
  1. The competition for creating multimodal large language models (LLMs) is heating up, with big players like Google, OpenAI, Meta, and Stability AI involved.
  2. Stability AI has already launched three models: StableLM, Stable Diffusion, and Stable Audio, and they plan to combine these into a single powerful system.
  3. This development marks just the start of exciting advancements in multimodal AI, promising more integrated and versatile technology in the future.

Stop Sulking, Start Building

Sector 6 | The Newsletter of AIM • 0 implied HN points • 12 Jun 23
🕹 Technology AI Software Engineering Innovation Development
  1. Software engineers today need to learn new skills beyond just building websites. They should focus on solving real problems that matter now.
  2. There is a concern about the shortage of GPUs, which are essential for running advanced AI models. This could affect both companies and developers relying on these technologies.
  3. It's essential to adapt and evolve with the tech landscape instead of getting stuck in old routines. Embracing change can lead to better opportunities and solutions.

Replit Outshines Amazon & Microsoft

Sector 6 | The Newsletter of AIM • 0 implied HN points • 18 Apr 23
🕹 Technology AI Software Cloud Development Data
  1. Replit is getting help from Google to make coding easier and faster, claiming it can help programmers finish projects in a fraction of the time.
  2. In India, Replit is leading the way in helping new software developers, with the number of developers expected to grow significantly this year.
  3. This partnership is aimed at competing with big names like Microsoft and Amazon in the coding and AI space.

The Fault in Our Stars

Sector 6 | The Newsletter of AIM • 0 implied HN points • 06 Apr 23
🕹 Technology AI Ethics Safety Development Criticism
  1. OpenAI has faced criticism and calls for a pause on its AI experiments, particularly around powerful models like GPT-4.
  2. The company claims to be working on developing safe and responsible AI systems, but many experts doubt the effectiveness of this approach.
  3. Some critics view OpenAI's recent communication as just a public relations effort without real substance.

The Curious Case of ChatGPT API Pricing

Sector 6 | The Newsletter of AIM • 0 implied HN points • 05 Mar 23
🕹 Technology AI Software APIs Development Enterprise
  1. ChatGPT's API has made it easier for businesses to use its features at a lower cost. This is helping many companies save money and improve their services.
  2. The reduction in costs associated with ChatGPT's API is likely to attract more users and increase its popularity. More people will want to try it out for their projects.
  3. Keeping some services free for a longer time can be beneficial for businesses, as it can lead to better long-term results. A company mentioned that their runway improved significantly after using ChatGPT's API.

GitHub Copilot: Indian IT Skepticism

Sector 6 | The Newsletter of AIM • 0 implied HN points • 02 Mar 23
🕹 Technology AI Software Development Coding Ethics
  1. There is a split in the Indian IT community between those who favor GitHub Copilot and those who prefer IBM CodeNet for coding assistance. Some developers are uncertain about which tool to trust.
  2. A class action lawsuit has been filed against Microsoft, OpenAI, and GitHub, accusing them of improperly using licensed code to develop Copilot. This legal challenge has caused concern for the companies involved.
  3. The skepticism around GitHub Copilot reflects broader worries about the use of AI in development. Many in the industry are cautious about how these tools might impact their work.

Node's getting TypeScript support

Andrew's Substack • 0 implied HN points • 30 Jul 24
🕹 Technology Programming Software Development Web Tools Open Source
  1. Node.js is getting support to run TypeScript files directly, making it easier for developers to work with TypeScript without the need for extra setups or tools.
  2. Currently, this TypeScript support will only allow basic features, meaning some advanced features like enums aren't included yet; however, most features will still be usable.
  3. Even though you can run TypeScript files, published packages on npm won't support TypeScript for now to avoid complicating things further.

AI Engineer World's Fair–Day 3: The Horizon and Beyond

Code and Context • 0 implied HN points • 29 Jun 24
🕹 Technology AI Development Ethics Innovation Research
  1. AI is becoming smarter and can now see, hear, and understand like people. This means it can handle more complex tasks.
  2. New tools for developing AI are being created, making it easier for engineers to work with AI technologies.
  3. There's an important focus on ethics and the impact of AI on society, ensuring that technology is used responsibly.

Attending the AI Engineer World's Fair–Introduction

Code and Context • 0 implied HN points • 29 Jun 24
🕹 Technology AI Software Development Innovation Ethics
  1. The AI Engineer World's Fair showcased the rapid developments in artificial intelligence, highlighting its transformative impact on technology. It's important to understand that AI is evolving quickly, and we need to keep up.
  2. Attendees felt a mix of excitement and concern about how AI could change our world. We should be prepared for these changes and use AI's benefits while being aware of the risks.
  3. Staying connected to our human culture is vital as we face these advancements. Engaging with art, music, and storytelling helps us hold onto our humanity amidst the rise of AI.

Improve Kotlin Code Review Part -1

Better Engineers • 0 implied HN points • 28 Mar 23
🕹 Technology Programming Software Development Engineering Code Review
  1. Kotlin has specific types like Unit and Nothing that help clarify your code. Unit shows a function has no meaningful return, while Nothing indicates a function will never finish normally, like when it throws an error.
  2. Destructuring in Kotlin allows you to unpack data structures easily. You can assign multiple values from a list or map to variables in a single line, making your code cleaner and more organized.
  3. Type aliases in Kotlin let you create simpler names for existing types. This can make your code easier to read and understand by replacing complex types with more descriptive names.

6 𝐰𝐚𝐲𝐬 to turn code into beautiful Architectural Diagrams

Better Engineers • 0 implied HN points • 01 Aug 22
🕹 Technology Software Development Engineering Design Visualization
  1. You can turn your code into diagrams using different tools. This helps visualize and understand system architectures better.
  2. Tools like Diagrams, Mermaid, and PlantUML allow you to create diagrams with simple text and code. They make it easier to track changes and modify designs.
  3. Using diagramming tools can improve communication in tech teams by providing clear visual representations of complex systems.

Github Action for Unit Testing

Better Engineers • 0 implied HN points • 06 Sep 20
🕹 Technology Software Development Automation Testing CI/CD
  1. GitHub Actions help automate tasks like building, testing, and deploying code. It's a great way to make your workflow easier and more efficient.
  2. Unit testing is important because it checks if individual parts of your code work correctly. Running these tests can help catch bugs early, saving time later on.
  3. You can set up GitHub Actions to prevent merging code if the unit tests fail. This ensures that only tested and working code makes it into your main project.

How I refactor large codebases with ChatGPT

The Future of Life • 0 implied HN points • 05 Jan 24
🕹 Technology AI Software Development Programming Automation
  1. ChatGPT can help with refactoring large codebases, but it works best when you break the project into smaller tasks.
  2. To get good results, you need to provide ChatGPT with details about your project's structure, business domain, and preferred organization methods.
  3. After ChatGPT suggests a new structure, it may take several adjustments to refine it, and you can ask for formats or scripts to help automate the setup.

Ready, Set, Test: Building Evaluation into Your LLM Workflow

LLMs for Engineers • 0 implied HN points • 13 Oct 23
🕹 Technology AI Software Development Engineering Innovation
  1. Developers need to create clear evaluation standards for large language model apps. This helps them understand what makes an app 'good' and improves user experience.
  2. The tool **llmeval** offers a systematic way to evaluate LLM applications using different methods like metrics, tools, and models. It helps teams quickly test and monitor their apps.
  3. Testing LLMs can be tricky because they often give different answers for the same input. Using sampling and setting thresholds in testing can help manage this unpredictability.

How to remove Nx cloud from your app

Shrek's Substack • 0 implied HN points • 24 Aug 23
🕹 Technology Software Development Cloud Performance Tools
  1. Nx Cloud can speed up tasks for big teams, but small projects might not need it. It's okay to skip it if you're working solo or on smaller tasks.
  2. If you encounter errors using Nx Cloud, switching to local runners is a good solution. Local runners can handle tasks without relying on the cloud.
  3. To remove Nx Cloud from your app, just change a setting in the nx.json file and switch to a local runner. You can also uninstall Nx Cloud easily with a command.

Have Gordon Ramsay do your initial code review

Shrek's Substack • 0 implied HN points • 15 Jun 23
🕹 Technology Programming Software Code Review Development Artificial Intelligence
  1. Using humor in coding reviews can help remove ego and make feedback more enjoyable. It's like having a friend point out mistakes in a fun way.
  2. Modernizing outdated code is important. Just like using fresh ingredients in cooking, using current coding practices makes your code better.
  3. Clear names and proper documentation are key. Good code should be as easy to understand as a well-labeled recipe.

The Tech Buffet #7: Better Manipulate Paths In Python With Pathlib

The Tech Buffet • 0 implied HN points • 13 Oct 23
🕹 Technology Software Programming Data science Development Coding
  1. Pathlib is a powerful alternative to the os module for managing paths in Python. It helps you work with file paths in a more intuitive way.
  2. Using Pathlib can make your code cleaner and easier to read. It's designed to handle file system paths without all the complexity of older methods.
  3. Learning Pathlib is beneficial for Python developers, especially if you frequently work with files and directories in your projects.

Multi-Modal Agentic Applications

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 23 Aug 24
🕹 Technology AI Software Development Automation Data science
  1. AI agents are software that can perform tasks and make decisions on their own. They break down complex jobs into smaller steps to make them easier to handle.
  2. These agents use various tools, including APIs and even humans, to help solve problems. This helps them be more effective and ensures safety in their operations.
  3. Multi-modal agents can use both language and vision. This makes them more powerful because they can analyze images and text together for better understanding and responses.

A Short History Of LLMs & Conversational UIs

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 13 May 24
🕹 Technology AI Data Software Development Machine Learning
  1. It's important to have a strong data plan when using AI because the technology is evolving quickly. Focusing on how to use data effectively can improve results.
  2. Many businesses struggle with using large language models because they rely on external services. Having local versions could help, but technical challenges make this tough.
  3. The use of AI in chatbot development has changed, starting from helping create better responses to managing conversations more smoothly, which makes interactions feel more natural.