The hottest Engineering Substack posts right now

And their main takeaways
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Announcing: Re-launching "Impact through Influence"

The Caring Techie Newsletter • 9 implied HN points • 29 Jan 25
🕹 Technology Engineering Leadership Influence Education Career growth
  1. The course 'Impact through Influence' focuses on helping tech professionals build their influence without needing formal authority. It's great for engineers who want to lead and motivate their teams.
  2. Participants will learn how to build their reputation, foster trust, and persuade others effectively. The course includes practical exercises to apply what you learn in real situations.
  3. This re-launch includes new features like hands-on exercises and cheat sheets for every module. It's designed to make the content more accessible and directly applicable to everyday challenges.

Weekly Dose of Optimism #117

Not Boring by Packy McCormick • 127 implied HN points • 25 Oct 24
🕹 Technology AI Engineering Innovation Environmental Healthcare
  1. TSMC is successfully producing chips in Arizona, even better than in Taiwan. This could help boost U.S. manufacturing and support the new CHIPS Act funding.
  2. Arkansas has a lot of lithium, estimated to be 5 to 19 million tons. This is great news for the EV industry and America's push for clean energy.
  3. Science has made a retinal implant that helps restore vision to some blind patients. This shows how technology can genuinely improve people's lives.

The loneliness of the long distance runbook

Wednesday Wisdom • 56 implied HN points • 11 Dec 24
🕹 Technology Software Engineering Documentation Management Processes
  1. Runbooks are often not followed closely because experienced engineers adapt them to their own knowledge and context. This can be good, but it also means runbooks might not be used as intended.
  2. When runbooks have errors or are not up to date, they can cause big problems. It's crucial to review and update runbooks regularly to keep them relevant and accurate.
  3. Don't expect runbooks to be perfect or solve all issues. They should be seen as guidelines rather than strict instructions, and everyone should have an understanding of the system behind them.

Code coverage doesn't matter much

Andrew's Substack • 83 implied HN points • 29 Nov 24
🕹 Technology Software Testing Development Engineering Programming
  1. Code coverage alone doesn't indicate whether tests are good or useful. It's more about the quality of the tests than the quantity.
  2. Not all tests are valuable; some can be complex and fail for reasons that don't matter, which can lead to false confidence in the code.
  3. The aim of testing should be to assure that your code works and to catch errors, instead of just trying to raise a coverage percentage.

Calif is hiring!

Thái | Hacker | Kỹ sư tin tặc • 738 implied HN points • 03 Nov 23
💼 Business Tech Recruitment AI Security Engineering
  1. Calif is a young firm on the verge of a big boom, working with top firms in AI, infrastructure, and products, and offering great work experiences.
  2. Calif is hiring excellent hackers to tackle important tech challenges and offers a unique opportunity to work in a company with a high standard reminiscent of Silicon Valley's early days.
  3. Calif has open positions for Offensive Security Engineer, Software Engineer, and Technical Project Manager, with a referral reward of USD 2,000 for successful hires.
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sqlmesh test

davidj.substack • 47 implied HN points • 12 Dec 24
🕹 Technology Software Data Engineering Testing Development
  1. Unit tests and data tests are different. Unit tests check if a function works right with set inputs, while data tests check if the data meets certain conditions.
  2. Running tests locally can save costs and speed things up. If you test your code on your own machine, you don’t have to pay for the cloud data warehouse until you’re ready.
  3. Creating external models in sqlmesh can be automated, making it easier to document source tables. You just run a command to generate the necessary files instead of doing it manually.

Breaking and Non-Breaking Changes

davidj.substack • 47 implied HN points • 11 Dec 24
🕹 Technology Software Development Data Engineering Analytics
  1. When making changes to data models, it's important to identify if they are breaking or non-breaking changes. Breaking changes affect downstream models, while non-breaking changes do not.
  2. SQLMesh automatically analyzes changes to understand their impact on other models. This helps developers avoid manual tracking and reduces the chances of errors.
  3. New features in SQLMesh will allow for more precise tracking of changes at the column level. This means less unnecessary work when something minor is modified.

The Reasoning Race: Can Small Models Reason?

TheSequence • 182 implied HN points • 05 Jan 25
🕹 Technology AI Models Research Engineering Philosophy
  1. The Sequence newsletter is evolving to offer more focused content, catering to both AI scientists and engineers. This means you'll get richer discussions on research and practical applications.
  2. There will be new editions each week that cover a variety of topics like education, engineering, interviews, and insights. This change aims to make the content shorter and easier to digest.
  3. The discussions around reasoning in AI are expanding to include smaller models, challenging the idea that only large models are capable of complex reasoning. It's an exciting area of exploration.

The misguided yearning for a better plan

Wednesday Wisdom • 104 implied HN points • 30 Oct 24
💼 Business Management Execution Education Engineering Incentives
  1. Having a better plan isn't the solution; it's all about how well you execute the plan you have. Good results come from good execution, not just a fancy plan.
  2. Many people look for secret techniques to improve, but the truth is that everyone knows what to do. The problem is usually that they just aren't doing it well.
  3. Instead of searching high and low for a better plan, focus on improving how you do what you're already doing. Making small changes in execution can lead to big improvements.

If I could travel back to 5 years ago, what would I talk to myself about Docker?

VuTrinh. • 299 implied HN points • 09 Mar 24
🕹 Technology Software Development Engineering Infrastructure Cloud
  1. Docker helps you package your applications and everything they need into containers. This makes it easier to deploy and run your apps anywhere.
  2. Containers are lighter than virtual machines because they share the host's operating system, saving resources and simplifying management.
  3. To get started with Docker, install it, then run a simple command to create your first container, like 'docker run hello-world' - it’s that straightforward!

Where Do Spacecraft Live: How to Choose the Right Satellite Orbit?

Space Ambition • 79 implied HN points • 28 Jun 24
🕹 Technology Space Exploration Engineering Satellite Technology Aerospace Industry
  1. Choosing the right satellite orbit is a key factor for the success of a space mission. It helps control costs and how well the satellite can perform its job.
  2. There are different types of orbits such as Low Earth Orbit (LEO), Medium Earth Orbit (MEO), and Geostationary Orbit (GEO), each serving different purposes and applications.
  3. As the number of satellites in space grows, effective disposal methods are crucial to avoid creating space debris, which could lead to future problems.

Thursday Links

Niko McCarty • 119 implied HN points • 30 May 24
🕹 Technology AI Biotechnology Engineering Research Innovation
  1. A company has set a new record by placing over 4,000 electrodes on a living human brain. This is a big step in brain-computer interface technology.
  2. There are some significant papers about CRISPR technology that are worth checking out. These studies could impact how we use gene editing in the future.
  3. A certain microbe can significantly reduce harmful gas emissions in soil. This is important because it's a natural solution that doesn't involve genetic engineering.

🌻 E46: Next-Gen Agent or a True Leap in AI Consciousness?

Musings on AI • 72 implied HN points • 11 Nov 24
🕹 Technology AI Research Innovation Development Engineering
  1. AI agents are still developing but show promise for the near future. They're getting better at aligning with human values and being more useful.
  2. Stanford's new method using Information-Directed Sampling helps AI learn more efficiently while keeping human preferences in mind. It can adapt well in changing environments.
  3. As AI becomes more common, we might see a mix of human-friendly websites and those that cater directly to AI agents. This means both types of users can interact effectively.

ChatGPT, North Koreans, and America's Infrastructure

Of All Trades • 8 implied HN points • 17 May 25
🕹 Technology Cybersecurity Remote work Engineering AI International relations
  1. North Korean remote IT workers are being used by the regime to earn foreign money, often through scams and cybercrime. They can make a lot of money for the government by working remotely.
  2. These workers are also stealing the identities of professional engineers to create fake design documents. This could lead to serious safety issues because the real engineers might be held responsible for bad work they didn't do.
  3. There's a concern that this situation could harm the future of remote design and national security. It's important to have strict systems to verify who is doing work and how to ensure public safety.

From J-10 to J-XD - History

TP’s Substack • 27 implied HN points • 26 Dec 24
🕹 Technology Aerospace Military Engineering Innovation History
  1. China's fighter jet development has evolved significantly from earlier models, with newer jets like the J-10 and J-20 showing vast improvements in technology and performance.
  2. The transition from 4th to 5th generation fighter jets has been important for the PLAAF, highlighting advancements in stealth, electronics, and weaponry.
  3. Looking ahead, the next generation of fighters, like the J-XD, will likely rely on AI and integrate with drones for enhanced combat capabilities.

What the world needs isn't "Artificial Intelligence" but Optimized Computational Methodologies

Top Carbon Chauvinist • 79 implied HN points • 21 Jun 24
🕹 Technology Artificial Intelligence Machine Learning Engineering Mathematics
  1. We should focus on making smarter tools instead of trying to make machines think like humans. Real progress comes from solving practical problems, not imitating nature.
  2. Copying how living things work is often a bad approach. Nature is full of flaws, and we don't need to mimic those to create better designs.
  3. It's important to clearly define the problems we want machines to solve. Without a clear goal, projects will struggle and waste resources on unnecessary tasks.

Can Machines Slip on Banana Peels?

Breaking Smart • 79 implied HN points • 30 Oct 24
🕹 Technology AI Robotics Design Engineering Systems
  1. It's funny when a self-important person slips on a banana peel because it shows their dignity being challenged. This humor comes from seeing someone with high self-esteem face an embarrassing moment.
  2. Machines can also have moments of failure, just like people. They slip up when their design looks seamless but actually has hidden flaws, similar to someone who overestimates their own abilities.
  3. Understanding the 'Contraption Factor' helps us analyze why machines fail. It shows a difference between how complex something is and how well it's designed, which can lead to unexpected problems.

I Wrote a Guest Post for Emerge Tools!

Jacob’s Tech Tavern • 656 implied HN points • 26 Feb 24
🕹 Technology Apps Tools iOS Engineering Startups
  1. The blog post compares the Twitter and X iOS app binaries, revealing insights like extra app icons and heavy use of dynamic libraries.
  2. Emerge Tools offers valuable solutions for mobile engineers to monitor their app's size and performance.
  3. The author recommends subscribing to Jacob's Tech Tavern for more insightful posts and to show support for the work.

Telescopes: Discoveries, Places to Visit, Key Facts

Space Ambition • 359 implied HN points • 19 Jan 24
🔬 Science Astronomy Astrophysics Technology Engineering Research
  1. Telescopes help us discover amazing things in space, like black holes and new planets. They've changed our understanding of the universe since Galileo's time.
  2. There are many types of telescopes, both in space and on Earth. Each one has its own strengths, like observing different wavelengths of light to see invisible objects.
  3. People are really getting into astronomy, and funding for telescopes is growing. It's easier than ever to rent telescopes or visit observatories to explore the night sky.

The Age of Feature Engineering is Here

From the New World • 37 implied HN points • 11 Dec 24
🕹 Technology AI Machine Learning Engineering Economics Innovation
  1. Specialization in technology makes things easier and more efficient. Just like we have different appliances for different tasks at home, specialized AI works better for specific jobs.
  2. Feature engineering is about creating AI that focuses on one thing really well, and it's actually really important for success in the tech world. It helps make machines smarter for real-life uses.
  3. The idea that one all-purpose AI model is best is a myth. In reality, there’s a growing trend toward making AI more specialized and tailored to different needs.

Year In Review - Illumina

ASeq Newsletter • 36 implied HN points • 17 Dec 24
🕹 Technology Biotech Innovation Market Trends Research Engineering
  1. Illumina remains a leader in the market, even with rising competition. They have strong inventions that could help them grow even more.
  2. The MiSeq i100 product has had mixed reviews, but it shows promise for improving clinical applications by integrating more processes.
  3. The author has published nearly 200 articles this year, and while they appreciate their subscribers, they still seek more financial support to continue their work.

Trapped Among the Root Causes

Atlas of Wonders and Monsters • 610 implied HN points • 07 Mar 24
🎭️ Culture Metaphor Engineering Problem Solving Environmental Issues
  1. Looking for root causes can be attractive, but sometimes it's better to focus on finding and implementing imperfect, temporary solutions instead of getting lost in the complexity of the 'true cause' of a problem.
  2. In complex systems like the environment or human societies, the idea of a single 'root cause' can be elusive, and efforts to dig deep might lead to unintended consequences due to interconnected issues.
  3. Patching things can be a practical approach, especially in evolving systems like nature and societies. Embracing the continuous cycle of problem-solving and expecting new challenges and solutions may be more sustainable than aiming for one perfect fix.

📝 Guest Post: How to Build the Right Team for Generative AI*

TheSequence • 994 implied HN points • 19 Jan 24
🕹 Technology AI Engineering Product Management Tooling
  1. You may not need ML engineers for Generative AI projects due to the availability of pre-trained models like GPT-4.
  2. Prompt engineering, the clear articulation of needs in natural language, is a crucial skill for AI application development.
  3. Product managers and domain experts play a significant role in shaping AI products through prompt engineering, reducing the need for technical experts.

Everything is (not) fine at Intel

Irrational Analysis • 159 implied HN points • 03 Apr 24
🕹 Technology Semiconductors Investment Analysis Engineering
  1. The Intel event highlighted concerning trends, particularly in product competitiveness and margins, with challenges in execution and manufacturing processes.
  2. Intel's strategic shift towards insourcing and reducing external foundry partnerships suggests significant changes in their manufacturing approach.
  3. Despite efforts to improve, Intel faces a tough road ahead with the need for advanced technology developments and a challenging competitive landscape.

Engineering Culture and Team Dynamics in a Challenging Climate

peoplefirstengineering • 12 implied HN points • 15 Jan 25
🕹 Technology Engineering Team Dynamics Culture Leadership Workplace
  1. Engineering culture is really important. It can help teams work better together and overcome tough times in the industry.
  2. Improving team dynamics and culture is hard work, but it pays off. When people feel motivated and safe, they can contribute more effectively.
  3. Since there's no one-size-fits-all approach, leaders need to pay attention to what works for their specific teams and focus on building supportive environments.

Building a technical career path at Spotify

It Depends / Nimble Autonomy • 19 implied HN points • 11 Aug 24
🕹 Technology Career development Engineering Company Culture Leadership
  1. Spotify emphasizes that career paths should fit the company's culture. Using a framework from another company often doesn't work well.
  2. Creating a career path framework should happen after seeing a real need for it, rather than forcing it too early in a company's growth.
  3. The Spotify model focuses on team success and personal growth, not just climbing a ladder. It encourages diverse development without penalizing role changes.

Season 4 Finale: A Fond Farewell, What’s Next, & Would You Rather?

Dev Interrupted • 23 implied HN points • 17 Dec 24
🎙 Podcasts Technology Engineering Leadership Software AI
  1. The show is ending its fourth season but is excited to change things up next year. They will introduce new ideas, formats, and even have live events.
  2. Programmers need focus time to be productive, and it's important to set aside non-negotiable blocks in the calendar to minimize distractions.
  3. In 2025, leaders want to see real results from AI investments instead of just hype. It's all about proving that AI can make a positive impact on their work.

Please take our programming assessment with an LLM

Creating Value from Nothing • 185 implied HN points • 05 Nov 24
🕹 Technology Software Engineering AI Product Remote work
  1. Clipboard Health is using real-case programming problems in their hiring process. This helps them see how candidates actually work and fit into their async work culture.
  2. They believe that using LLMs, like chatbots or AI tools, is okay during assessments. They see these tools as standard parts of a modern engineer's toolkit, not as cheats.
  3. By allowing LLM use, they hope to create better assessments that truly evaluate a candidate's skill, helping to find the best engineers for their team.

Harmony, melody, and coding with AI

Sunday Letters • 39 implied HN points • 07 Jul 24
🕹 Technology AI Programming Software Innovation Engineering
  1. We are experiencing a shift in programming that changes how we interact with code and AI. Just like moving from desktop to cloud, this new way will come with challenges and need new thinking.
  2. Combining traditional coding with AI models is important. It's like writing music where the code provides a solid structure, while AI adds creativity and flexibility.
  3. To succeed in this new environment, programmers should keep learning and adapting, using both past knowledge and new technologies carefully together.

Author's Introduction

Fields & Energy • 439 implied HN points • 30 Sep 23
🔬 Science Physics Engineering Education Technology History
  1. Physicists and engineers often focus on different aspects of understanding reality. Physicists typically ask 'why' things happen, while engineers ask 'how' to make things work.
  2. Electromagnetism is a key part of our everyday experience, but training in this field has become disconnected between physics theory and practical applications. There's a need for better communication and education between physicists and engineers.
  3. New ideas in science can often be met with skepticism or rejection. It's important to question established norms and be open to fresh perspectives, even if they challenge widely accepted beliefs.

AI, The Idiot Ant Queen

Desystemize • 1404 implied HN points • 07 Mar 23
🕹 Technology AI Ethics Science Engineering Data
  1. Artificial intelligence could lead to a loss of understanding and agency in decision-making
  2. AI ethics issues stem from existing power imbalances and biases, not just the capabilities of AI systems
  3. The real concern with AI is the potential control it may have over societal institutions, impacting human autonomy and decision-making

Good Luck/Bad Luck. Good Design/Bad Design

Sunday Letters • 99 implied HN points • 28 Apr 24
🕹 Technology Software Design Engineering User Experience Coding Practices Project management
  1. Software can be easy to create but hard to maintain. It's important for engineers to think about how their choices today will affect the future.
  2. Using simple designs and clear roles in a project can help avoid complicated problems later. Teams should focus on making changes quickly and smartly.
  3. Sometimes, the best solution is to remove unnecessary parts instead of adding more. If something isn't needed right now, it's better to not include it.

Developer Productivity Will Decline in 2025 | Predictions from LinearB’s Ori Keren

Dev Interrupted • 23 implied HN points • 10 Dec 24
🕹 Technology Software AI Productivity Cybersecurity Engineering
  1. Developer productivity may decrease in 2025 due to an influx of AI tools. Short-term challenges might arise before these tools bring long-term benefits.
  2. In 2025, engineering leaders need to embrace data-driven decision-making. It's important to measure performance to optimize team productivity effectively.
  3. Cybersecurity will be a big focus in 2025, with AI-driven threats and new vulnerabilities. Teams will need to improve their security measures and collaborate better to stay safe.

Finding the CAP theorem of agents

Sunday Letters • 59 implied HN points • 02 Jun 24
🕹 Technology Software AI Distributed Systems Engineering Programming
  1. The CAP theorem shows that in any distributed system, you can only achieve two out of three things: consistency, availability, or partition tolerance. This means when things go wrong, you have to choose which one you're willing to sacrifice.
  2. In AI programming, there's a similar tension between using complex AI models and the need for reliable, deterministic code. Balancing these two aspects is a challenge, much like the early challenges with web applications.
  3. As technology evolves, the understanding and frameworks around these issues may improve. Just like how programmers now design around the CAP theorem, we might see better solutions and choices for AI challenges in the future.

No sacred masterpieces

Basta’s Notes • 753 HN points • 15 Sep 23
🕹 Technology Software Development Data science Engineering Project management Web Development
  1. Sometimes, valuable projects end abruptly without much recognition or lasting impact.
  2. It's important to focus on creating business value with your work, rather than building impressive but ultimately unnecessary solutions.
  3. Every piece of code you write as an engineer is legacy and may not last forever, so focus on learning from each project's outcome.