The hottest Software Development Substack posts right now

And their main takeaways
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Top Technology Topics

DSW Slack Group Invitation Link

Data Science Weekly Newsletter • 19 implied HN points • 04 May 23
🕹 Technology Data science Software Development Machine Learning Artificial Intelligence Online Communities
  1. There's a Slack group for those who subscribe to Data Science Weekly. It's a great place to connect and learn together.
  2. The invite link for the Slack group is exclusive to paid subscribers, so make sure to keep it private.
  3. The group aims to help members interact, learn, and support each other in the field of data science.

[Solution]Problem 64:Group Anagrams[Amazon]

Technology Made Simple • 19 implied HN points • 11 Nov 22
🕹 Technology Coding Interviews Leetcode Software Development
  1. The problem discussed is about grouping anagrams, which involves rearranging the letters of a word or phrase to form another word or phrase.
  2. An example input is given with an array of strings and the expected output of grouping the anagrams together.
  3. Constraints for the input strings and a link to test solutions are included in the post.

Heuristic evaluation vs. user testing

UX Psychology • 39 implied HN points • 20 Jan 22
🕹 Technology UX Design Usability testing User Experience Software Development Research Studies
  1. Heuristic Evaluation involves experts examining an interface to find good and bad points, following specific industry standards for evaluation.
  2. User Testing is a more effective method since real users perform tasks on the interface, detecting major usability issues and providing valuable insights.
  3. While Heuristic Evaluation is quicker and cheaper, User Testing offers better performance estimates and detects more significant problems that affect user experience.
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Episode 40: Better Built By Burkhard

burkhardstubert • 19 implied HN points • 15 Apr 23
🕹 Technology Software Development Continuous Integration Code Quality
  1. I/O-free tests are better for Test-Driven Development (TDD) because they are faster, isolated, and repeatable. This makes them more suitable for writing reliable software.
  2. It doesn't really matter if tests are labeled as unit, integration, or acceptance tests. What matters is how easy they are to write and how quickly they run.
  3. Successful software development practices like pair programming require a supportive company culture and a willingness from each developer to learn and adapt.

😎 Developer’s Private Spot: “Harmlessly-Interruptible” vs. “Do Not Disturb”

ppdispatch • 5 implied HN points • 08 Oct 24
🕹 Technology Software Development AI Tools Workplace culture Data Management Productivity
  1. Hiring a separate Scrum Master can create unnecessary overhead, and teams might manage the process better on their own.
  2. AI coding tools like GitHub Copilot can actually increase bugs and may not reduce developer burnout as expected.
  3. Creating a work environment that supports both deep focus and collaboration can boost productivity for programmers.

Chuyện bây giờ mới kể: Made in Vietnam

Thái | Hacker | Kỹ sư tin tặc • 179 implied HN points • 27 Jun 19
🕹 Technology Open Source Operating Systems Software Development Tech Companies Cybersecurity
  1. The open source culture in technology allows people to share and use creative accomplishments, contributing to the backbone of the Internet.
  2. Vietnam has programmers involved in important open-source projects, providing a valuable way to learn, share, connect, and introduce themselves to the world.
  3. Despite the popularity of Linux worldwide, schools, companies, and government agencies in Vietnam still predominantly use Windows, showing a one-way flow of technology from the world into Vietnam.

Am I still relevant as a programmer now that there's AI?

Andrew's Substack • 33 HN points • 14 Mar 23
🕹 Technology AI Programming Software Development Machine Learning
  1. Computers can now do impressive things with AI like answer questions and generate code or art.
  2. Concerns exist over the relevance of human programmers in the future due to advancements in AI technology.
  3. To remain pertinent, focus on developing human skills, learn about AI, and stay updated on software development practices involving AI.

Toward Better AI Milestones

Am I Stronger Yet? • 15 implied HN points • 20 Nov 23
🕹 Technology Software Development Machine Learning Artificial Intelligence
  1. Defining good milestones for AI progress is challenging due to the evolution of tasks as AI capabilities advance.
  2. Milestones should focus on real-world tasks with economic implications to avoid proxy failures.
  3. Measuring AI progress through milestones like completing software projects independently or displacing human workers in certain jobs can provide insights on capabilities and real-world impact.

Week 80 - E8 - 🤖 AI Integration for Faster, Better Product Development

The Product Channel By Sid Saladi • 10 implied HN points • 25 Feb 24
🕹 Technology Artificial Intelligence Product Management Market Analysis Decision-making Software Development
  1. Artificial Intelligence (AI) is a pivotal force in reshaping industries, offering product managers opportunities to enhance their development lifecycle.
  2. Integrating AI into product development leads to reduced time-to-market, increased efficiency, and better resonance with users.
  3. AI helps in enhancing ideation by analyzing customer feedback, conducting market research, and generating innovative concepts to uncover promising opportunities.

Episode 38: Better Built By Burkhard

burkhardstubert • 19 implied HN points • 16 Mar 23
🕹 Technology Software Development Continuous Delivery Metrics DevOps Performance
  1. Continuous Delivery (CD) means making software ready for users quickly and consistently. It's important for teams to measure their progress with metrics to see how well they are doing.
  2. High-performance teams benefit from focusing on both stability and throughput to deliver great software. Balancing these two areas helps reduce bugs while keeping updates frequent.
  3. Setting clear goals for deployment and recovery times can lead to better software and happier customers. Fast response to issues helps retain customer trust and satisfaction.

Through Your User's Eyes

Tribal Knowledge • 19 implied HN points • 10 Jan 23
🕹 Technology Usability User Experience Software Development Web3 Customer Feedback
  1. Users don't see products like creators do. They focus on the problem and need the solution to be presented clearly and function well.
  2. Understanding the technical capabilities of users is crucial. Intuitive design is key, as Apple exemplifies in their products.
  3. Building with user experience in mind is essential. Software should be intuitive, especially for everyday consumers, as clunky designs are no longer tolerated.

Context matters

Sunday Letters • 59 implied HN points • 24 Oct 21
🕹 Technology Software Development Product Management Design principles Engineering Practices
  1. Finding the right balance between short-term and long-term focus is important in building complex software. You need to address immediate issues without losing sight of broader goals.
  2. Metrics should reflect real business goals, not just vanity numbers. It's better to watch user engagement than just sales figures.
  3. Being able to switch between different contexts and focus on what's most important is a key skill for engineers and business people. Understanding where to concentrate your efforts can greatly impact success.

Episode 36: Better Built By Burkhard

burkhardstubert • 19 implied HN points • 15 Feb 23
🕹 Technology Software Development Embedded Systems Continuous Delivery Automation Quality Assurance
  1. A Continuous Delivery pipeline helps keep software always ready for release by quickly identifying problems at various stages.
  2. The workflow consists of three main stages: Commit Stage, Acceptance Stage, and System Stage, with each stage increasing confidence in the software's reliability.
  3. It's best to start building your CD pipeline now, even if it's simple, and improve it step by step as you learn.

KP leads Codeium's Series B

Leigh Marie’s Newsletter • 9 implied HN points • 30 Jan 24
🕹 Technology AI Startups Programming Software Development Entrepreneurship
  1. LLMs are advancing in developer tooling, capable of automating coding tasks efficiently.
  2. Some developers don't use AI-powered coding tools due to compliance, security, IP concerns, or unique codebases.
  3. Codeium evolved from an ML software company to a full-stack AI coding platform, showing the importance of iterating and customer focus.

LabKey

Axial • 7 implied HN points • 15 Mar 24
💼 Business Startups Data Management Software Development Revenue Models Partnerships
  1. LabKey provides data management solutions tailored to researchers, clinicians, and biotech companies.
  2. LabKey's evolution from a project at Fred Hutchinson Cancer Research Center to a successful software company is inspiring for startups.
  3. LabKey's strategic shift to a tiered subscription service model helped in sustaining revenue and investing in new product development.

Episode 28: Burkhard on Qt Embedded Systems

burkhardstubert • 39 implied HN points • 04 Apr 22
🕹 Technology Embedded Systems Software Development Programming Cloud Computing Agile Methodology
  1. Burkhard is switching from a newsletter format to a blog for sharing his thoughts on Qt Embedded Systems. He believes this will help him attract more readers and focus better on his writing.
  2. There are different levels of architecture diagrams for Qt embedded systems, such as context and container levels. These diagrams help in understanding system interactions and can guide the organization of development teams.
  3. Spotify uses a unique structure for its teams, like squads and tribes, to encourage communication and collaboration. This approach helps address dependencies between teams and enhances productivity.

💀 Life & Death (?) of Stack Overflow

HackerPulse Dispatch • 8 implied HN points • 20 Feb 24
🕹 Technology Software Development Artificial Intelligence Coding API Data handling
  1. Understanding popular Stack Overflow questions reveals insights on efficiency, mastering tools, and effective problem-solving in coding.
  2. Monitoring Stack Overflow questions can provide developers with valuable signals for documentation improvements and API enhancements.
  3. The emergence of AI, like OpenAI's Codex and GitHub Copilot, is impacting traditional coding platforms like Stack Overflow, causing a decline in traffic and engagement.

The Busy Trap: How to Distinguish Being Busy from Being Productive

Wisdom over Waves • 3 HN points • 06 Mar 24
🕹 Technology Productivity Software Development Collaboration Code Review
  1. The bulk of a work item's lifecycle in software development is often spent waiting in queues, not in active development or QA activities, highlighting inefficiencies in the process.
  2. More planning and parallel tasks do not necessarily lead to increased productivity; streamlined processes and effective collaboration are key for true productivity.
  3. Individual busyness does not equate to team productivity; focusing on removing bottlenecks and promoting collaborative efforts leads to faster project timelines and meaningful progress.

A Deep Dive on AI Inference Startups

East Wind • 3 HN points • 10 Jul 24
🕹 Technology AI Startups Venture Capital Software Development Market Trends
  1. AI inference startups help companies use AI without needing a strong technical team. They make it easier to access and manage AI models through simple APIs.
  2. The competition in the AI inference space is tough, with many companies offering similar prices and performance. This makes it challenging for any single startup to stand out.
  3. Investors need to believe that the market for AI inference will grow significantly, and these startups will need to expand their product offerings or be attractive acquisition targets for larger companies.

#48

The Nibble • 7 implied HN points • 24 Feb 24
🕹 Technology AI Crypto Web Development Software Development Data Structures
  1. Feedback is being sought for the newsletter content to better cater to readers' interests.
  2. Interesting developments in the tech world include potential $7 trillion AI chip funding, Reddit IPO unique share distribution, and US Tech getting into the Indian market.
  3. Noteworthy advancements in AI technologies, such as new models like LLM streaming and fast inference engines, are shaping diverse industries.

Soft software

johan’s substack • 1 HN point • 06 Jun 24
🕹 Technology Language Models Software Development Artificial Intelligence Human-AI Interaction
  1. Human language can be seen as executable, prompts serve as soft software that triggers computational processes within language models.
  2. Soft software interacts with language models in a fluid and non-deterministic manner, akin to a read-evaluate-print loop with state.
  3. Soft software creation in the Semioscape involves embracing uncertainty, exploring, and co-adapting with language models as a medium for inventive exploration.

Data Science Weekly - Issue 472

Data Science Weekly Newsletter • 19 implied HN points • 08 Dec 22
🕹 Technology Data science Machine Learning Artificial Intelligence Software Development Data Engineering
  1. Machine learning can unintentionally develop biases from training data, which is important to detect and fix, especially in critical areas like healthcare and self-driving cars.
  2. Google Sheets now offers a way to use machine learning without coding skills, making it accessible for everyone to perform simple data tasks like predicting values and identifying anomalies.
  3. There is a trend in tech companies to make machine learning processes happen in real-time, which can lead to faster and more efficient data insights.

Data Science Weekly - Issue 471

Data Science Weekly Newsletter • 19 implied HN points • 01 Dec 22
🕹 Technology Data science Machine Learning Artificial Intelligence Software Development Analytics
  1. MLOps is important for automating and managing machine learning products. It helps researchers and practitioners understand the principles and challenges of operating ML systems.
  2. Companies face trade-offs when transitioning to real-time machine learning pipelines. They must balance performance, cost, and infrastructure complexity to find the best solution.
  3. The FDA and other agencies have created guiding principles for using machine learning in medical devices. These principles aim to ensure the safety and effectiveness of AI/ML in healthcare.

Data Science Weekly - Issue 470

Data Science Weekly Newsletter • 19 implied HN points • 24 Nov 22
🕹 Technology Data science Machine Learning Artificial Intelligence Data Engineering Software Development
  1. Using recommender systems can lead to problems like clickbait and addiction if they're only focused on engagement. We need to think differently to create better systems that really serve people's needs.
  2. GitLab has a detailed Data Team Handbook that explains how their data team works, what data is available, and how it helps different departments make decisions. This can guide other teams looking to improve their data processes.
  3. Deep learning techniques are being researched to playtest video games like Candy Crush. This shows how AI can create more human-like testing methods and improve the gaming experience.

A Letter to Devs: What to Expect from Product Managers

Odai’s Substack • 3 HN points • 12 Feb 24
🕹 Technology Product Management Software Development Collaboration Innovation User Feedback
  1. Product Managers need to excel in figuring out the next most valuable thing to build and bring clarity to the dev team.
  2. Product Management involves a structured 'discovery' process with stages like framing, observation, synthesis, strategy, and prototyping.
  3. Product Managers should show the value proposition of what is being built, provide clear direction during development, and measure outcomes to ensure usefulness.

The Blurred Line Between Methodology and Framework

Building Rome(s) • 13 implied HN points • 24 Aug 23
🕹 Technology Methodology Framework Software Development Agile Project management
  1. The role of a Technical Program Manager (TPM) involves defining and implementing the methodology and framework for software development projects.
  2. Methodologies provide general principles while frameworks offer specific plans of action.
  3. It's important for TPMs to be flexible in choosing the right methodology and framework based on the project's specific needs and requirements.

Beware programmer traps!

Sunday Letters • 39 implied HN points • 21 Nov 21
🕹 Technology Software Development User Experience Programming Web Development Product Design
  1. It's hard for people in tech to explain ideas to non-technical folks. What seems clear to a programmer can be confusing to others.
  2. Designing products based on complex models can lead to failure if they don’t connect with everyday users. Sometimes, simpler products that reflect real user needs work better.
  3. Being aware of different perspectives is key. User testing helps ensure ideas make sense to everyone, not just those with technical backgrounds.

Exploring Claude 3: A Comprehensive Analysis and Practical Guide

The AI Observer • 6 implied HN points • 05 Mar 24
🕹 Technology AI Tech industry API Artificial Intelligence Software Development
  1. Claude 3 comes as part of a trio, with Haiku, Sonnet, and Opus models each offering unique strengths and pricing structure.
  2. Claude 3 models showcase advances in nuanced understanding and offer high accuracy, with Opus doubling accuracy compared to previous versions.
  3. The comprehensive guide on interacting with Claude's API in a C# environment provides a step-by-step instruction for building a console app to engage with the latest models.