The hottest Software Engineering Substack posts right now

And their main takeaways
Category
Top Technology Topics

4 hours of work for a promotion- How a Pintrest Android Engineer made waves with a weekend project[Storytime Saturdays]

Technology Made Simple • 59 implied HN points • 06 Aug 23
🕹 Technology Software Engineering
  1. To stand out for promotions, focus on meaningful projects that showcase your skills and impact.
  2. Instead of waiting for approval, consider building a useful side project to demonstrate your value to your organization.
  3. By presenting a strong proof of concept project, you can negotiate effectively and secure impactful work opportunities for yourself.

[Solution]Problem 85: Count Complete Tree Nodes [Amazon]

Technology Made Simple • 59 implied HN points • 05 May 23
🕹 Technology Software Engineering
  1. The post discusses a problem related to counting the number of nodes in a complete binary tree, emphasizing the importance of understanding recursion, trees, and data structures.
  2. It mentions starting with a brute force solution to count nodes but highlights the need for optimization to achieve time complexity better than O(n).
  3. The approach for solving the problem involves using a recursive template to count nodes efficiently by considering the root and the number of nodes in the left and right subtrees.

Design Documents

Engineering Open Societies • 58 implied HN points • 12 Mar 23
🕹 Technology Software Engineering
  1. Design documents are essential for software engineers to communicate ideas and solutions with others.
  2. Design documents should be treated as ephemeral artifacts used to drive a collaborative process and then discarded.
  3. In design documents, focus on presenting the problem, provide solution-independent correctness conditions, and offer a solution with trade-offs and decisions.

How to Test a Private Method Inside a Widget

Widget Tricks • 58 implied HN points • 08 Mar 23
🕹 Technology Software Engineering
  1. It is recommended not to test private methods, as they are for internal use only.
  2. You may need to test a private method when working with legacy code, fixing bugs, or dealing with widget dependencies.
  3. To test a private method inside a widget, create a forwarder method, use the @visibleForTesting annotation, and follow specific steps based on widget type.

Bug Report

Software Engineering Tidbits • 58 implied HN points • 22 Mar 23
🕹 Technology Software Engineering
  1. Recommend following a 'Help me Help you' approach in software engineering
  2. In bug reports, provide clear title, priority, severity, repro steps, expected result, actual result, and additional details for easier resolution
  3. Consider adding valuable information like screen recordings and detailed context in bug reports for the engineering team
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Edge 439: SSMs with Attention, Understanding Zamba

TheSequence • 112 implied HN points • 15 Oct 24
🕹 Technology Software Engineering
  1. Combining state space models (SSMs) with attention layers can create better hybrid architectures. This fusion allows for improved learning capabilities and efficiency.
  2. Zamba is an innovative model that enhances learning by using a mix of Mamba blocks and a shared attention layer. This approach helps it manage long-range dependencies more effectively.
  3. The new architecture reduces the computational load during training and inference compared to traditional transformers, making it more efficient for AI tasks.

Three traits of the software engineers that are promoted fastest[Storytime Saturdays]

Technology Made Simple • 59 implied HN points • 26 Mar 23
🕹 Technology Software Engineering
  1. Top engineers integrate feedback to grow faster by seeking and incorporating detailed feedback, and following up on the impact.
  2. Top engineers prioritize their time by focusing on high-return activities and ruthlessly assessing what is worth pursuing.
  3. Top engineers communicate effectively by articulating the 'why', avoiding jargon, tailoring messages to the audience, and sharing updates regularly.

Solving f'(x)= f^(-1)(x) [the inverse of f(x)] [Math Mondays]

Technology Made Simple • 79 implied HN points • 17 Jan 23
🚌 Education Software Engineering
  1. Solving f'(x)= f^(-1)(x) is a powerful technique in problem solving used in Math and Software.
  2. Math and coding share similar neural pathways, making a Math background beneficial for coding.
  3. When solving problems, start with a warm-up, rely on pattern matching, attack problems from multiple angles, and remember that complex solutions can have simple building blocks.

Let's get rid of security reviews

Frankly Speaking • 254 implied HN points • 16 Nov 23
🕹 Technology Software Engineering
  1. The current security review process is outdated and not aligned with modern development practices.
  2. Implementing efficient and effective security measures may involve integrating software engineers with security teams.
  3. Scaling security efforts requires a rethink of traditional security review processes towards more collaborative and contextual approaches.

Applying AI where it matters

Engineering Enablement • 7 implied HN points • 26 Nov 25
🕹 Technology Software Engineering
  1. Use a simple need-vs-use map to decide where to invest in AI, so you can spot high-need, low-use opportunities to build and high-need, high-use areas to harden.
  2. Developers welcome AI for repetitive operational work, use it cautiously for high-stakes technical tasks to reduce effort or check mistakes, and limit AI in mentoring or identity-defining work that requires human judgment.
  3. AI tools must be safe, reliable, private, transparent, and easy to control, with more experienced or AI-savvy developers especially valuing transparency and steerability.

Why you should analyze the distribution of your Data [Math Mondays]

Technology Made Simple • 59 implied HN points • 14 Mar 23
🕹 Technology Software Engineering
  1. Analyzing the distribution of your data is crucial for accurate analysis results, helps in choosing the right statistical tests, identifying outliers, and confirming data collection systems.
  2. Common techniques to analyze data distribution include histograms, boxplots, quantile-quantile plots, descriptive statistics, and statistical tests like Shapiro-Wilk or Kolmogorov-Smirnov.
  3. Common mistakes in analyzing data distribution include ignoring or dropping outliers, using the wrong statistical test, and not visualizing data to identify patterns and trends.

How do I get everyone to use AI?

The Engineering Manager • 5 implied HN points • 18 Dec 25
🕹 Technology Software Engineering
  1. AI adoption follows a J-curve: there’s early hype, a frustrating trough where things feel slower, and then real productivity gains once people and processes adapt.
  2. Forcing AI can work for a few big-brand companies, but heavy mandates usually breed resentment and risk losing good people, so coercion is risky for most orgs.
  3. Help adoption by investing in training, time to experiment, and the right tools, and make a clear business case for costs versus expected gains to get finance on board.

Exploring recent Python repositories

Mostly Python • 314 implied HN points • 22 Jun 23
🕹 Technology Software Engineering
  1. Use the GitHub API to explore popular new Python projects and find potential projects to contribute to.
  2. Consider filtering out AI-focused projects when exploring Python repositories to discover a variety of coding projects.
  3. Pruning repositories using specific terms can help identify non-AI Python projects to work on, providing valuable learning opportunities.

Introducing Orchestra: rapidly Build and Monitor Data and AI Products

The Orchestra Data Leadership Newsletter • 19 implied HN points • 07 Mar 24
🕹 Technology Software Engineering
  1. Launching a free tier for Orchestra, a tool to build and monitor data and AI products, offering a lightweight approach to improving business value and AI integration.
  2. Addressing the challenges faced by data teams in balancing business value and software engineering best practices through tools like Nessie, dbt, and emerging 'as-code' BI platforms.
  3. Providing an end-to-end platform with features like declarative pipelines, data quality monitoring, granular alert control, and asset-based data lineage to empower data teams in accelerating their initiatives.

Microsoft’s New Love

Sector 6 | The Newsletter of AIM • 39 implied HN points • 17 Nov 23
🕹 Technology Software Engineering
  1. Large language models (LLMs) like ChatGPT are powerful but costly to run and customize. They require a lot of resources and can be tricky to adapt for specific tasks.
  2. Small language models (SLMs) are emerging as a better option because they are cheaper to train and can give more accurate results. They also don't need heavy hardware to operate.
  3. Many companies are starting to focus on developing small language models due to their efficiency and effectiveness, marking a shift in the industry.

Breaking orthodoxies in venture capital

SarHaribhakti's Newsletter • 355 implied HN points • 25 Feb 23
💼 Business Software Engineering
  1. Root Ventures breaks traditional VC norms by focusing on hard tech, staying close to seed roots, and having all engineer partners.
  2. It's important for investors to avoid overfitting their models and to keep building new projects to stay relevant.
  3. Technical founders should focus on hiring employees who fit the startup environment and prioritize results over corporate measures.

Don't wait until it's not messy

Sunday Letters • 99 implied HN points • 21 Feb 23
🕹 Technology Software Engineering
  1. Don't wait for things to be perfect before starting something new. It's better to jump in while things are a bit messy.
  2. As an engineer or creator, focusing on solutions is key. Look for interesting problems to solve instead of getting stuck on why things are hard.
  3. If everyone only started when it was easy, no one would ever innovate. Embrace the challenges and start building!

Five Lessons for Building Robust AI Agents from Coding Agents

Tanay’s Newsletter • 56 implied HN points • 22 Jan 25
🕹 Technology Software Engineering
  1. Having clear rules and structured frameworks helps AI work better. By defining specific inputs and outputs, AI can understand what to do more easily.
  2. Using well-organized and detailed data helps AI learn faster. The more context and reasoning behind data points, the better AI can make decisions.
  3. Measuring how well AI performs with clear goals and regular tests is important. This allows AI to keep improving and adapting to different situations.

Welcome to Wisdom over Waves

Wisdom over Waves • 39 implied HN points • 31 Oct 23
🕹 Technology Software Engineering
  1. Technology trends may focus on the latest and greatest, but essential concepts are sometimes overlooked in the marketing hype.
  2. Years of experience can bring insight into the importance of foundational practices like writing test cases and implementing CI/CD.
  3. Wisdom in software engineering lasts longer than fleeting technology trends and can withstand ecosystem changes.

Interesting Data Gigs # 79: Want a job today as Sofware Engineer? Learn COBOL and Exilir ASAP

Interesting Data Gigs Weekly • 19 implied HN points • 10 Feb 24
🕹 Technology Software Engineering
  1. Rob Mee and his team at Mechanical Orchard are leveraging Generative AI to modernize critical, old code running on mainframes efficiently and properly.
  2. Legacy systems in the U.S. still heavily rely on languages like COBOL, offering job opportunities for those skilled in it.
  3. Mechanical Orchard's use of COBOL and Elixir highlights the demand for modernizing old systems and the potential for increased profits after such modernization.

How To Communicate With Software Engineers So That They Understand You

Money in Transit • 39 implied HN points • 09 Oct 23
🕹 Technology Software Engineering
  1. Software engineering is not inherently more difficult than other professions like medicine or law.
  2. Effective communication with software engineers can be facilitated by using frameworks like The Spreadsheet Analogy and the Given-When-Then method.
  3. Communication breakdowns between engineers and non-engineers can be bridged by understanding software engineering concepts and speaking a shared language.

"Technical Debt" is a bad metaphor

Cybersect • 39 implied HN points • 31 May 23
🕹 Technology Software Engineering
  1. Technical debt is misused and misunderstood in software engineering, often seen as a moral crusade against bad code.
  2. Refactoring is essential for addressing technical debt, focusing on making code more readable and maintainable.
  3. The concept of technical debt is not about avoiding problems but understanding the ongoing costs of decisions in software development.

Reinventing the Wheel of Data Activation

Sarah's Newsletter • 99 implied HN points • 26 Jul 22
🕹 Technology Software Engineering
  1. Data activation is not just a concern for the data team; it affects the entire data ecosystem and requires consideration of how data moves from one destination to another.
  2. Tools like Zapier and Make are essential for activating data, even bypassing warehouses, though maintaining software engineering principles like testing and version control is crucial for data teams.
  3. Integration bridges will always be necessary to connect applications that aren't warehouse-native, highlighting the importance of scalable systems and minimizing potential points of failure in data movement.

You Should Learn How to Code

Jake [Building in NYC] • 19 implied HN points • 01 Feb 24
🕹 Technology Software Engineering
  1. Learning to code is easier than ever with powerful tools and a supportive community. Many resources and frameworks are available to help beginners quickly set up projects.
  2. Becoming a product engineer lets you create and deploy software rapidly, using existing APIs and tools to add functionality. You can build applications that connect to various services without starting from scratch.
  3. Software engineering offers good salaries and a growing job market. There are many opportunities for those who are willing to work, both in traditional roles and through self-employment options.

Using AI to accelerate hiring and productivity at Zapier

Engineering Enablement • 4 implied HN points • 03 Dec 25
🕹 Technology Software Engineering
  1. Build lightweight AI agents to remove coordination and repetitive overhead so engineers can focus on the work only they can do.
  2. As AI cuts administrative work, each hire becomes more productive. That makes adding headcount more attractive than reducing it.
  3. Deploy agents iteratively: start with real bottlenecks like standups and onboarding, test in safe channels, and maintain observability and governance to measure and scale what actually improves outcomes.

Legacy Shmegacy

David Reis on Software • 59 implied HN points • 24 Nov 24
🕹 Technology Software Engineering
  1. Legacy code often gets that label just because newer programmers don’t understand it. The core issue is usually about people, not the actual code quality.
  2. To avoid creating legacy code, focus on writing clear and simple code that others can easily understand, and engage in practices like mentoring and pair programming.
  3. When dealing with legacy code, try to understand it fully before deciding to rewrite it. Often, working with what's there and improving it gradually is the better choice.

Unpacking METR’s findings: Does AI slow developers down?

Engineering Enablement • 15 implied HN points • 06 Aug 25
🕹 Technology Software Engineering
  1. A study found that using AI coding tools may actually slow developers down instead of speeding them up, which was surprising to many involved. Developers often focus on the fun of using AI rather than the time it takes to solve problems.
  2. It's important for developers to use AI for specific tasks where it excels, like documentation and unit tests, rather than for tasks it struggles with. Understanding which tasks suit AI can make a big difference in productivity.
  3. When working with AI, developers should be mindful of their time and set limits. If an AI tool isn't delivering results quickly, it might be better to switch to manual coding instead.

Find the Middle of a Singly LinkedList[Technique Tuesdays]

Technology Made Simple • 39 implied HN points • 08 Mar 23
🕹 Technology Software Engineering
  1. To find the middle of a singly linked list, use 2 pointers - one fast and one slow. This approach simplifies the process and is efficient.
  2. The reasoning behind finding the middle involves understanding the ordered structure of values in a linked list. It exploits this organized structure to bisect the list and locate the middle.
  3. Learning to think in abstract groups instead of specific data types can enhance problem-solving skills. This technique can be extended to more complex structures beyond linked lists.

The Leverage Points in Engineering Ecosystems

peoplefirstengineering • 50 implied HN points • 18 Dec 24
🕹 Technology Software Engineering
  1. Complex systems, like software teams, are made up of many parts that interact with each other and change over time. Understanding these interactions can help improve how we manage and work within these systems.
  2. Donella Meadows' framework shows that not all changes in a system will have the same impact. Some changes, like adjusting goals or encouraging new mindsets, can lead to much bigger improvements than simply tweaking numbers or rules.
  3. To create a successful and adaptable environment, it's important to give teams the freedom to self-organize, share information openly, and align their goals with the overall mission of the organization.

Weekly Top Picks #67

The Algorithmic Bridge • 116 implied HN points • 18 Mar 24
🕹 Technology Software Engineering
  1. The post discusses Nvidia GTC keynote, BaaS in science, Apple's potential collaboration with Google Gemini, and more key AI topics of the week.
  2. It features conversations between Sam Altman and Lex Friedman, touches on jobs in the AI era, and examines the response from NYT to OpenAI.
  3. There's a question about whether OpenAI's Sora model is trained using YouTube videos, among other intriguing topics.

AI and Knowledge Work

Tanay’s Newsletter • 119 implied HN points • 22 Feb 24
🕹 Technology Software Engineering
  1. AI is enhancing productivity and quality in knowledge work like software engineering and customer support.
  2. AI benefits are not uniform; it tends to help lower performers more, but can also assist top performers by reducing menial tasks.
  3. AI is not a cure-all; it has limitations and understanding when to use it is crucial for optimal results.

To hack or not to hack

Sunday Letters • 179 implied HN points • 24 Jan 22
🕹 Technology Software Engineering
  1. In software development, it's a challenge to choose between making a general solution or focusing on a specific problem. Both approaches have their pros and cons.
  2. If you hack your code without planning, it can become messy and hard to manage. But if you overthink it and try to make it too general too soon, you might waste time and effort.
  3. To find the right balance, ask how hard it is to change things later and how long the general solution will take to pay off. It's about making smart decisions based on the problem at hand.

How to Create Good Documentation in Software Engineering and Tech[Technique Tuesdays]

Technology Made Simple • 59 implied HN points • 19 Oct 22
🕹 Technology Software Engineering
  1. Good documentation in software engineering is crucial as it provides clarity to the team about goals and work done, enhancing productivity.
  2. Key pillars of good documentation include having a vision for the company and products, outlining resource/situational constraints, detailing data sources and processing, tracking projects in progress, sharing actual code, and establishing ownership.
  3. Benefits of good documentation in tech include aligning teams, clarifying vision and plans, reducing onboarding time, and promoting asynchronicity in an increasingly remote working environment.