The hottest Engineering Substack posts right now

And their main takeaways
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Top Business Topics

Industry Impact, Predictive Tech, and Financial Prospects of Solar Storms Forecasting

Space Ambition • 199 implied HN points • 10 Nov 23
🔬 Science Engineering
  1. Solar storms can disrupt important systems like GPS, communications, and power grids. Understanding these storms helps us protect our technology and infrastructure.
  2. Predictive technology now allows us to forecast solar storms 20 hours in advance. This gives us time to prepare and possibly avoid some of the negative impacts.
  3. As satellite technology grows, so does the risk from solar storms. We're learning to adjust satellite operations to minimize damage and keep them functioning better in space.

The Sequence Engineering #671: How Anthropic Built a Research Agent?

TheSequence • 140 implied HN points • 25 Jun 25
🕹 Technology Engineering
  1. The Research feature in Claude allows AI to handle complex research tasks better by using a multi-agent system. This means that different AI agents can work on separate parts of a question at the same time.
  2. A LeadResearcher controls the process by breaking down a user's question into a plan and assigning tasks to specialized Subagents. This helps the system gather more information efficiently.
  3. Each Subagent does its job—like searching online or analyzing data—and sends back its results to the LeadResearcher, who then puts everything together into one clear report.

CROSSPOST: LEIF WEATHERBY: Our Spreadsheet Overlords

Brad DeLong's Grasping Reality • 146 implied HN points • 09 Jun 25
🕹 Technology Engineering
  1. AI tools like ChatGPT are often seen as super smart, but they're really just advanced digital bureaucrats. They help manage data and tasks but can hide errors behind a layer of complexity.
  2. Relying too much on AI can lead us to overlook its limitations. It doesn't think like humans; it's more about processing and translating data rather than genuine understanding.
  3. There's a risk in using AI for important tasks without careful oversight. As it automates jobs and decision-making, we need to stay aware of the potential for misuse and the loss of human judgment.

A Primer on Data Architecture

Data Engineering Central • 117 implied HN points • 01 Feb 24
🕹 Technology Engineering
  1. Data architecture is an important topic for data engineers to understand.
  2. Choosing tools like Airflow, Snowflake, and Databricks is not the only approach to data architecture.
  3. Approaching data architecture without a strategic plan can lead to challenges within an organization or team.

Xenobots: Self-Replicating Biobots

Solve Cancer in 365 days • 2 HN points • 14 Sep 24
🔬 Science Engineering
  1. Xenobots are made from frog cells and can swim, heal, and move in groups. They are different from regular robots because they are living organisms created by scientists.
  2. Researchers design Xenobots by separating skin and heart cells and using computer algorithms to find the best ways to make them move. This combines biology with engineering.
  3. Xenobots can self-replicate by using loose stem cells to create new Xenobots. They could help with pollution cleanup and even serve purposes in medicine, like repairing organs.
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The Sequence Knowledge #670: Evaluating AI in Software Engineering Tasks

TheSequence • 133 implied HN points • 24 Jun 25
🕹 Technology Engineering
  1. Software engineering benchmarks are important to assess how well AI can help with coding. These tests look at more than just generating code; they check if AI can understand bigger projects and fix actual bugs.
  2. One standout benchmark is SWE-bench, which uses real GitHub issues and pull requests. It challenges AI models to solve bugs and pass tests like human engineers would.
  3. These benchmarks are designed to figure out if AI can work alongside engineers reliably, just like a helpful teammate.

Starting a business

Tribal Knowledge • 39 implied HN points • 23 May 24
💼 Business Engineering
  1. Consider the appeal of bootstrapped startups over venture-backed ones for lower risk and more flexibility
  2. Reflect on past business experiences to learn from shortcomings and apply lessons in future endeavors
  3. Explore alternative ways to grow skills and start a business, like content creation, to balance conflicting desires

The Sequence Engineering #681: Building Agents with Amazon Strands

TheSequence • 119 implied HN points • 09 Jul 25
🕹 Technology Engineering
  1. Amazon Strands is an open-source framework that lets AI models work independently to plan and complete tasks. This means developers don’t have to write specific instructions for every single action.
  2. The framework uses three key components: a model, tools, and prompts to build intelligent agents easily. This helps in creating smarter systems with less coding effort.
  3. The essay goes into detail about how Amazon Strands works, including its structure and how it can handle multiple agents, making it a powerful tool for developers.

O-Day - Explaining Frank Polifka's Windhexe

Remote View • 216 implied HN points • 30 Mar 23
🔬 Science Engineering
  1. A technology called Windhexe can turn various materials into powder, even turning gravel to dust and reducing waste into powder.
  2. The Windhexe device functions by creating a tornado-like vortex in a chamber, causing materials to be smashed and pulverized into tiny particles.
  3. Windhexe technology has been used by different companies for processing food wastes, manufacturing debris, and even for drying materials quickly.

Inventions I Like To See

David Friedman’s Substack • 125 implied HN points • 23 Jun 25
🕹 Technology Engineering
  1. Ziplock bags with built-in reseals help keep flatbreads fresh after opening. It's a smart design that solves a common problem.
  2. Shower designs that allow users to adjust water temperature safely make for a more comfortable experience. Simple solutions like combined tub and shower setups are very effective.
  3. New kitchen gadgets, like edgeless can openers and color-changing plastic eggs, show how inventiveness can improve everyday tasks. They add convenience and safety while cooking.

Destroying the World is a Difficult Problem

Maximum Effort, Minimum Reward • 255 implied HN points • 23 Jan 25
🕹 Technology Engineering
  1. There's a big difference between theorists and experimentalists in science. Theorists think a lot about ideas, while experimentalists deal with the real-world messiness of experiments.
  2. Many fears about AI being super dangerous come from theorists who underestimate the practical challenges. Even super smart AIs will face real-life problems that slow them down.
  3. Destroying the world is actually hard and takes time. Even if an AI is super intelligent, making big changes in reality is complicated and can't happen instantly.

AI, The Idiot Ant Queen

Desystemize • 1404 implied HN points • 07 Mar 23
🕹 Technology Engineering
  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

Jet Propulsion: Evolution of Technology & the Future of Interplanetary Travel. Part 1.

Space Ambition • 319 implied HN points • 14 Apr 23
🕹 Technology Engineering
  1. Jet propulsion is a key technology for space travel. It works by pushing gas out one way to move in the opposite direction, based on Newton's third law.
  2. There are two main types of engines: high-thrust engines for fast launches and low-thrust engines for long, efficient journeys in space. Each type has its own use depending on the mission.
  3. The market for propulsion systems is growing rapidly, with innovations like 3D printing helping to make production cheaper and more efficient. This growth is driven by increasing satellite launches and the need for better space technology.

The Sequence Opinion #758: From Language to Landscape: The Age of Spatially Intelligent AI

TheSequence • 28 implied HN points • 20 Nov 25
🕹 Technology Engineering
  1. AI is currently good at understanding language and images, but it struggles to understand the three-dimensional world. Researchers believe teaching AI spatial intelligence is the next big step.
  2. World models help AI imagine and interact with virtual environments. They can simulate how different actions change these spaces, making learning more interactive and realistic.
  3. There are exciting projects working on these technologies, like Marble and Genie. However, there are still challenges to overcome, like making sure these models work in real-life situations.

Data Science Weekly - Issue 494

Data Science Weekly Newsletter • 319 implied HN points • 12 May 23
🕹 Technology Engineering
  1. Open source AI is rapidly advancing, but may always lag behind the best quality models. It's great for innovation but has its limits.
  2. Many academic papers promise data sharing but often fail to deliver, which can hinder scientific research and verification.
  3. Understanding how to craft effective prompts is essential when using generative AI tools. This skill can greatly enhance the results you get from those tools.

The Illusory Learning Curve

Gordian Knot News • 241 implied HN points • 23 Jan 25
🕹 Technology Engineering
  1. There is not much of a learning curve when building ships or power plants. Each project is unique, so little efficiency is gained from past projects.
  2. Regulation plays a big role in increasing costs for nuclear power plants, making them expensive to build. Regulations can limit the benefits of any learning curve.
  3. Despite claims of future savings, history shows that costs for nuclear plants often do not decrease significantly with experience. The actual savings are minimal.

Data Science Weekly - Issue 493

Data Science Weekly Newsletter • 319 implied HN points • 05 May 23
🕹 Technology Engineering
  1. Data scientists often lack key skills needed for the job, which can be frustrating for those hiring. It's important for data scientists to continually improve their skills and adapt to job requirements.
  2. There's a significant increase in data downtime and resolution times, signaling that overall data quality management needs improvement. Companies should focus on better data practices to enhance their operations.
  3. New programming languages, like Mojo, are emerging that aim to simplify coding and enhance user experience. These advancements can make programming more accessible and enjoyable for everyone.

I Wrote a Guest Post for Emerge Tools!

Jacob’s Tech Tavern • 656 implied HN points • 26 Feb 24
🕹 Technology Engineering
  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.

The Four Anxieties of Engineering Leaders

Maestro's Musings • 140 implied HN points • 02 May 25
💼 Business Engineering
  1. Engineering leaders worry about losing top performers to burnout. These key team members are crucial, and their departure can hurt projects and team morale.
  2. There's a constant push and pull between achieving exceptional results and maintaining a healthy team culture. Leaders need to find a balance that works for everyone on the team.
  3. Most current metrics used to measure engineering success are flawed. They focus on activities rather than real impact, making it hard for leaders to see what's truly happening in their teams.

Five Lessons From Building AI Developer Tools

Kathy PM • 15 implied HN points • 22 Dec 25
🕹 Technology Engineering
  1. AI shifts complexity rather than removing it. The mess moves from configs and docs into prompts, retries, and opaque layers, so teams must decide where to contain it.
  2. Developers want AI that manages itself quietly in the background. They don’t want to babysit agents, re-run tasks, or constantly context-switch between new dashboards and chats.
  3. Trust and integration matter more than flashy features. Predictability, consistency, and small reliable automations inside editors and pipelines make work lighter and let developers feel in control.

How to avoid the Migration Trap | Bruce Wang - Director of Engineering at Netflix

platocommunity • 98 implied HN points • 18 Jan 24
🕹 Technology Engineering
  1. Successful technology migrations require thorough planning, dedicated resources, and strategic funding to avoid falling into the "Migration Trap."
  2. Proving significant value in a migration is essential - the new system must offer transformative benefits that the old system couldn't achieve to justify the effort and resources required for the migration.
  3. Maintaining a learning mindset throughout the migration process is crucial; being open to challenges, re-evaluating assumptions, and being willing to abandon the migration if it doesn't serve its intended purpose can lead to better outcomes.

Quick Survey on RISC-V Development

Fprox’s Substack • 83 implied HN points • 19 Jul 25
🕹 Technology Engineering
  1. The author is curious about how people develop using RISC-V tools and hardware. They want to see what tools are commonly used.
  2. The author shares their experience using specific tools like clang and GCC for RISC-V development. They find both useful for different tasks.
  3. A survey is included for readers to share their own RISC-V development tools and experiences. The author encourages sharing the survey with others.

The Sequence AI of the WeeK #690: Team Memories & Multi‑Agent Minds: Inside Reflection AI’s Asymov

TheSequence • 84 implied HN points • 23 Jul 25
🕹 Technology Engineering
  1. Reflection AI is a new lab in AI that focuses on making software engineering smarter and more efficient. Their goal is to connect how humans understand language with how computers understand code.
  2. Their first model, Asymov, represents a change from traditional single-function models to a system that uses multiple agents. This setup helps it understand tasks better and do them more accurately.
  3. The post goes deep into how Reflection AI has evolved and what makes Asymov special. It shares detailed insights for those who want to learn more about this advanced technology.

When a PM takes over engineering

Leading Developers • 92 implied HN points • 01 Jul 25
🕹 Technology Engineering
  1. It's important for engineers to think like product people. They should understand the problem they are solving and not just build what’s written down.
  2. Good engineering managers help their teams understand the value behind technical projects, making clear connections to business goals. This helps everyone stay focused and aligned.
  3. After launching a product, teams should keep engaging with the data and user feedback to continually improve. This mindset helps engineers take ownership and see the bigger picture.

What makes a security product "good"?

Frankly Speaking • 305 implied HN points • 23 Oct 24
🕹 Technology Engineering
  1. A good security product isn't about having a lot of features. It's more important that it provides real value and helps people work efficiently.
  2. Security tools should help fill gaps in a team's capabilities rather than just adding more complexity. Sometimes a 'good enough' solution is better than a perfect one.
  3. The focus should shift from just ranking products to understanding what really helps customers. A good product makes life easier and solves the right problems.

Trapped Among the Root Causes

Atlas of Wonders and Monsters • 610 implied HN points • 07 Mar 24
🎭️ Culture Engineering
  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.

Understanding Software Idempotency [Math Mondays]

Technology Made Simple • 119 implied HN points • 11 Dec 23
🕹 Technology Engineering
  1. Idempotency ensures the same output regardless of how many times an operation is executed, providing data consistency and preventing duplicate operations.
  2. Idempotency is crucial for resilience, scalability, performance, simplicity, and provability in software systems.
  3. Implementing idempotency involves using unique identifiers, versioning, transaction management, and leveraging HTTP methods, offering benefits like better error handling and faster response times.

Spotlight: Adrien Michaud – Rocket Lab Space Ambassador

Space Ambition • 319 implied HN points • 03 Mar 23
🕹 Technology Engineering
  1. Space tech isn't just for engineers; there are many paths into the industry. You can find roles in areas like HR or business development even if you don’t have a traditional aerospace background.
  2. The future of space tech may resemble civil aviation or the car industry, with either a few big players or many smaller companies. This means a lot of new ideas and technologies may emerge, but they also need solid ways to make money.
  3. Watching inspiring films like Apollo 13 can ignite passion for space and problem-solving. Many people find their calling early and choose careers that let them work on real-world challenges in space tech.

Chapter Bundles of Options

Software Design: Tidy First? • 198 implied HN points • 06 Feb 25
🕹 Technology Engineering
  1. Creating options in software development is essential, especially when there's uncertainty. Keeping options open increases the value of the project.
  2. Investing time in software design is important for better cohesion and less coupling. This helps the system work more efficiently together.
  3. The more you avoid tight connections between parts of the software, the more flexibility you will have. This flexibility is crucial for future changes or improvements.

Of Hurricanes and Heroes

Litverse • 139 implied HN points • 11 Nov 23
💾 History Engineering
  1. Henry Flagler's influence on the development of modern Florida was significant, as seen through his investments in hotels, railroads, and the Overseas Railroad.
  2. Flagler's ambitious vision to connect New York City to Key West with the Overseas Railroad faced challenges like hurricanes, but his determination to overcome these obstacles was unwavering.
  3. The tragic events surrounding the Overseas Railroad, including the impact of the 1935 Labor Day Hurricane, highlight the complex legacy of Flagler's monumental engineering feat.