The hottest Software Development Substack posts right now

And their main takeaways
Category
Top Technology Topics

✨🎄 Some AGI optimism: an early Xmas present

Faster, Please! • 639 implied HN points • 23 Dec 24
🕹 Technology Artificial Intelligence Machine Learning Data science Software Development Tech Innovation
  1. OpenAI has released a new AI model called o3, which is designed to improve skills in math, science, and programming. This could help advance research in various scientific fields.
  2. The o3 model performs much better than the previous model, o1, and other AI systems on important tests. This shows significant progress in AI performance.
  3. There's a feeling of optimism about AGI technology as these advancements might bring us closer to achieving more intelligent and capable AI systems.

10 Situations Where Scrum Is a Burden For Developers

Ageling on Agile • 79 implied HN points • 10 Oct 24
🕹 Technology Software Development Agile Methodology Project management Team Collaboration Product Management
  1. Scrum is not always the best fit for software teams. It works well in complex environments but can become a hassle if the situation is straightforward.
  2. When teams don't need to work together, like in the case of maintenance or support tasks, Scrum can feel unnecessary and unhelpful.
  3. If there’s no proper interaction with stakeholders or a culture of learning, the Scrum framework can hinder progress instead of helping it.

Reflections on Palantir

Nabeel S. Qureshi • 1678 implied HN points • 15 Oct 24
💼 Business Tech Companies Data Integration Software Development Corporate culture Entrepreneurship
  1. Palantir focuses on solving tough problems in important industries like healthcare and manufacturing. The company aims to tackle complex issues that others often ignore, offering a unique opportunity for engineers who want to make a real impact.
  2. The role of forward deployed engineers (FDEs) is key at Palantir. They work closely with customers to understand their needs and integrate data effectively, helping to create software solutions that solve real business problems.
  3. The culture at Palantir is intense and promotes open communication, where criticism and debate are welcomed. This environment encourages employees to think deeply and cultivate a unique set of skills that can lead to successful startups.

Reflections on 2024 and Exciting Plans for 2025

Confessions of a Code Addict • 529 implied HN points • 18 Dec 24
🕹 Technology Software Development Community Building Content creation Subscriptions Programming Languages
  1. The community grew a lot in 2024, from 4,212 to about 9,380 readers. This shows that more people are enjoying the content and getting involved.
  2. There will be new perks for paid subscribers in 2025. This includes early access to articles and a new series sharing resources and interesting materials.
  3. Upcoming live sessions will include interactive discussions on research papers. This will help everyone understand complex topics better together.

Claude Sonnet 3.7 Compared with Previous AI Models

Jakob Nielsen on UX • 13 implied HN points • 25 Feb 25
🕹 Technology AI User Experience Web Design Usability Software Development
  1. The new AI model, Claude Sonnet 3.7, performs better than previous versions and outperforms other models, like Grok 3, in explaining key concepts like Jakob's Law.
  2. Jakob's Law highlights that users form their expectations based on their experiences with other websites. This means that following common design patterns is crucial for creating a user-friendly experience.
  3. Interactive demos created by AI can help users see how standard and non-standard designs affect usability, making it easier to understand the importance of sticking to familiar web conventions.
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The AI Agent Spectrum

Democratizing Automation • 451 implied HN points • 18 Dec 24
🕹 Technology AI agents Reinforcement Learning Software Development Digital Tools Automation
  1. AI agents need clearer definitions and examples to succeed in the market. They're expected to evolve beyond chatbots and perform tasks in areas where software use is less common.
  2. There's a spectrum of AI agents that ranges from simple tools to more complex systems. The capabilities of these agents will likely increase as technology advances, moving from basic tasks to more integrated and autonomous functionalities.
  3. As AI agents develop, distinguishing between open-ended and closed agents will become important. Closed agents have specific tasks, while open-ended agents can act independently, creating new challenges for regulation and user experience.

No more shell scripts!

Wednesday Wisdom • 94 implied HN points • 29 Jan 25
🕹 Technology Software Development Programming Languages Open Source Automation
  1. Shell scripts used to be great for automating tasks, but they have many limitations now. New programming languages do a better job and are more reliable.
  2. The Unix system made software development easier with tools and commands that could be combined. This modular approach set a solid foundation for coding.
  3. While shell scripts were revolutionary, modern programming languages and libraries have improved our ability to write better and more efficient programs.

Clean Code — Writing Readable and Maintainable Code

Weekly PHP • 19 implied HN points • 22 Oct 24
🕹 Technology Software Development Web Development Coding Practices Frameworks
  1. Clean code is all about making your code easier to read and understand. This helps other developers (and your future self) when they look at your work later.
  2. Small changes in how you write code can make a big difference. Focusing on readability can lead to fewer bugs and easier maintenance over time.
  3. Using coding principles from the book 'Clean Code' can help improve your coding habits. Following these guidelines makes your projects more manageable and enjoyable.

7 Lessons I Learned the Hard Way From 9+ Years as a Data Engineer

SeattleDataGuy’s Newsletter • 730 implied HN points • 21 Nov 24
🕹 Technology Data Engineering Software Development Career Advice Project management Skills Training
  1. It's important to avoid building complex systems just for the sake of it. Focus on creating infrastructure that actually helps your team and the business.
  2. If you don’t plan your data model, you’ll end up with a messy one. Always take the time to design it properly to make future work easier.
  3. Good communication is really powerful. Being able to share your ideas clearly can help you get support and make a bigger impact in your projects.

Object-Oriented Brain Rot

Burning the Midnight Coffee • 96 implied HN points • 31 Jan 25
🕹 Technology Software Development Object Oriented Programming Systems Engineering Software Design Computer Science
  1. When modeling objects like rectangles and squares, thinking too rigidly can lead to problems. Sometimes, it's simpler to just write a function to handle what you need rather than forcing everything into class hierarchies.
  2. Object-oriented programming can sometimes make things overly complicated. It's better to focus on solving the actual problem instead of worrying about fitting everything into a strict structure.
  3. Learning to think in terms of complex class hierarchies can actually harm your ability to solve problems. Simple, direct solutions are often more effective than trying to model everything in a complicated way.

Software Quality

Engineering Enablement • 21 implied HN points • 12 Feb 25
🕹 Technology Software Development Engineering Practices Product Management Developer Productivity Quality Assurance
  1. Software quality has four main types: process quality, code quality, system quality, and product quality. Each type affects the others, so improving one can help improve the rest.
  2. Process quality is crucial because a good development process leads to better code quality. This means having proper testing and code reviews can help avoid defects later on.
  3. Product quality is what customers experience and it includes a product's usability and reliability. Engineers need to team up with product managers to ensure that products meet customer needs.

We need to talk about AI

Unreported Truths • 29 implied HN points • 30 May 25
🕹 Technology AI Ethics Software Development Future Trends Automation Innovation
  1. Many people believe AI will change our world quickly, but it's hard to know how true that is. People have different opinions and experiences with AI.
  2. AI can do some tasks well, like coding and answering questions, but it often lacks creativity and originality. It mimics emotions but doesn't really challenge users.
  3. The future of AI is uncertain, and it's important to hear from others about their views and experiences with it. There may be real risks or benefits ahead.

How Did LinkedIn Handle 7 Trillion Messages Daily With Apache Kafka?

VuTrinh. • 299 implied HN points • 13 Aug 24
🕹 Technology Data Engineering Infrastructure Software Development Open Source
  1. LinkedIn uses Apache Kafka to manage a massive flow of information, handling around 7 trillion messages every day. They set up a complex system of clusters and brokers to ensure everything runs smoothly.
  2. To keep everything organized, LinkedIn has a tiered system where data is processed locally in each data center, then sent to an aggregate cluster. This helps them avoid issues from moving data across different locations.
  3. LinkedIn has an auditing tool to make sure all messages are tracked and nothing gets lost during transmission. This helps them quickly identify any problems and fix them efficiently.

Historically, 4NF explanations are needlessly confusing

Minimal Modeling • 608 implied HN points • 05 Dec 24
🕹 Technology Database Design Data Structures Software Development Information Systems
  1. Fourth Normal Form (4NF) is mainly about creating simple two-column tables to link related data, like teachers and their skills. This straightforward design is often overlooked in favor of complex definitions.
  2. Many explanations of 4NF start with confusing three-column tables and then break them down into simpler forms. This approach makes it harder for learners to grasp the concept quickly and effectively.
  3. The term 'multivalued dependency' can be simplified to just mean a list of unique IDs. You don’t really need to focus on this term to design good database tables; it's more of a historical detail.

A Visual Guide to Mamba and State Space Models

Exploring Language Models • 3942 implied HN points • 19 Feb 24
🕹 Technology Artificial Intelligence Machine Learning Data science Software Development Algorithm Design
  1. Mamba is a new modeling technique that aims to improve language processing by using state space models instead of the traditional transformer approach. It focuses on keeping essential information while being efficient in handling sequences.
  2. Unlike transformers, Mamba allows for selective attention, meaning it can choose which parts of the input to focus on. This makes it potentially better at understanding context and relevant information.
  3. The architecture of Mamba is designed to be hardware-friendly, helping it to perform well without excessive resource use. It uses techniques like kernel fusion and recomputation to optimize speed and memory use.

My Wronggest Content

Jacob’s Tech Tavern • 656 implied HN points • 26 Nov 24
🕹 Technology Social media Software Development Marketing Content creation Programming
  1. Posting wrong code online can lead to getting helpful feedback from others. Sometimes people are quick to point out mistakes, but that can help you learn.
  2. Using social media regularly can grow your audience. Posting interesting and engaging content helps attract more subscribers.
  3. Accepting criticism is important. It can be tough to hear people say your work is bad, but it's a chance to improve and grow.

"Don't talk to strangers" also applies to software development.

System Design Classroom • 499 implied HN points • 19 Jul 24
🕹 Technology Software Development System Design Programming Software Engineering Architecture
  1. Loose coupling is important in software. It means different parts of a program should depend on each other as little as possible, making it easier to change and fix things.
  2. The Law of Demeter suggests that objects should only talk to their direct friends and not reach out too far. This helps to keep dependencies low and makes code more manageable.
  3. Using strategies like the Single Responsibility Principle, interfaces, and dependency injection can improve your code's structure. This makes modules clear, easy to test, and maintain.

OpenAI's o1 using "search" was a PSYOP

Democratizing Automation • 435 implied HN points • 04 Dec 24
🕹 Technology AI Research Machine Learning Data science Computer Science Software Development
  1. OpenAI's o1 models may not actually use traditional search methods as people think. Instead, they might rely more on reinforcement learning, which is a different way of optimizing their performance.
  2. The success of OpenAI's models seems to come from using clear, measurable outcomes for training. This includes learning from mistakes and refining their approach based on feedback.
  3. OpenAI's approach focuses on scaling up the computation and training process without needing complex external search strategies. This can lead to better results by simply using the model's internal methods effectively.

LLMs Fight With Both Hands Tied Behind Their Back

Am I Stronger Yet? • 313 implied HN points • 27 Dec 24
🕹 Technology Artificial Intelligence Machine Learning Programming Data science Software Development
  1. Large Language Models (LLMs) like o3 are becoming better at solving complex math and coding problems, showing impressive performance compared to human competitors. They can tackle hard tasks with many attempts, which is different from how humans might solve them.
  2. Despite their advances, LLMs struggle with tasks that require visual reasoning or creativity. They often fail to understand spatial relationships in images because they process information in a linear way, making it hard to work with visual puzzles.
  3. LLMs rely heavily on knowledge in their 'heads' and do not have access to real-world knowledge. When they gain access to more external tools, their performance could improve significantly, potentially changing how they solve various problems.

Can LLMs earn $1M freelancing?

HackerPulse Dispatch • 5 implied HN points • 21 Feb 25
🕹 Technology AI Machine Learning Software Development Multimodal models Freelancing
  1. AI models are being tested to see if they can earn a million dollars through freelancing. But it turns out many of them struggle with real-world tasks.
  2. A new video model can create high-quality videos from text descriptions. It uses advanced techniques to improve video quality and generation.
  3. Small AI models can perform better when they are trained on easier tasks instead of trying to learn from more complex ones.

Cultivate a Privacy-First Mindset

Building Rome(s) • 3 implied HN points • 17 Feb 25
🕹 Technology Data Privacy AI Ethics Product Management Software Development
  1. Privacy is super important for AI products, and Technical Program Managers (TPMs) play a key role in keeping user data safe and building trust.
  2. TPMs should involve legal and privacy teams early in the project to make sure privacy is part of the design, not an afterthought.
  3. It's essential to prioritize privacy throughout the development process, treating any privacy issues as top priorities and integrating privacy checks at every stage.

On Typing Chinese

Reboot • 31 implied HN points • 03 Feb 25
🕹 Technology Digital Literacy Software Development Cultural impact User Interfaces Language processing
  1. Typing in Chinese is complex because it involves using different input methods to represent thousands of characters. This process can be frustrating and often requires negotiating between what you want to say and how the computer interprets your typing.
  2. There is a digital divide in China between generations and socioeconomic groups. Younger people are more familiar with technology, while older individuals may struggle to adapt, leading to varying experiences in the digital world.
  3. Moving from typing Chinese to English can be challenging, as it requires adjusting your muscle memory and skills. This switch highlights how language and technology can create feelings of exclusion for those not fully versed in the dominant digital practices.

Multi-robot collaboration,Grok 3 , smallest video language model, Generative AI Model for Gameplay, AI co-scientist, Mistral Saba, Fiverr Go, Step-Video-T2V and Step-Audio, Pikaswaps & more

AI Brews • 15 implied HN points • 21 Feb 25
🕹 Technology Artificial Intelligence Robotics Machine Learning Software Development Open Source
  1. Grok 3 is a powerful reasoning model that can handle a massive amount of information at once, making it one of the best tools for chatbots right now.
  2. New advancements in AI, like the Vision-Language-Action model Helix and the generative AI model Muse, are making robots smarter and more capable in their tasks.
  3. AI tools are getting more user-friendly, such as Pikaswaps, which allows you to easily replace parts of videos with your own images, making editing simpler for everyone.

Data's final format

Data People Etc. • 391 implied HN points • 09 Dec 24
🕹 Technology Data Management Cloud Computing Software Development Tech Innovation
  1. Apache Iceberg™ is a popular way to manage data, offering features like scalability and openness. However, using it can feel complicated and less exciting than expected.
  2. CSV format is an easy and humble way to manage data, requiring no special knowledge or complex setups. It’s simple and widely understood, making it a go-to choice for many.
  3. The transformation of data management, like Iceberg™, is like building a transcontinental railroad. It's a huge effort aimed at improving the way we process and use information in the modern world.

BLT: Byte Latent Transformer

Gonzo ML • 315 implied HN points • 23 Dec 24
🕹 Technology Artificial Intelligence Machine Learning Data processing Software Development Innovation
  1. The Byte Latent Transformer (BLT) uses patches instead of tokens, allowing it to adapt based on the complexity of the input. This means it can process simpler inputs more efficiently and allocate more resources to complex ones.
  2. BLT can accurately encode text at a byte level, overcoming issues with traditional tokenization that often lead to mistakes in understanding languages and simple tasks like counting letters.
  3. BLT architecture has shown better performance than older models, handling tasks like translation and sequence manipulation more effectively. This advancement could improve the application of language models across different languages and reduce errors.

Why Teams Will Break This Year (and How to Fix Them) | Battery Venture’s Dharmesh Thakker

Dev Interrupted • 14 implied HN points • 11 Feb 25
🕹 Technology AI Tools Software Development Engineering Teams Tech industry Productivity
  1. AI could greatly help developers by automating routine tasks and improving productivity. It's important for teams to embrace these changes to stay effective.
  2. Communication is crucial in engineering teams. It's vital to allow junior developers to learn from their mistakes and for everyone to share insights openly.
  3. Good management practices are often lacking but very valuable. Establishing clear goals and regular check-ins can help teams perform better.

Apache Kafka - Overview

VuTrinh. • 539 implied HN points • 06 Jul 24
🕹 Technology Data Engineering Software Development Systems Architecture Distributed Systems
  1. Apache Kafka is a system for handling large amounts of data messages, making it easier for companies like LinkedIn to manage and analyze user activity and other important metrics.
  2. In Kafka, messages are organized into topics and divided into partitions, allowing for better performance and scalability. This way, different servers can handle parts of the data at once.
  3. Kafka uses a pull model for consumers, meaning they can request data as they need it. This helps prevent overwhelming the consumers with too much data at once.

Stuff Worth Reading - Sep 2024

clkao@substack • 79 implied HN points • 30 Sep 24
🕹 Technology Software Development Version Control Analytics Pricing Strategy
  1. GitHub succeeded because it created tools that developers really wanted and used. The combination of Git's technical features and GitHub's social features made it very popular.
  2. The analytics and data workflow still lag behind traditional development methods. It's important to find better ways to show the value of data to businesses.
  3. There's a new way to think about pricing that considers what buyers really want, not just traditional methods. This can lead to smarter pricing strategies.

The CTO’s Hidden Notebook

The CTO Substack • 339 implied HN points • 26 Jul 24
🕹 Technology Productivity Tools Note Taking Knowledge Management Software Development Personal Development
  1. Taking notes is about more than just gathering information. It's about building your own understanding and knowledge over time.
  2. Using a structured method, like the Zettelkasten system, can help you organize your thoughts and learn more effectively.
  3. Writing regularly about what you learn can change how you approach your work and meetings, making them opportunities for growth.

Seven things I know after 25 years of development

zverok on lucid code • 57 implied HN points • 27 Jan 25
🕹 Technology Software Development Programming Conferences Technical Writing
  1. After many years of working in development, it's clear that balancing technical skills with human connection is crucial. Building good relationships can make a big difference in your career.
  2. Learning is a lifelong journey, and it's important to be open to new ideas and changes in the industry. Staying curious helps you adapt and grow.
  3. Reflecting on personal and professional lessons can lead to meaningful growth. Taking time to think about your experiences is valuable for future decisions.

The value of grunge work

Wednesday Wisdom • 113 implied HN points • 15 Jan 25
🕹 Technology Software Development Agile Methodology Tech Debt Work Culture Engineering Practices
  1. Tech debt happens when we make bad decisions in software development. It can pile up, making fixing problems a big task for teams.
  2. Doing hands-on work, or 'grunge work,' helps deepen understanding of the tech systems. It’s crucial for maintaining and improving technology.
  3. To tackle tech debt effectively, it should be part of official job expectations. This way, everyone contributes and helps keep things running smoothly.

Being an Engineering Manager at Meta

Leading Developers • 100 implied HN points • 14 Jan 25
🕹 Technology Software Development Engineering Management Company Culture Leadership Career development
  1. At Meta, managers are there to support their engineers, who have the freedom to choose their projects and set goals. This leads to a culture where trust and autonomy help engineers excel.
  2. Managers at Meta are evaluated based on the impact of their team and how they help individual contributors grow. It's important for managers to realize their role in coaching and supporting their engineers, rather than taking credit for their success.
  3. Meta encourages a fast-paced environment where developers can easily set up their work and start contributing quickly. This focus on efficiency comes from long-term investments in tools that make working faster and smoother.

GenAI Isn’t Replacing Devs (And It Shouldn’t)

HackerPulse Dispatch • 8 implied HN points • 18 Feb 25
🕹 Technology Software Development Artificial Intelligence Programming Languages Engineering Tech industry
  1. Firing programmers to replace them with AI can backfire. Companies might end up facing big problems like untrained workers and high costs to hire good developers back.
  2. Experience and human intuition are important in software development. AI can't solve every problem, and skilled developers are still needed for complex tasks.
  3. The new Python 3.14 interpreter will make code run faster without needing any changes. This is great for developers because it saves time and effort.

Report: OpenAI Spends Millions a Year Miscounting the R's in 'Strawberry'

The Algorithmic Bridge • 573 implied HN points • 22 Nov 24
🕹 Technology Artificial Intelligence Machine Learning Tech Ethics Data science Software Development
  1. OpenAI has spent a lot of money trying to fix an issue with counting the letter R in the word 'strawberry.' This problem has caused a lot of confusion among users.
  2. The CEO of OpenAI thinks the problem is silly but feels it's important to address because users are concerned. They are also looking into redesigning how their models handle letter counting.
  3. Some employees joked about extreme solutions like eliminating red fruits to avoid the R issue. They are also thinking of patches to improve letter counting, but it's clear they have more work to do.

Practical Data Engineering using AWS Cloud Technologies

VuTrinh. • 339 implied HN points • 23 Jul 24
🕹 Technology Cloud Computing Data Engineering Software Development Information Systems
  1. AWS offers a variety of tools for data engineering like S3, Lambda, and Step Functions, which can help anyone build scalable projects. These tools are often underused compared to newer options but are still very effective.
  2. Services like SNS and SQS can help manage data flow and processing. SNS allows for publishing messages while SQS aids in handling high event volumes asynchronously.
  3. Using AWS for data engineering is often simpler than switching to modern tools. It's easier to add new AWS services to your existing workflow than to migrate to something completely new.

GPTs Are Maxed Out

The Algorithmic Bridge • 647 implied HN points • 11 Nov 24
🕹 Technology AI Computing Machine Learning Data science Software Development
  1. AI companies are hitting limits with current models. Simply making AI bigger isn't creating better results like it used to.
  2. The upcoming models, like Orion, may not meet the high expectations set by previous versions. Users want more dramatic improvements and are getting frustrated.
  3. A new approach in AI may focus on real-time thinking, allowing models to give better answers by taking a bit more time, though this could test users' patience.

Data Science Weekly - Issue 559

Data Science Weekly Newsletter • 219 implied HN points • 08 Aug 24
🕹 Technology Data science AI Machine Learning Software Development Statistics
  1. Camera calibration is crucial in sports analysis. It helps track players' movements accurately by mapping video frame positions to real field locations.
  2. Understanding the context of data is important for responsible data work. Datasets need good documentation and stories to highlight their historical and social backgrounds.
  3. There's a new, free encyclopedia for learning about cognitive science. It offers easy-to-read articles on various topics for students and researchers.

In The Context Of Long Context

Adjacent Possible • 553 implied HN points • 21 Nov 24
🕹 Technology AI Machine Learning Software Development Innovation Digital Media
  1. A new AI feature can turn a whole book into a fun audio conversation, making learning more engaging. This feature has caught a lot of attention online and even received media coverage.
  2. The ability of the AI to handle large amounts of text—up to 1.5 million words—makes it much more useful for users, allowing for better, more detailed interactions.
  3. Long context models can help organizations make better decisions by recalling important documents and past experiences, adding a new kind of intelligence to team discussions.