The hottest Software Engineering Substack posts right now

And their main takeaways
Category
Top Technology Topics

Burning Rangers: the 1997-12-20 build

Rings of Saturn • 43 implied HN points • 18 Dec 24
🕹 Technology Software Engineering
  1. There's a playable demo of the game 'Burning Rangers' from a 1997 build. It has many unique features and glitches not found in the final version.
  2. Players can change game settings to skip certain demo parts and play missions normally. This allows for a more complete gaming experience of the prototype.
  3. The demo has several bugs and issues during gameplay, like broken swimming mechanics and crashes, which make it feel very different from the final game.

[Solution]Problem 54:Multiply Strings[Google]

Technology Made Simple • 59 implied HN points • 02 Sep 22
🕹 Technology Software Engineering
  1. The problem discussed involves multiplying two non-negative integers represented as strings without using built-in libraries or converting them directly to integers. This approach is used to prevent overflow.
  2. Understanding the process of multiplication and breaking it down into individual steps is crucial in tackling problems like this. It helps in figuring out the next steps and finding a path forward.
  3. Consider unique approaches, such as examining how computers encode characters and utilizing this knowledge to work around constraints. Building a strong foundation in software engineering fundamentals is beneficial for problem-solving.

Reflections on the React community

Optimism (for the web) • 10 implied HN points • 11 Aug 25
🕹 Technology Software Engineering
  1. React has built a big community and ecosystem, mostly because it's stable and allows for good architecture. This helps developers build great things without worrying too much about changes.
  2. Managing a community like React is tough. It needs dedicated people to keep it running smoothly, and misunderstandings can lead to unnecessary stress and drama.
  3. Commercial and non-commercial projects have different goals. While React is a free tool that Meta supports, others built on it may have their own business motives, affecting how they interact with the community.

Deterministic Simulation Testing - Antithesis

Why Now • 1 implied HN point • 20 Jan 26
🕹 Technology Software Engineering
  1. Deterministic simulation testing runs your entire distributed system inside virtual machines controlled by a deterministic hypervisor so each test run is reproducible. It replaces wall-clock time with instruction-count-based virtual time so timing-dependent bugs can be replayed exactly.
  2. The platform combines property-based testing, fuzzing, and fault injection to automatically explore many scenarios and surface rare race conditions. All tests run in sandboxed clones of production so you can inject network blips and failures without risking real users.
  3. Determinism is achieved with techniques like single-core execution, intercepted time calls, and deterministic I/O plus numerous micro-optimizations. The outcome is precise, replayable failures that make debugging and fixing distributed-system bugs much easier.
Get a weekly roundup of the best Substack posts, by hacker news affinity:

Consumer-focused API Design

The API Changelog • 1 implied HN point • 17 Jan 26
🕹 Technology Software Engineering
  1. Design APIs by engaging real users first and doing product discovery so you define problems, needs, and value before building anything.
  2. Use user stories that name the user, their location (tool/context), their goal, and the benefit; these details guide the right API style and workflows.
  3. Treat API capabilities as business-aligned features that deliver clear benefits and marketable value, and adopt a product-focused mindset instead of designing for engineering convenience.

Resiliency beyond the Classic Circuit Breaker

System Design Classroom • 2 HN points • 10 Jul 24
🕹 Technology Software Engineering
  1. To handle system failures, you can use different strategies like 'Fail Fast' which stops operations quickly to save resources. But this can affect user experience because they won't get a chance to recover from the error.
  2. Another approach is 'Fail Silent', where instead of showing an error, the system quietly returns a default value. It helps keep things running smoothly, but users might miss important information if data is missing.
  3. Lastly, there's 'Custom Fallback', which uses saved local data when a service fails. This keeps the service active, but the information might be outdated, which can confuse users.

Problem 49:Min Stack[Google]

Technology Made Simple • 59 implied HN points • 27 Jul 22
🕹 Technology Software Engineering
  1. Problem 49 involves designing a stack to support various operations like push, pop, and finding the minimum element in constant time
  2. The newsletter celebrates almost reaching 50 problems by offering a special promo of 50% off the subscription for a limited time
  3. To enhance problem-solving skills, the newsletter encourages tackling challenging questions like the Boolean Satisfiability problem and provides solutions and guidance

How to crush your Daily Standups[Technique Tuesdays]

Technology Made Simple • 59 implied HN points • 12 Jul 22
🕹 Technology Software Engineering
  1. Give detailed updates in your daily standups, including your decision-making process, collaborators, important information, and technical details.
  2. Involve more stakeholders by discussing how your work impacts others, inviting collaboration for better projects.
  3. Understand and express the 'why' behind your tasks, which provides context for creating thorough solutions and requires knowledge of both Computer Science and project economics.

Should Data Teams care about Data Contracts?

The Orchestra Data Leadership Newsletter • 19 implied HN points • 05 Nov 23
🕹 Technology Software Engineering
  1. Consider data contracts if your internal data changes often to ensure collaboration between software engineering and data engineering teams.
  2. If you have important metrics that depend on software engineering actions, like defining 'Active Users,' data contracts can help maintain data quality.
  3. In cases where software engineering and data engineering roles overlap, implementing data contracts can streamline data ingestion processes and improve data quality.

The Mathematics of Scale [Math Mondays]

Technology Made Simple • 59 implied HN points • 07 Jun 22
🕹 Technology Software Engineering
  1. Economies of scale mean costs decrease as production increases, benefitting companies by spreading costs over more goods.
  2. Tech and software engineering benefit greatly from scaling and replication, allowing for efficient large-scale operations.
  3. To leverage the principles of scale for career growth, understand how your solutions fit into the big picture and build a strong foundational knowledge across different areas.

Notes on Service Level Objectives

A Small, Good Thing • 19 implied HN points • 24 Mar 25
🕹 Technology Software Engineering
  1. Service Level Objectives (SLOs) are important for understanding if services are reliable, but many organizations find them hard to use effectively. It's like a tool that sounds great but often doesn't work as well in practice.
  2. Adopting and managing SLOs usually requires a lot of effort and support from the whole team, not just the SREs. If the company culture isn't ready for it, SLOs often get ignored.
  3. There's a big gap between the theory of SLOs and how they're applied in real companies. Many teams struggle with choosing the right metrics and getting everyone to care about reliability over new features.

[Solution]Problem 21: Rotate List by k elements[Facebook/Meta]

Technology Made Simple • 79 implied HN points • 20 Jan 22
🕹 Technology Software Engineering
  1. When trying to solve a problem involving rotating a list by k elements, consider the pattern finding technique to optimize the solution.
  2. Understanding the periodic nature of the problem can help reduce the number of operations needed, especially with large values of n and k.
  3. A key insight for rotating a list by k elements is to split the list into sublists based on the pivot (k) and manipulate these sublists to achieve the desired rotation without creating new copies.

Minimum Lazy Product

Thoughts • 19 implied HN points • 18 Sep 23
🕹 Technology Software Engineering
  1. Implementing new ideas can be challenging and often requires a lot of effort to complete.
  2. Consider the concept of Minimum Lazy Product (MLP) as a minimalistic approach to presenting and validating ideas.
  3. Categorize tasks into 'Easy/Fun' and 'Hard/Unfun' to make project development more manageable and efficient.

Software Engineering Radio

One Thing at a Time • 19 implied HN points • 08 Jun 23
🕹 Technology Software Engineering
  1. Dave Cross shared his experience of being a guest on a podcast to discuss GitHub Actions.
  2. Dave Cross found Generative AI tools like ChatGPT and GitHub Copilot to significantly boost his productivity in coding.
  3. Dave Cross is exploring AI services like CodeWhisperer at the AWS Summit and is looking for work opportunities in Perl, Linux, web development, databases, and more.

How I think about product at Ribbon

ML / Genomics / Deep Tech • 38 implied HN points • 16 Sep 24
🕹 Technology Software Engineering
  1. Separate your product ideas into imperatives and experiments. Imperatives are must-have features from customer needs, while experiments are guesswork that may or may not succeed.
  2. Plan for the future by assuming your AI tools will improve. Be ready to adapt as technology gets better and make use of advancements in AI.
  3. Don't fear deleting unwanted features or code. It’s a normal part of refining your product and helps you focus on what really matters.

Bayesian Thinking for Software Engineering [Math Mondays]

Technology Made Simple • 59 implied HN points • 03 May 22
🕹 Technology Software Engineering
  1. Bayes Theorem allows us to update beliefs based on evidence, crucial for software developers making decisions.
  2. Bayesian Thinking is implicit in many decisions we make, and recognizing its importance can prevent fallacies.
  3. Learning Bayesian Thinking involves understanding intuition behind the math, using resources like StatsQuest and 3Blue1Brown.

Edition 23: A framework to securely use LLMs in companies - Part 3: Securing ChatGPT and GitHub Copilot

Boring AppSec • 84 implied HN points • 05 Sep 23
🕹 Technology Software Engineering
  1. The post discusses a framework for securely using LLMs like ChatGPT and GitHub Copilot in companies.
  2. It highlights key risks and security controls for ChatGPT, focusing on data leakage and over-reliance on AI-generated output.
  3. For GitHub Copilot, it addresses risks like sensitive data leakage and license violations, along with suggested security controls.

Workflows Give Purpose to APIs

The API Changelog • 1 implied HN point • 31 Dec 25
🕹 Technology Software Engineering
  1. Workflows turn abstract CRUD APIs into meaningful, user-focused operations by combining multiple low-level requests into a single higher-level action.
  2. A workflow operation like “onboard” can hide database details, perform lookups and validations, and make integration much easier for consumers.
  3. Workflows let teams adapt generic APIs to real use cases and prototype new operations quickly, and they enable non-technical people to define or iterate on behaviors without changing the underlying API.

The art of making Simplifying Assumptions[Technique Tuesdays]

Technology Made Simple • 39 implied HN points • 26 Jul 22
🕹 Technology Software Engineering
  1. The technique of making simplifying assumptions can help in problem-solving in various areas like System Design, Competitive Programming, and Math.
  2. Loosening computational constraints and accepting tradeoffs in performance metrics can lead to more optimal solutions by focusing on key aspects rather than trying to solve everything at once.
  3. Reducing scale, simplifying input, and picking optimal battlegrounds are strategies to make problem-solving more manageable and effective by breaking down complex problems into simpler components.

The need for beautiful code

Wednesday Wisdom • 56 implied HN points • 28 Feb 24
🕹 Technology Software Engineering
  1. Investing time in writing beautiful code is crucial for code longevity and maintainability.
  2. Code that 'mostly works' is not the standard to aim for; focus on creating code that is always functional and meets significant requirements.
  3. Developing a culture of producing beautiful code in a team requires more than guidelines and prizes; it involves a collective shift in mindset and commitment.

Zenful Estimates: Ditching Task Estimates to Build a Faster Team

Dev Interrupted • 51 implied HN points • 14 Mar 24
🕹 Technology Software Engineering
  1. Engineering task estimates are often costly in time and resources, leading to inaccuracies and increased stress within the team.
  2. Distinguishing between task estimation and project estimation can help teams prioritize better and allocate resources more effectively.
  3. By adopting a 'Zenful' approach that focuses on project estimates rather than granular task estimates, teams can save time, reduce stress, and improve overall efficiency.

AI-First in 2025: Hype, Reality, and Your Next Move

Rémi Ounadjela • 6 implied HN points • 06 Aug 25
🕹 Technology Software Engineering
  1. AI can be useful in many areas of a company, but it's important to choose the right tools carefully. Think about the problems you want to solve first.
  2. There are different levels of AI tools, ranging from basic productivity helpers to complex systems that can perform tasks on their own. Each level comes with its own benefits and risks.
  3. As you use more advanced AI tools, remember that higher risks come with higher rewards. Make sure to set up good guardrails and track how well things are working.

On the "Death of the Software Engineer by GenAI"

Laszlo’s Newsletter • 64 implied HN points • 13 Nov 23
🕹 Technology Software Engineering
  1. Software engineering has drastically improved over the years with advancements in tools and techniques like high-level abstractions and unit testing.
  2. Natural language is not suited for specifying programming instructions due to its imprecise nature, unlike the detailed specs required for coding.
  3. Generative models like ChatGPT can assist in programming tasks and improve efficiency, but they won't replace the need for human software engineers.

How a Software Engineer went from SW2 to Principal in 4 Years [StoryTime Saturdays]

Technology Made Simple • 39 implied HN points • 13 Jun 22
🕹 Technology Software Engineering
  1. Sometimes, in software engineering, it's important to simplify the solution rather than making it overly complex.
  2. In problem-solving, considering economic aspects alongside technical solutions can lead to more efficient and sustainable outcomes.
  3. To excel in software development, it's crucial to broaden your knowledge and decision-making skills beyond just coding.

[Solution]Problem 41: Create your own Datastructure with O(1) Time complexity (Dropbox)

Technology Made Simple • 39 implied HN points • 11 Jun 22
🕹 Technology Software Engineering
  1. Creating a data structure with O(1) time complexity involves implementing functions like plus, minus, get_max, and get_min efficiently.
  2. Utilizing a Doubly Linked List allows for maintaining a sorted collection of keys, enabling quick access to elements with the lowest and highest values.
  3. Developing algorithms to handle key count increments and decrements while preserving the sorted order of the linked list is crucial for a functional solution.

How to beat the critical path

Wednesday Wisdom • 47 implied HN points • 13 Mar 24
🕹 Technology Software Engineering
  1. To beat the critical path, the first step is to acknowledge its existence.
  2. Effective project planning, like utilizing the Critical Path Method (CPM), can prevent delays and ensure timely project completion.
  3. Maintaining a Directed Acyclic Graph of project activities with expected durations is crucial in project management to identify critical paths and manage dependencies effectively.

How to Make Money in Machine Learning, without doing the Math/Theory[Finance Fridays]

Technology Made Simple • 39 implied HN points • 07 May 22
🕹 Technology Software Engineering
  1. There are various ways to make money in Machine Learning beyond the traditional roles like AI research and Data Analysis, such as specializing in software engineering aspects like developing hardware, building data sources, creating pipelines, and designing platforms.
  2. Important skills to succeed in these alternative paths include writing good tests, mastering data compression and handling, and becoming proficient in large-scale system design to ensure scalability.
  3. Staying updated with ML resources and technologies like Airflow, Kubernetes, and Snowflake can be valuable for maximizing income opportunities in Machine Learning without needing to focus on the mathematics and theory aspects.