No summary available.

Summary of Estimating Work as a Staff Software Engineer

Estimating the time for software projects is notoriously difficult, and many software engineers believe it is impossible to provide accurate estimates. While some small, well-defined tasks can be estimated accurately, most software work involves unknown factors that complicate predictions.

Many engineering teams use informal methods, like t-shirt sizes for estimates, which are later converted into time by management. This is often due to pressure from higher-ups who rely on estimates to make funding and planning decisions.

Estimates often dictate the nature of the work rather than the other way around. For example, if a project has a tight deadline, engineers may simplify their approach to meet that timeline. When estimating, the focus should be on understanding the political context and the risks involved, rather than producing a specific time frame.

When presenting estimates, it’s more effective to offer a range of possible outcomes and highlight the unknowns and risks associated with each approach. This allows managers to make informed decisions about priorities and trade-offs.

Overall, effective estimation in software engineering involves recognizing the limitations of known work and focusing on the uncertainties that dominate most projects.

No summary available.

The Polyhedral Structures Laboratory at the Pennovation Center combines designers, engineers, and computer scientists to innovate in construction. They use graphic statics to create structures that balance forces, resulting in strong and efficient designs that require less material.

The "20 breakthroughs of 2025" report highlights various research advancements at Penn, ranging from ancient tombs to tiny robots, personalized gene editing, and AI weather models. It emphasizes how curiosity and collaboration lead to impactful knowledge across different fields and around the world.

The author has been using GitLab for personal projects for years, initially choosing it because it offered free private repositories, unlike GitHub at the time. Even after GitHub made private repositories free, the author continued using GitLab due to their established workflow, which includes CI pipelines and deployment scripts.

A key feature for the author is GitLab's Container Registry, which allows them to build and store Docker images without needing a separate Docker Hub account. The 10GB project limit is not an issue for them as they manage their image sizes well.

GitLab CI/CD is user-friendly, allowing for easy versioning of configuration files. The author appreciates the shared runners provided by GitLab, although they sometimes use their own for specific needs. While the documentation is thorough, it can be overwhelming.

However, the author notes some downsides, such as a sluggish web interface and an overload of features that they don't fully utilize. Despite this, the author finds great value in GitLab, as all their private projects are hosted for free, making it an ideal space for their unpolished ideas.

In contrast, they use GitHub for public projects, allowing them to benefit from collaboration and visibility while keeping their private work organized in GitLab. This dual approach suits their workflow well.

Summary of DSHR's Blog on Internet Archive's Storage

David Rosenthal discusses the Internet Archive's storage systems in his blog. Bruce Li's report, "The Long Now of the Web," explores how the Archive preserves internet content and its innovative storage solutions.

Key points include:

1. PetaBox Development: The Internet Archive has developed several generations of PetaBox storage systems since 2004, significantly increasing their data capacity. The latest versions can hold 1.4 petabytes per rack by using larger hard drives.

2. Cooling Efficiency: Instead of traditional air conditioning, the Archive uses San Francisco's cool climate to cool its servers, converting excess heat into warmth for the building during winter. This reduces energy costs significantly.

3. Data Redundancy: With over 28,000 hard drives, some drive failures are expected. The Archive’s system mirrors data across multiple locations to prevent data loss, making it less critical to replace every failed drive immediately.

4. Economic Challenge: Rosenthal emphasizes that long-term data preservation is more about budget constraints than technical challenges. The Archive operates on a budget of $25-30 million annually, which is much lower than typical commercial cloud services.

5. Data Accessibility: The Archive's storage strategy involves tiering data, moving less frequently accessed data to cheaper storage options, which helps manage costs effectively.

Overall, the Internet Archive's approach combines innovative technology with practical budgeting to tackle the challenges of digital preservation.

No summary available.

No summary available.

The article discusses the development and functioning of the Codex CLI, a software agent created by OpenAI for producing reliable software changes. It introduces the concept of the "agent loop," which is the core logic that enables interaction between the user, the Codex model, and the tools the model uses to perform tasks.

Key points include:

1. Agent Loop Process: The agent takes user input and creates a prompt for the model. It queries the model, which generates a response or requests a tool call. This process repeats until the model provides a final response or an assistant message indicating completion.

2. Model Inference: The Codex CLI uses an API to send requests to the model for generating responses, which involves transforming user input into tokens and then back into text.

3. Prompt Structure: When querying the model, the prompt is built from various inputs, including system instructions, tools the model can use, and user instructions. The order and structure of these inputs are crucial for the model's understanding.

4. Context Management: As conversations grow, the length of the prompts increases, which can exhaust the model's context window (the maximum input it can handle). The agent manages this by compacting conversations and ensuring that important information is retained.

5. Performance Considerations: The article highlights the importance of efficient prompt management to avoid excessive data traffic and improve performance. Techniques like prompt caching and conversation compaction are used to enhance efficiency.

Overall, this post serves as an introduction to the Codex agent loop, setting the stage for future discussions on its architecture and functionalities.

Summary: Can AI Grow Corn?

In January 2026, a discussion arose about whether AI can impact agriculture. The response is that AI, represented by Claude Code, can manage corn farming from planting to harvest by making decisions based on data rather than directly operating machinery.

Key Points:

• AI's Role: Claude Code acts like a farm manager, using data to make decisions about planting, irrigation, and harvesting while coordinating human workers.
• System Architecture:
  • Data Inputs: Uses IoT sensors, weather forecasts, and satellite data.
  • Orchestration: Manages farmers, suppliers, and equipment.
  • Outputs: Generates decision logs, commands, and ultimately, corn.

Current Status:

• Farmer Fred is operational in Texas and planning in Iowa and Argentina.
• Budget: $12.99 spent so far.
• Timeline: The project involves setup and growing seasons from January to October 2026.

Engagement: Interested parties can contact Farmer Fred for inquiries, and all project details are available on a GitHub repository.

Summary of 80386 Multiplication and Division

The Intel 80386, released in October 1985, was a groundbreaking 32-bit x86 processor that significantly enhanced personal computing. It expanded the register size from 16 to 32 bits, allowing for a much larger address space and better performance compared to earlier models. This made it capable of running modern operating systems and maintaining compatibility with older DOS software.

Key Features:

• 32-bit Architecture: Introduced a flat 4GB address space and effective virtual memory.
• Improved Arithmetic Performance: Multiplication and division became significantly faster with the 386. For example, 32-bit multiplication took only 9-38 cycles, compared to over 120 cycles on the 8086.

Multiplication Method:

• The 386 uses an "add-and-shift" multiplication algorithm, which is efficient and allows flexibility for different operand sizes (8, 16, and 32 bits).
• The algorithm involves shifting and adding based on the bits of the multiplier, with optimizations to exit early if possible.

Division Method:

• The 80386 employs a non-restoring division algorithm, which shifts the dividend and adjusts based on the divisor to build the quotient.
• Signed division (IDIV) is more complex, requiring sign adjustments after performing unsigned division.

Comparison to Modern CPUs:

• While the 80386 was advanced for its time, modern processors have vastly improved multiplication and division speeds, using dedicated hardware for faster calculations.

The 80386 laid the groundwork for future advancements in computing, balancing performance with compatibility and efficiency.

No summary available.

Summary of Crane Resources

• Getting Started: Learn how to install Crane, set up Rocq, and perform your first data extraction.

• Design Principles: Understand the goals and considerations behind Crane's C++ extraction method.

• Examples: Check out sample Rocq projects and the C++ code that they generate.

• Reference Manual: Find detailed information on Crane's options, extraction rules, and settings.

• Crane Base Library: Access the Rocq library that includes types, monads, and other tools used in the extracted code.

• Roadmap: Review planned features and future updates for Crane.

• Papers: Read the research paper titled "Crane Lowers Rocq Safely into C++" by Matthew Z. Weaver and Joomy Korkut, presented at RocqPL 2026.

In 2020, Connie Sherburne lost her husband, Peter, in a plane crash after 31 years of marriage. Immediately, she focused on practical tasks, like transferring insurance. During this process, a woman at the insurance office offered her a simple yet powerful piece of advice: "Let them," referring to accepting help from others.

Initially hesitant to seek support, Sherburne realized she needed assistance, especially with tasks like chopping firewood, which her husband used to handle. Following the advice, she accepted help from friends and neighbors, who supported her in various ways, including cooking meals for years.

Sherburne later returned to the insurance office to thank the woman for her impactful words, though she discovered that the woman no longer worked there. The advice had a significant effect on her ability to cope with her grief, showing how small gestures can make a big difference.

Summary of "Management Time: Who’s Got the Monkey?"

In this article, William Oncken, Jr. and Donald L. Wass explore why managers often feel overwhelmed with tasks while their subordinates seem to have less to do. They categorize management time into three types:

1. Boss-imposed time: Tasks required by a manager's boss.
2. System-imposed time: Activities needed to support peers.
3. Self-imposed time: Tasks that a manager chooses to take on themselves, which can be further divided into subordinate-imposed time and discretionary time.

The authors use the metaphor of a "monkey" to illustrate how subordinates' problems can shift from their shoulders to the manager's. When a subordinate brings a problem to a manager, they often unintentionally transfer the responsibility (the monkey) to the manager, who then feels obligated to resolve it. This leads to managers being bogged down with others' issues instead of focusing on their own responsibilities.

To reclaim their time, managers need to set boundaries and ensure that subordinates retain responsibility for their own tasks. This involves having clear conversations about who is responsible for what and establishing a system where subordinates must take the initiative. The article emphasizes the importance of empowering subordinates to make decisions and solve their problems, which ultimately frees up the manager's time for more strategic tasks.

The commentary by Stephen R. Covey reflects on the evolution of management practices since the article was first published, noting that while empowerment is now a key focus, it still requires effort and a trusting relationship between managers and their teams. Covey emphasizes that empowering others leads to better organizational outcomes, and that managers must learn to let go of control to foster growth in their subordinates.

In conclusion, the piece advocates for a shift in managerial mindset, encouraging leaders to delegate effectively and manage their time by focusing on developing their team's capabilities.

Summary of Vidstack's Journey and Video.js v10 Development

Vidstack's development journey is shaping Video.js v10, following significant milestones like 9 billion CDN requests and 7 million NPM downloads. The journey began in 2020 with the creation of Vime, a video player library that aimed to overcome the limitations of existing players like Video.js and Plyr. Initially, Vime offered a complicated plugin system that didn’t fully solve the challenges of video playback.

In 2021, a collaboration with Dave Furfero from Reddit led to the birth of Vidstack, which focused on building a more flexible web component library. This library aimed to provide developers with composable video player components rather than rigid widgets. Despite some successes, Vidstack faced challenges with its architecture, leading to a bloated design and difficulties in customization.

By early 2025, the limitations of the existing architecture became clear, prompting the decision to join Mux for a more sustainable approach. The upcoming Video.js v10 will integrate the best aspects of Vidstack while addressing previous issues. It will feature improved APIs, true modularity, and customizable skins, allowing developers greater control and flexibility.

The transition to Video.js v10 is not an abandonment of Vidstack but rather an evolution, incorporating lessons learned to create a more effective video player solution. The alpha version is expected to launch in early February, promising a composable and extensible player built from the ground up.

The author shares their personal habits and practices when writing C, having learned it as their first programming language but primarily using C# for gaming modding and Python for automation. They appreciate C for prototyping but note its lack of standard style guidelines, which can lead to inconsistencies.

Key points include:

1. C23 Usage: They prefer using C23 for new projects, ensuring CHAR_BIT is 8 for compatibility.
2. Type Definitions: They create custom typedefs for fixed-length types to simplify code.
3. String Handling: They utilize a length+data structure for strings instead of null-terminated strings, which they find problematic.
4. Parsing Philosophy: They advocate for "parsing, not validating," focusing on strict type systems to improve API robustness.
5. Tuples and Sum Types: They use tuples to return multiple values and create sum types with structs to handle different outcomes in a type-safe way.
6. Dynamic Memory: They don't often use dynamic memory in C and prefer using other languages for projects requiring it.
7. Standard Library: They mostly avoid standard library functions unless necessary, preferring to implement their own.

Overall, the author encourages others to think about their own C coding styles, appreciating the language despite its challenges.

No summary available.

Summary:

The text discusses Steve Yegge's project, "Gas Town," an agent orchestrator designed to manage multiple coding agents. It emphasizes the chaotic and inefficient nature of Gas Town, which, despite its flaws, sparks important conversations in the software engineering community about the future of coding and agent orchestration.

Key points include:

1. Design Bottleneck: As agents automate coding, the biggest challenge shifts from coding speed to design and planning. Effective design is crucial to guide the agents and ensure they produce useful outputs.

2. Agent Roles: Gas Town features agents with specific roles (e.g., Mayor, Polecats) that allow for more organized task management. Each agent has a clear job, reducing conflicts and making it easier to assign tasks.

3. High Costs vs. Value: Operating Gas Town is expensive, but it may offer significant value by speeding up development processes. The potential cost savings compared to hiring a developer could make it appealing for companies.

4. Code Oversight Debate: Yegge argues for a hands-off approach, suggesting that developers might not need to look at code at all. This raises questions about accountability and the level of oversight necessary as coding becomes more automated.

The text concludes that while Gas Town itself may not be a practical tool, it raises essential questions and patterns for future development tools. As automation increases, the need for thoughtful design, planning, and quality control will become more crucial.

Crafted with Love Summary

Designed by a dedicated team in Somerville, USA, and London, UK, this project focuses on creating clear visual representations of data. The team is seeking input on which transit network to develop next.

No summary available.

The author usually creates web games in C++ but found using Emscripten too complex for their needs. They wanted to improve the interaction between JavaScript and WebAssembly (WASM), so they developed a system using Shared Memory with Command and Event buffers. This approach significantly increased performance, achieving 100 FPS compared to Emscripten's 40 FPS in tests.

To make writing DOM logic easier, the author created a new language called Coi, which analyzes changes at compile-time for efficient updates without the usual Virtual DOM overhead. In benchmarks against React and Vue, Coi outperformed them in various tasks and had the smallest bundle size.

Coi allows easy integration of new browser APIs by simply updating a schema file, which automatically adds new functions during compilation. The author is proud of the progress and is considering extending Coi for server-side use, enabling component sharing across the stack.

The text includes example Coi code for a simple counter component and an application that displays a score. The author invites feedback and shares links to a live demo and the project's GitHub repository.

No summary available.

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The author is trying to create a local voice assistant that processes audio with low latency, allowing for real-time interaction. They believe the Qwen3 Omni model is a promising option, but they can't find clear instructions on how to use it for real-time speech-to-speech processing. Most available resources focus on converting speech to text or audio output only after processing, rather than providing a continuous voice interaction.

They are seeking information about what tools and setups people are using in 2026 for local and open voice processing. They want to know if anyone is successfully using end-to-end speech models locally or if the best approach is still combining different systems for automatic speech recognition (ASR), language models (LLM), and text-to-speech (TTS).

The author is looking for recommendations on hardware and software configurations that work well with a single GPU, as well as any personal experiences or tips from others who have successfully implemented this technology. They are particularly interested in the performance metrics, such as the time it takes for the system to respond after receiving input from a microphone.

No summary available.

The text discusses how Android builds often use the command sdkmanager --licenses to automatically download and accept licenses needed for development. When using a preconfigured VPS with Claude Code to create an Android app, it typically accepts the necessary licenses without user intervention. The author expresses surprise at this behavior and raises a question about the legal validity of agreements accepted in this way, especially considering that some people might misuse this system.

The text discusses a unique experiment where a PC, specifically an IBM PC, is booted using a vinyl record instead of traditional storage methods like hard drives or USB sticks. The setup involves connecting the PC to a record player through an amplifier. A custom bootloader is created to work with the PC's rarely used "cassette interface," which is triggered when other boot options fail.

The vinyl record contains a bootable RAM drive with a modified FreeDOS kernel. The process includes converting a boot image into an audio signal that can be recorded on vinyl and requires specific audio adjustments to ensure proper playback. The bootloader reads the data from the record and loads it into memory to start the system.

Overall, this experiment showcases a creative way to boot a computer using a vinyl record, combining old technology with innovative methods.

No summary available.

The text discusses the release of openpilot version 0.10.3 on December 21, 2025. It likely includes updates, features, and improvements made in this version. The summary does not provide specific details about these changes, but it highlights the release date and version number.

Summary of Mental Models: The Best Way to Make Intelligent Decisions

What Are Mental Models? Mental models are simplified representations of how things work, helping us understand complex ideas by focusing on key information. They serve as tools to navigate the world better by compressing complexity into manageable concepts.

Key Concepts:

1. General Thinking Tools: These include important ideas from various disciplines that enhance decision-making, problem-solving, and opportunity recognition.

2. The Map is Not the Territory: Our mental models are not the same as reality. It's essential to recognize that our understanding can be flawed and to seek accurate information.

3. Circle of Competence: Know your strengths and weaknesses. Focus on areas where you have expertise to make better decisions.

4. First Principles Thinking: Break down complex problems into fundamental truths to find effective solutions instead of following conventional wisdom.

5. Thought Experiments: Use hypothetical scenarios to test ideas and clarify thinking without real-world constraints.

6. Second-Order Thinking: Consider the long-term consequences of your decisions instead of just immediate outcomes.

7. Probabilistic Thinking: Embrace uncertainty by assessing risks and updating beliefs as new information becomes available.

8. Inversion: Instead of focusing only on how to succeed, consider what would lead to failure to uncover better solutions.

9. Occam’s Razor: Prefer the simplest explanation that makes the fewest assumptions when faced with multiple solutions.

10. Hanlon’s Razor: Assume that mistakes are often due to incompetence rather than malice to foster empathy and reduce conflicts.

Applications of Mental Models:

• Relativity: Recognize that perceptions vary based on individual experiences and contexts, promoting empathy.
• Reciprocity: Treat others well to receive kindness in return; your actions shape social interactions.
• Thermodynamics: Understand energy and disorder in life; maintaining order requires effort against the natural tendency towards chaos.
• Inertia: Change is hard, but starting with small steps can help overcome resistance to change.

These mental models can improve critical thinking and decision-making by providing valuable frameworks for understanding complex situations and human behavior.

David Bushell is a web designer and developer based in the UK. He offers services in web design, building, and consulting. He is available for hire and works on projects globally.

Summary of phase8 Acoustic Synthesizer

The phase8 is an innovative eight-voice acoustic synthesizer that combines the natural qualities of sound with electronic control. It uses KORG's advanced Acoustic Synthesis technology, allowing for a rich, responsive musical experience.

Key Features:

1. Sound Generation: Utilizes vibrating steel resonators to create sound, enhanced by electronic controls for a lively, interactive experience.

2. Customizable Resonators: Comes with 13 tunable resonators, allowing users to install 8 at a time and customize sounds from percussive to sustained notes.

3. Sequencer: Features an intuitive sequencer for step programming and live recording, with the ability to save and recall sequences across 8 slots.

4. Modulation Options: Offers three types of amplitude modulation effects, including tremolo and pitch-dependent variations.

5. Real-time Interaction: Users can physically interact with the instrument by touching or strumming the resonators, creating unique sound textures.

6. Connectivity: Supports MIDI, USB-MIDI, and CV for external control and synchronization with other devices.

7. Exclusive Presale Package: Includes limited-edition percussive resonators designed for unique sound exploration, available only through the presale.

Overall, the phase8 is designed for creative musicians looking to explore new sonic possibilities through a blend of acoustic and electronic music techniques.

The article discusses a shift in the tech landscape, highlighting how technology is becoming more diverse and personalized again after years of consolidation.

Key points include:

1. Tech Evolution: The author reflects on growing up with technology in the 90s and early 2000s, where devices were unique and specialized, unlike today's multifunctional gadgets.

2. Consolidation Issues: Over time, many tech products merged into singular devices (like smartphones), which led to a loss of individuality and creativity in tech.

3. Emerging Alternatives: Recently, new technologies like VR and AR are gaining traction, and there's a growing nostalgia for older tech, with consumers showing interest in single-purpose devices and retro products.

4. Design and Personalization: There is a revived emphasis on design and personal expression in tech, with products that feel unique and tailored to individual preferences.

5. Market Dynamics: Antitrust actions and consumer dissatisfaction with large tech platforms are fostering a healthier, more varied market with more choices for users.

6. Consumer Behavior: People are increasingly seeking products that allow for a focused and disengaged experience, moving away from algorithm-driven recommendations.

7. Future Outlook: The author believes we are entering a new golden era of technology characterized by diversity, personality, and choice, rather than dominance by a few big companies.

Overall, the text emphasizes a positive trend towards a more eclectic and personal tech environment.

No summary available.

On January 22, 2026, Cloudflare experienced a route leak due to an error in their automated routing policy. This mistake led to unintended advertising of some Internet traffic from a Miami data center, affecting not only Cloudflare customers but also other external networks.

Key points of the incident include:

• Duration and Impact: The route leak lasted for 25 minutes, causing network congestion, increased latency for users, and some discarded traffic.
• Cause: The issue stemmed from a misconfiguration that allowed internal traffic to be advertised externally. Specifically, a change meant to stop forwarding traffic to a data center in Bogotá accidentally made the policy too permissive, allowing all internal IPv6 traffic to be sent out improperly.
• Response: Cloudflare's network team quickly identified and addressed the problem, reverting the faulty configuration within 25 minutes of its occurrence.
• Prevention Measures: Cloudflare is taking steps to prevent future route leaks, including improving their routing policies, implementing safeguards, and validating routing equipment to ensure compliance with best practices.

Cloudflare apologized for the disruption caused by this incident and is committed to enhancing their routing security to avoid similar issues in the future.

Whosthere Summary

Whosthere is a tool for discovering devices on your Local Area Network (LAN) with a user-friendly Terminal User Interface (TUI), built using Go. It allows you to easily explore your network and identify devices without needing special permissions.

Key Features:

• Modern Interface: Navigate discovered devices easily.
• Fast Scans: Uses multiple scanning methods at the same time.
• No Special Permissions Needed: Operates in user-space.
• Device Information: Shows device manufacturers using OUI lookups.
• Port Scanning: Optionally scan found devices (get permission first!).
• Daemon Mode: Can run in the background with an HTTP API for integration.

Installation Options:

• Install via Homebrew: brew tap ramonvermeulen/whosthere and brew install whosthere
• Install with Go: go install github.com/ramonvermeulen/whosthere@latest
• Build from source: Clone the repository and use make build.

Usage:

• Start the interactive TUI: whosthere
• Run in daemon mode: whosthere daemon --port 8080
• Access help with: whosthere --help

Supported Platforms:

• Linux, macOS, and Windows.

Configuration: Whosthere can be customized using a YAML file for settings like scan intervals, themes, and scanners. Logs are stored in specific directories based on your operating system.

Important Notes:

• Whosthere should only be used on networks where you have permission to perform scans.
• Contributions and suggestions for improvement are welcome on GitHub.

For more details, check the documentation or run the application to explore its features.

Summary of Air Traffic Control: The IBM 9020

The IBM 9020 was a significant development in air traffic control (ATC) technology in the United States, emerging from earlier air defense systems like SAGE. While SAGE was designed for military air defense, it lacked many safety features necessary for civilian ATC. In the late 1950s, the FAA, in collaboration with the Air Force, initiated projects like SATIN to adapt SAGE technology for civilian use.

By the 1960s, the FAA faced growing mid-air collision issues and recognized the need for a centralized and automated ATC system. This led to the NAS Enroute Stage A project, aimed at creating a reliable and efficient air traffic control system using IBM's advanced computer technology.

The IBM 9020 was developed as a real-time, fault-tolerant system designed to manage air traffic data. It consisted of multiple interconnected S/360 computers, allowing for high performance and redundancy. This architecture enabled the system to handle numerous input sources, including radar and flight plans, and to manage tasks effectively with a unique control program and error analysis program.

The 9020 system included sophisticated controller consoles with radar displays, flight data entry devices, and communication tools, allowing air traffic controllers to manage flights safely and efficiently. As air traffic increased, the 9020 adapted to incorporate more advanced features.

Despite its success, the 9020 was eventually phased out in the 1980s in favor of newer technology, but it played a crucial role in the evolution of the National Airspace System (NAS) and set the foundation for future ATC systems.

On January 12, 2026, a customer reported a performance issue with a query that was slow on its first run after a batch job but fast on subsequent executions. Initially, the customer thought it was a caching issue, but the execution plan varied between the runs.

Dalibo suggested running the VACUUM ANALYZE command after the batch job to resolve the issue, but the customer confirmed that the tables had not been analyzed between the two executions.

The query in question involved a LEFT JOIN between two tables, and the first execution used a Merge Join while the second used a Nested Loop Join. The difference in execution plans stemmed from the optimizer’s ability to access accurate statistics on the data. In the first run, the optimizer struggled to gather information due to many dead tuples in the index, leading to an inefficient plan. By the second execution, the optimizer had better data, resulting in a faster plan.

The article concludes that it is possible for the execution plan to change between runs without any changes in data or statistics, highlighting a complex interaction within the PostgreSQL optimizer. The author encourages feedback and discussion regarding this case.

Summary of FastRender Project by Wilson Lin

Wilson Lin discussed FastRender, a web browser developed using autonomous coding agents, in a recent conversation. Here are the key points:

1. What is FastRender?
   FastRender is a web browser created from scratch using a large number of parallel agents. It was initially a personal project to test advanced AI models like Claude Opus 4.5 and GPT-5.1, focusing on complex tasks.

2. Current Functionality:
   As of now, FastRender can load web pages, but it lacks a functioning JavaScript engine, which has been temporarily disabled. Despite this, it can render sites like GitHub, Wikipedia, and CNN, albeit slowly.

3. Development Process:
   At its peak, around 2,000 agents worked simultaneously, producing thousands of code commits each hour. The project has made nearly 30,000 commits overall. The agents are organized in a tree structure to optimize task execution without causing many merge conflicts.

4. Research Focus:
   The goal of FastRender is not to compete with established browsers like Chrome but to study how multiple agents can collaborate effectively on complex software projects.

5. Feedback Mechanisms:
   The project uses specifications and visual feedback loops to guide the agents’ work, including screenshot analysis to refine results. The Rust programming language aids in ensuring code quality through strict compilation checks.

6. Agent Autonomy and Errors:
   Agents work autonomously, with the system running for extended periods without human intervention. Interestingly, small errors are permitted in the code to enhance throughput, allowing the system to maintain high productivity.

7. Conclusion:
   FastRender exemplifies how a single engineer, aided by a swarm of agents, can accomplish extensive coding tasks rapidly. It serves as a research tool to explore new methods of software engineering through multi-agent collaboration.

No summary available.

Summary: Kotlin's Rich Errors: A New Approach to Error Handling

At KotlinConf 2025, the Kotlin team introduced a feature called Rich Errors, which uses union types for better error handling. This allows functions to return types like String | Error, meaning they can return either a valid result or an error. This new method moves away from the traditional try-catch approach, making error handling more explicit and part of the type system.

Key Points:

• Rich Errors: These enable functions to clearly indicate possible errors in their return types, enhancing type safety.
• Comparison to Current Practices: While Kotlin already has Result<T> and other libraries like Arrow for error handling, Rich Errors integrate this functionality more naturally into the language.
• Benefits:
  • Type Safety: Developers can see what errors a function might produce just by looking at its signature.
  • Performance: Handling errors as regular values is more efficient than using exceptions, which have a runtime cost.
  • Composability: Error handling can be managed more smoothly with operations like mapping and flat-mapping.

The Rich Errors feature is still in development and may evolve, but it aims to streamline error management in Kotlin, making it more user-friendly and effective. This shift suggests a growing trend towards explicit error handling in programming languages.

The author created a project to measure age in kilometers instead of years because they found years boring. Initially, they used Earth's speed, but it felt too slow, so they switched to the Milky Way's speed, which is about 600 km/s, to create a sense of urgency. The project is a simple HTML file with no extra dependencies, and the main technical challenge was creating a smooth starfield. They pre-allocated star objects to prevent performance issues on mobile devices. The author invites feedback on the physics and performance.

No summary available.

The Anthropic Economic Index report analyzes how AI, specifically the Claude model, is impacting the economy as of November 2025. Here are the key points:

1. AI Usage Metrics: The report introduces new metrics to measure Claude's usage across five dimensions: user and AI skills, task complexity, autonomy of Claude, success rates, and purposes of use (personal, educational, or work).

2. Geographic Variations: There are significant differences in AI usage across regions. The US, India, Japan, the UK, and South Korea lead in usage, while global adoption correlates with GDP per capita. Within the US, states with more tech professionals show higher Claude usage, but there's a trend toward more equal usage across states.

3. Changes Since Last Report: Claude's usage remains concentrated on a few tasks, especially coding-related ones. However, augmented use (where users interact collaboratively with Claude) has increased, now comprising over half of all interactions.

4. Task Success Rates: Claude generally performs well on tasks, but struggles with more complex ones. The report suggests that AI's impact on jobs varies; some roles may see deskilling, while others may experience upskilling.

5. Implications for the Economy: Understanding task success rates and user education levels can inform projections about job automation and productivity changes. Countries with higher education levels may benefit more from AI, regardless of their adoption rates.

Overall, the report provides insights into how AI is reshaping work and productivity, emphasizing the need for ongoing research into its economic effects.

Summary:

Developers dislike lag when using remote coding environments. Compyle aimed to create low-latency development sandboxes, but their initial setup faced issues with slow startup times (10-30 seconds) and high latency (>200ms) due to extra network hops and inefficient routing.

To improve performance, they implemented a "warm pool" of machines, reducing startup time to about 50ms. However, latency remained a problem. The solution involved cutting out the middleman by directly connecting users to their sandboxes, simplifying authorization, billing, and message handling.

By using Fly.io's clever routing techniques, they improved user experience significantly. They then established multiple regional pools of sandboxes, allowing users to access environments closer to them, leading to average latency dropping to just 14ms.

The key takeaway is that simplifying architecture and removing unnecessary components can lead to better performance.

Summary:

Mark Gascoyne discusses a new approach to Internet Service Provider (ISP) infrastructure by creating an open-source, eBPF-accelerated Broadband Network Gateway (BNG) that runs directly on Optical Line Terminal (OLT) hardware. Traditional ISPs rely on centralized BNG appliances, which are costly and create a single point of failure. Gascoyne proposes distributing BNG functions to the edge, allowing each site to operate independently and keeping subscriber traffic local.

Key points include:

1. Centralized BNG Issues: Current models are expensive, rely on proprietary hardware, and can fail, affecting all subscribers.

2. Distributed BNG Concept: By implementing BNG functions on OLTs, ISPs can reduce bottlenecks and increase resilience.

3. eBPF/XDP Advantages: Gascoyne chose eBPF/XDP for its simplicity and adequate performance at edge sites, compared to more complex alternatives like VPP.

4. Architecture: The BNG architecture features a central control server for operations but keeps subscriber traffic local to each edge site.

5. Performance Insights: The system efficiently handles DHCP requests primarily through a fast path in the kernel, ensuring low latency and high request rates.

6. Edge Autonomy: If a site loses connectivity to the central server, it can still function independently for existing sessions and renewals.

7. Future Development: While the code is functional, it still needs enhancements like device authentication, IPv6 support, and a management UI. Gascoyne is considering open-sourcing the project to provide a viable alternative to expensive proprietary solutions.

In conclusion, this distributed architecture is more cost-effective, resilient, and operationally simpler, aligning with modern computing capabilities and the evolving needs of ISPs.

No summary available.

Summary of Updates to Web Search Products & Programmable Search Engine Capabilities

On January 20, 2026, Google announced changes to its Programmable Search Engine (PSE) to better serve various partners like academic institutions and retail websites. The updates aim to provide more focused and effective search solutions.

Key Changes:

1. Simplified Tools: Google is making it easier to choose the right tools for different search needs.

   • For Specific Sites: The Programmable Search Element (Search Element) will be simplified for creating tailored search experiences on individual websites.
   • For Advanced Needs: Google Vertex AI Search will still be available for features like AI-driven conversational search for businesses.
   • For Full Web Search: A complete web search option is available for those needing to search beyond a set number of domains.

2. Transition Planning: Partners are encouraged to prepare for transitions to these updated tools by January 1, 2027.

   • For Searches up to 50 Domains: The Search Element remains ideal for focused results.
   • For Searches Over 50 Domains: Users needing to search more than 50 domains should contact Google for information on the full web search solution.
   • For Custom Search JSON API Users: Vertex AI Search is a suitable option for up to 50 domains, with full web search available upon request.

3. New Engine Configuration: From now on, all new search engines must use the “Sites to search” feature, although existing engines can continue using the “Search the entire web” option until the transition deadline.

These updates aim to enhance search experiences for developers and partners.

Ken Shirriff's blog discusses the Intel 8086 processor, introduced in 1978 as a key development in computer history that shaped the x86 architecture. The 8086 is a 16-bit processor with a complex arithmetic-logic unit (ALU) capable of performing 28 different operations, including addition, subtraction, and logic operations like AND, OR, and XOR.

The ALU's operation involves a two-step process: first, a micro-instruction configures the ALU for a specific operation, and second, another micro-instruction retrieves the result from the ALU. Control circuitry connects the micro-instructions to the ALU to manage these operations. The 8086 processor is divided into two main parts: the Bus Interface Unit (BIU), which manages memory and instruction fetching, and the Execution Unit (EU), which executes instructions.

The 8086 uses microcode to implement machine instructions, with each micro-instruction performing two tasks: moving data and executing an operation. Some operations share microcode, and the specific ALU operation is determined by the machine instruction's opcode. The processor must remember the ALU operation between micro-instructions since the result is not immediately available.

The blog also highlights the ALU's design, which is crucial for performance and varies significantly among different processors. Overall, the 8086's architecture and microcode structure illustrate the complexities of early microprocessor design.

French artist Théo Champion, also known as Rootkid, has created an art installation called "Spectrum Slit" that visualizes nearby radio signals by turning them into light. Using a Raspberry Pi and a software-defined radio, Champion captures Wi-Fi and Bluetooth signals, which are then displayed through 64 LED filaments.

The installation's light changes based on wireless activity: when network usage is low, it emits faint light, and as activity increases, the light intensifies. Champion's goal is to highlight the technology that surrounds us and show its beauty.

Building this piece took about three weeks of research and experimentation, plus a week for assembly, costing around $1,000. Champion is considering displaying "Spectrum Slit" in Paris and is open to creating additional copies if commissioned.

Summary of "Bug Apple Loves #001: Mail Search Doesn't Work"

Apple's Mail app has a significant issue: the search function often fails. Users try to find emails by searching for the sender's name, subject line, or specific words but usually get no results. Frustrated, many switch to Gmail, where they can find the emails quickly. This problem has persisted for over a decade.

User Impact:

• Affected Users:
  • 14 million macOS users
  • 210 million iOS users
  • 28 million iPadOS users
• About 35% of these users rely on Apple Mail, and 40% of them experience search failures.

Search Process:

• Users typically spend extra time trying various search methods before giving up and checking Gmail. This can take several minutes, including attempts to fix the issue by reindexing or adjusting settings.

Wasted Time:

• Daily, users waste around 37.1 million hours on failed searches.
• Annually, this amounts to 1.5 million years of lost productivity.
• Over the years, this adds up to 21.8 million years of wasted time, costing humanity about $406.3 billion each year.

Conclusion: Despite the extensive time lost, Apple has not fixed this issue, which could potentially be resolved with 320 hours of engineering work.

The phrase "just fork it" is a popular saying in the Free and Open Source Software (FOSS) community, suggesting that if you dislike a project, you can simply create a new version of it. While technically true, this idea overlooks the complexities of maintaining a software project. Forking code is easy, but keeping a project running requires social effort, including managing users, trust, governance, and conflict resolution.

When people advise forking, they often avoid addressing the underlying social issues, leading to fragmentation rather than empowerment. This results in many poorly maintained projects, duplicated efforts, and smaller communities that struggle to thrive. The phrase "just fork it" can protect existing power structures and discourage meaningful engagement and collaboration.

Instead of defaulting to forking, the focus should be on fostering conversations and resolving conflicts within the community. Contribution should involve stewardship and cooperative problem-solving, rather than simply walking away from challenges. While forking can be valuable in certain situations, it should not be the first option. The goal should be to create shared, adaptable infrastructure that encourages collaboration over endless new projects.

The text discusses European alternatives for various digital products and services. Here are the key points:

1. Secure Email: Offers a secure email option to protect user privacy.
2. Support Local Businesses: Buying from local companies benefits the community by generating jobs and tax revenue.
3. Data Protection: Many non-European companies may not comply with data protection laws like GDPR.
4. VAT and Billing: Businesses in Europe can get VAT refunds on services from other European companies, which also provide familiar payment methods.
5. Legal Consistency: Operating within the EU simplifies legal processes due to common laws across member states.

The text also lists various categories of digital services, along with the number of European alternatives available for each, including web analytics, cloud computing, email providers, and more.

Summary: Floating-Point Printing and Parsing Simplified

This article by Russ Cox, published on January 19, 2026, discusses new methods for converting floating-point numbers between binary and decimal formats efficiently.

Key Points:

1. Floating-Point Basics: A floating-point number consists of a mantissa (m) and an exponent (e). Computers typically use binary (base 2), while humans prefer decimal (base 10).

2. Fast Conversion: The author argues that not only can conversions be simple, but they can also be fast. The post introduces a method called "fast unrounded scaling," which allows for quick approximations using efficient algorithms.

3. Algorithm Overview: The article provides a structured breakdown of various algorithms for formatting and parsing floating-point numbers:

   • Fixed-Point and Floating-Point Numbers: Definitions and differences.
   • Unrounded Numbers: Introduction of unrounded numbers based on IEEE754 standards.
   • Fixed-Width and Shortest-Width Printing: Techniques for formatting numbers.
   • Fast Unrounded Scaling: The implementation details that make the algorithms efficient.
   • Performance Comparison: How these new methods outpace existing algorithms.

4. Implementation in Go: The algorithms are implemented in Go, with the expectation that they will be included in an upcoming version (Go 1.27).

5. Historical Context: The post also reflects on the evolution of floating-point number algorithms over the past decade, suggesting that the simplicity and efficiency of the new methods may be approaching an optimal solution.

The article is detailed and serves as a comprehensive guide to understanding and improving floating-point printing and parsing.

The text includes CSS code for displaying images in a collection list on different screen sizes, along with recent news headlines.

Key Points:

1. CSS Code:

   • On large screens (min-width 992px), only the first item in groups of four shows a small image.
   • On tablets (768px to 991px), the same rule applies.
   • On mobile (240px to 768px), again only the first item shows a small image.

2. Recent News Headlines (dated January 24, 2026):

   • Ukraine is planning to create combat units for its foreign intelligence service.
   • The US Congress did not restrict President Trump’s military actions in Venezuela.
   • A key donor of Trump will provide fuel to the German Air Force (Luftwaffe).
   • The US released a new defense strategy that addresses China without mentioning Taiwan.
   • The manufacturer of IRIS-T is opening a new facility and plans to produce 10 air defense systems in 2026.

On January 15, 2026, Firestore announced a major update in partnership with Google Cloud, introducing a new query engine that enhances its capabilities. This updated engine features over a hundred new query options, allowing developers to build more complex and efficient applications while maintaining real-time sync and offline caching.

Key Features of the New Firestore Update:

• Pipeline Operations: This new feature allows developers to chain multiple stages within a query, enabling advanced operations like aggregations and string matching. Indexes are now optional, giving developers more control over performance.
• Example Use Case: A recipe app can now easily extract and suggest popular tags from recipe documents without needing separate tag data storage.
• Improved Performance: Firestore Enterprise edition does not automatically index collections, which can result in better write performance and lower costs. However, developers need to manage their own indexes.
• Flexible Pricing: Enterprise edition combines write and delete operations for billing and supports a generous free tier, making it cost-effective for development.
• Migration: Existing Firestore users can migrate their data to the new Enterprise edition but will need to set up new indexes and security rules.

Developers can start using these features by updating their Firestore SDKs and creating a new Enterprise edition database. The Standard edition will still be supported, allowing users to choose the best option for their needs.

No summary available.

No summary available.

AI is compared to a horse in several ways:

• It can move faster than walking, depending on the terrain.
• It's slower and less dependable than a train but can access more places.
• It requires a lot of resources (like data and power).
• You can't just command it to do something; you need to guide it with specific instructions.
• It generally stays on the right path, but you have to keep it focused.
• You can provide it with information, but you can't force it to use that information.
• A well-functioning AI responds well to guidance.
• People are often cautious about those who hype AI too much.

No summary available.

Radicle is an open-source platform for collaborative coding that operates on a peer-to-peer network using Git. Unlike traditional code hosting services, Radicle doesn’t have a central authority, giving users full control over their data and collaborative processes.

Key features of Radicle include:

• Decentralization: Code repositories are stored across various user nodes, ensuring no single point of control.
• Data Ownership: Users maintain ownership of their data, allowing for easy migration and backup.
• Local Functionality: Radicle can be used offline, providing consistent access to all features.
• Extensibility: Developers can create custom collaboration tools using Radicle’s framework.
• Security: All data is stored securely in Git and verified through cryptographic methods.

Radicle is available for Linux, macOS, and BSD, and offers a desktop client for a graphical experience. Users can install Radicle via a simple command or build it from source. It is open-source software, encouraging community contributions.

Stay updated on new releases and community discussions through various social media platforms and their community forums.

Summary of Cap’n Proto

Cap’n Proto is a very fast data format and remote procedure call (RPC) system, designed to be quicker than similar formats like JSON and Protocol Buffers. It has no encoding/decoding step, allowing direct writing of data to disk, making it efficient for in-memory representation.

Key features include:

• Platform Independence: The data format is consistent across platforms, designed for modern CPU efficiency.
• Backwards Compatibility: New fields can be added without changing existing ones, ensuring old messages remain compatible.
• Space Efficiency: Although it may seem to waste space with extra bytes, it can compress messages effectively, often resulting in smaller sizes than Protocol Buffers.
• Security: Cap’n Proto includes validation methods to ensure data integrity and security, making it reliable for use in secure environments.

Additional advantages include:

• Incremental Reads: Start processing a message before it's fully received.
• Random Access: Read specific fields without needing to decode everything.
• Memory-Mapping: Efficiently read large files.
• Inter-language and Inter-process Communication: Easily share data between different programming languages and processes.
• Optimized Memory Allocation: Faster handling of objects through arena allocation.
• Compact Code: Generates smaller code compared to Protocol Buffers.

Cap’n Proto was developed by Kenton Varda, who previously worked on Protocol Buffers, and it aims to improve upon its predecessor based on user feedback.

To get started with Cap’n Proto, users can visit the installation page and join the discussion group for contributions and updates.

Summary of "The Lost Art of XML"

The article discusses the decline of XML in favor of JSON and argues that this shift was misguided. While many developers now dismiss XML as outdated, the author believes its structured features provide significant advantages over JSON, particularly in areas like validation, namespacing, and self-documentation.

Key Points:

1. XML vs. JSON:

   • XML offers robust schema validation, allowing precise data structure definitions, which JSON lacks.
   • XML supports namespaces, enabling the combination of multiple schemas without conflicts, while JSON can lead to naming collisions.
   • XML allows comments within documents for better documentation, whereas JSON does not permit comments.

2. Convenience vs. Correctness:

   • The preference for JSON stems from its simplicity and ease of use, but this convenience often comes at the cost of accuracy and reliability.
   • XML's complexity, such as requiring closing tags, actually aids in clarity and structure.

3. Binary XML Solutions:

   • The article points out that binary formats like Fast Infoset and EXI exist, which retain XML's benefits while reducing size and improving transmission efficiency.

4. Industry Trends:

   • The author criticizes the industry's trend of prioritizing developer convenience over the robustness of data formats, resulting in more errors and less structured data.

5. Conclusion:

   • XML remains a superior choice for complex systems requiring durability and correctness, despite being seen as "old-fashioned." The article calls for a reevaluation of XML's practicality and benefits in modern software engineering.

A person created a large isometric pixel art map of New York City called isometric.nyc using no-code tools like nano banana and coding agents. They didn't write any code themselves, but the project required a lot of manual work. They also wrote an article discussing their process and thoughts on the future of AI in coding and creativity. You can read more about it at the provided link.

Summary: Replacing Protobuf with Rust for Faster Query Processing in PgDog

PgDog is a tool for enhancing PostgreSQL performance, utilizing Rust to interact with the libpg_query library for SQL query processing. Initially, it relied on Protobuf for data serialization, but the team found that eliminating Protobuf and using direct Rust-to-C bindings significantly boosted performance—making query parsing five times faster and deparsing nearly ten times faster.

Key Performance Improvements:

• Parsing Queries:

  • With Protobuf: 613 queries/second
  • Without Protobuf (Direct C to Rust): 3,357 queries/second (5.5x faster)

• Deparsing Queries:

  • With Protobuf: 759 queries/second
  • Without Protobuf (Direct Rust to C): 7,319 queries/second (9.6x faster)

Process Overview:

1. Profiling: The team used profiling tools to identify slow parts of the code, focusing on the pg_query_parse_protobuf function.
2. Caching: They implemented a caching system for query parsing to reduce duplicate work, but encountered issues with certain ORMs and outdated PostgreSQL drivers.
3. AI Assistance: They utilized a language model to help rewrite the bindings from Protobuf to Rust, resulting in 6,000 lines of code that connected Rust and C types effectively.

Implementation Details:

• The Rust code uses unsafe functions to handle C structs and perform conversions back to Rust, maintaining performance while ensuring data integrity.
• The recursive algorithm used for converting the Abstract Syntax Tree (AST) is efficient and leverages stack memory, enhancing speed and readability compared to iterative approaches.

Conclusion: Removing Protobuf has significantly improved PgDog's performance, making it faster and more efficient to operate. The team is seeking a Founding Software Engineer to further develop their project and continue enhancing PostgreSQL scalability.

The text discusses the concept of workspaces and monorepos in package managers, explaining their purpose and how they function across different programming ecosystems.

Key Points:

1. Definition and Purpose:

   • Workspaces allow package managers to manage local dependencies efficiently, so you don’t have to publish changes every time you alter a dependency. They automatically link packages during installation, enabling immediate access to changes.

2. Common Use Cases:

   • Workspaces are beneficial not just for large projects but also for smaller setups, such as:
     • Libraries with plugins
     • Applications with local utilities
     • Packages tested against example apps
     • Debugging local copies of dependencies

3. Difference Between Workspaces and Monorepos:

   • Workspaces help manage packages developed together, while monorepos consolidate all code in one location. They overlap but serve different purposes.

4. How Different Package Managers Handle Workspaces:

   • npm: Uses a workspaces field in package.json, linking local packages but lacking special publish support.
   • Yarn: Similar to npm but introduced workspaces earlier and maintains the same configuration.
   • pnpm: Does not hoist dependencies and uses a unique workspace protocol for resolving local packages.
   • Other ecosystems like Rust (Cargo), Go (go.work), and PHP (Composer) have their own implementations, often focusing on local development and linking.

5. Common Issues:

   • Phantom Dependencies: Occur when hoisted dependencies can be imported without being declared, potentially leading to errors upon publishing.
   • Version Mismatches: Local development may overlook version constraints, leading to issues after publishing.
   • Tooling Compatibility: Tools like Jest and TypeScript may need configuration to work with workspaces.
   • Build Order: Workspaces manage code organization but not the order of builds, often requiring additional tools.
   • Publishing Coordination: Workspaces simplify development but not the process of releasing packages together.

6. Conclusion:

   • The discussion suggests that while workspaces and monorepos make package management easier, they introduce complexity, particularly in coordinating updates and publishing. The author invites feedback from those who regularly use workspaces about their experiences.

No summary available.

The author shares their experience with the Nüborn Baby after three months of use. While many people praise the product, the author has found several issues.

1. Ordering and Delivery: The ordering process is complicated and can take up to 40 weeks. There are extra costs for delivery insurance, and the product is often out of stock.

2. Pricing: Although marketed as free, there are many hidden costs, such as genetics tests and potential third-party fertility treatments that can be very expensive.

3. Product Features: The Baby arrived needing repairs and did not have the expected features. Many capabilities require lengthy updates to unlock, which can take months or years.

4. Maintenance and Care: The Baby requires constant recharging and cleaning, which can make it hard for owners to manage other responsibilities. There are also additional products needed for feeding and maintenance that can add to the overall cost.

5. User Interface: The Baby only has one type of alert (loud crying), which is frustrating and does not clearly indicate what the issue is.

Overall, the author is not impressed with the Nüborn Baby, despite a few charming moments, and questions the authenticity of positive reviews.

No summary available.

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Text-to-speech technology for blind users has not significantly improved in the last 30 years, unlike the advancements seen in the sighted world. Blind users prefer voices that are fast, clear, and efficient, often resulting in a preference for robotic-sounding voices that can be understood at high speeds. The most popular voice, Eloquence, hasn’t been updated since 2003, causing issues with compatibility and security as technology evolves.

Blind users of other languages face similar challenges, with many modern voices being inadequate. While espeak-ng aims to support numerous languages, it has issues with pronunciation accuracy and maintenance.

Recently, attempts to integrate modern AI-based text-to-speech systems, such as Supertonic and Kitten TTS, into screen readers like NVDA revealed numerous problems. These include:

1. Dependency Bloat: Large, complex dependencies slow down systems and pose security risks.
2. Accuracy Issues: AI models often skip words or misread numbers, which is unacceptable for screen readers.
3. Speed Limitations: Modern systems require complete text chunks before generating speech, unlike older systems that respond immediately.
4. Lack of Customization: AI models offer limited control over voice parameters, reducing functionality for users.

The future for blind screen reader users looks uncertain. Current options are outdated or inadequate, and creating a modern, efficient system may require significant funding and expertise. In the meantime, users may have to rely on "good enough" solutions while hoping for advancements that meet their needs.

"Connected and Alone" discusses how technology, especially social media, can create a false sense of connection while actually isolating people. It highlights that while we can communicate easily online, these interactions often lack depth and emotional connection. The text emphasizes the importance of real, face-to-face relationships for our well-being and suggests that relying too much on digital communication can lead to feelings of loneliness. Overall, it urges individuals to seek genuine connections beyond their screens.

No summary available.

eBay has updated its User Agreement, effective February 20, 2026, which includes significant changes:

1. Ban on AI Agents: eBay now explicitly prohibits AI "buy for me" agents and large language model (LLM) bots from accessing its platform without permission.

2. Arbitration and Dispute Resolution:

   • The updated agreement clarifies the rules around arbitration, including restrictions on class actions and other group legal actions.
   • Users can only pursue claims individually, and cannot join class actions or seek damages for third parties.
   • The address for sending arbitration requests has changed to a new location in Draper, UT.

3. Opt-Out Changes: Only new users can opt out of the arbitration agreement; existing users missed their chance if they did not opt out before May 16, 2025.

Overall, these updates aim to tighten control over how AI interacts with eBay and clarify the legal processes for users. Users are encouraged to read the full terms for a comprehensive understanding.

Summary of ast-grep (sg)

ast-grep is a command-line tool designed for code searching, linting, and rewriting based on the structure of code rather than just text. It uses an abstract syntax tree (AST) to match patterns, allowing users to write patterns similar to regular code.

Key Features:

• Pattern Matching: Use $ followed by uppercase letters (e.g., $MATCH) as wildcards to match AST nodes.
• Installation: Available through various package managers like npm, pip, cargo, and homebrew. You can also build it from source using Rust.
• Command Line Usage: Example command: ast-grep --pattern 'var code = $PATTERN' --rewrite 'let code = new $PATTERN' --lang ts.
• Intuitive API: Offers an easy way to find and replace code with a jQuery-like API for AST traversal.
• YAML Configuration: Allows users to create new linting rules or modify code configurations.
• Performance: Optimized for speed using a compiled language and tree-sitter parsing.

ast-grep aims to simplify working with abstract syntax trees, making it beneficial for open-source developers, tech leads, and security researchers who want to enforce best practices or adopt changes easily.

AI Usage Policy Summary

The Ghostty project has clear rules for using AI:

1. Disclosure Required: Always state what AI tool you used and how much it assisted in your work.

2. Pull Requests (PRs):

   • AI-generated PRs can only address accepted issues.
   • PRs without an accepted issue will be closed.
   • If AI use is suspected but not disclosed, the PR will also be closed.
   • For non-accepted issues, start a discussion instead.

3. Verification: AI-generated code must be fully tested by humans first. Do not allow AI to write code for environments you can't test.

4. Human Oversight: AI can assist in discussions, but all AI-generated content must be reviewed and edited by humans to ensure quality.

5. Media Restrictions: Only text and code can be generated by AI; no AI-generated images, videos, or audio are allowed.

6. Accountability: Poor AI users will face consequences. While support is available for junior developers, they are encouraged to learn without relying on AI.

7. Maintainers' Freedom: Maintainers can use AI tools at their discretion, as they have proven their ability to use judgment effectively.

8. Respect for Human Effort: All contributions should reflect effort and quality to avoid burdening maintainers.

The policy is not anti-AI; it aims to ensure quality due to many inexperienced users misusing AI tools. Ghostty welcomes AI as a helpful tool when used responsibly.

Sahil and Manu, two brothers, have spent two years developing text-to-video models, which they are now releasing under the Apache 2.0 license. Their models can generate 2-5 seconds of video at 360p or 720p resolution and have better motion capture and aesthetics compared to similar models.

They started from scratch because previous models struggled with temporal coherence and transitioning between images and videos. Their version 2 uses advanced techniques for text encoding and compression, while also incorporating a smaller, efficient VAE for performance.

They found that their model works well for cartoon styles, food, and nature scenes but struggles with complex movements and consistent text. They aim to create a flexible product by directly enhancing the model instead of relying on existing solutions.

Future plans include improving physics and deformations, increasing speed, adding audio capabilities, and scaling the model. They are open to sharing their methods and answering questions about their development process.

Turso Database Summary

Turso Database is a new SQL database written in Rust that is compatible with SQLite. It is currently in beta, so it may have bugs, and caution is advised when using it with important data.

Key Features:

• Compatibility with SQLite in SQL dialects and file formats.
• Real-time change tracking (Change Data Capture).
• Supports multiple programming languages: Go, JavaScript, Java, Python, Rust, and WebAssembly.
• Asynchronous I/O support for Linux.
• Works on multiple platforms: Linux, macOS, Windows, and browsers.
• Vector support for search and manipulation.
• Enhanced schema management features.

Experimental Features:

• Improved write performance with concurrent operations.
• Data encryption for security.
• Incremental computation capabilities.
• Full-Text Search powered by the tantivy library.

Upcoming Features:

• Vector indexing for faster searches.

Getting Started: You can install Turso Database using a command line script. After installation, you can interact with the database using SQL commands.

Programming Language Examples:

• Rust: Use cargo to add and connect to the database.
• JavaScript: Install via npm and connect easily.
• Python: Use pip to install and connect.
• Go: Use go get to install and connect.

MCP Server Mode: Turso includes a Model Context Protocol (MCP) server, allowing AI assistants to interact with databases. You can configure it to handle database queries in natural language.

Contributing: Contributions are welcome, and there are rewards for reporting bugs that lead to data corruption.

Important Notes:

• Turso Database is not ready for production use yet.
• It aims to evolve SQLite with features like async support and vector search, distinguishing itself from the libSQL project.

License: The project is licensed under the MIT license, and contributions will also be under the same license.

For more detailed information, refer to the Turso Database Manual.

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Zotero has launched Zotero 8, a major update that enhances the features introduced in Zotero 7. Key improvements include:

• Unified Citation Dialog: A redesigned citation tool with two modes (List and Library) for easier citation management. You can customize citations and switch modes easily.

• Annotations Display: Annotations from PDFs and other documents now appear under their respective items, making it easier to view and search them.

• Reader Appearance Panel: A new panel for customizing document view settings and themes, including options for dark and light modes.

• Note Tabs: Notes can now be opened in tabs for better organization and readability.

• Reading Mode for Webpages: A new feature that cleans up webpage snapshots for easier reading.

• Tabs Menu Enhancements: Improved navigation for tabs, allowing quick access and management.

• Continuous File Renaming: Attachment filenames will automatically update when you change item metadata.

• New Attachment Title Options: Improved handling of attachment titles for consistency and simplicity.

• ARM Linux Support: Zotero 8 now supports Linux on ARM devices, enhancing compatibility.

• User Interface Improvements: Various tweaks for easier navigation and item management.

• Tag Autocomplete: The Zotero Connector now supports tag suggestions and allows note-taking during item saving.

Zotero 8 has additional features and requires macOS 10.15+, Windows 10+, or a compatible Linux system. Users can upgrade or download the new version from the Zotero website.

The article discusses a collection of over 50 optical illusions created using CSS and HTML. It highlights various types of illusions, explaining how they trick our perception. Here are the key points:

1. Poggendorff Illusion: A diagonal line appears misaligned due to a vertical bar interrupting it, even though both segments are continuous.

2. Induced Gradients: Gray bars placed over a gradient make it seem like they have their own gradients.

3. Cornsweet Illusion: Identical colors look different based on their surrounding contrasts.

4. White’s Illusion: Gray columns appear different shades due to their backgrounds.

5. Wertheimer-Koffka Ring: A ring appears to change color based on its background.

6. Adelson’s Illusion: Two tiles appear to be different colors when they are the same, influenced by their surroundings.

7. Color Illusions: Several illusions, like the ColorSpheres, show how our brain interprets overlapping patterns as different colors.

8. Motion Illusions: Some images give the impression of movement despite being static, like the Expanding Hole and Rotating Snakes.

9. Animated Illusions: Some animations create deceptive perceptions of motion, such as the Animated Ebbinghaus Illusion.

The article encourages readers to interact with the illusions by hovering over demos to see the effects clearly. It also credits sources of inspiration for these optical phenomena.

The text discusses the difference between "askers" and "guessers" in how people approach knowledge and problem-solving. Askers are open to seeking help and requesting information, while guessers tend to rely on their own assumptions without asking questions. The article highlights that askers often achieve better outcomes because they gather more information and perspectives. Overall, it suggests that being willing to ask questions is a valuable skill that can lead to success.

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Reference ID: 0.73b82917.1769270755.21e53e49

No summary available.

The text is a prompt indicating that the browser is being checked, which will only take a brief moment.

The author describes their experience of being banned from using Claude, an AI tool, after attempting to automate the creation of a CLAUDE.md file for their projects. They were a paying user, but suddenly received a message stating their account was disabled without any warning or feedback. The author explains that they were using two instances of Claude to help with project scaffolding by having one instance update a tool while the other worked on a new project.

They suspect their actions triggered the platform's security measures, leading to the ban. Despite appealing the decision and trying to communicate with support, they received no response, only a credit note for their subscription fee. The author reflects on the lack of effective customer support and the challenges of AI moderation, which often prioritizes safety over user intent. Ultimately, they plan to rework their project independently, highlighting the frustrations of navigating automated systems.

Summary: Making PDFs Smaller with Brotli Compression

iText is introducing Brotli compression to PDFs, promising to reduce file sizes by 15-25% without losing quality. This is a major upgrade from the 30-year-old Deflate algorithm, which has been the standard for PDF compression.

Key Points:

1. Brotli Compression: Developed by Google, Brotli is already widely used on the web and is now being added to the PDF specification to enhance file efficiency.
2. Compatibility Challenges: Introducing new compression methods in PDFs is complex due to the need for backward compatibility with existing software. The PDF Association is working to ensure new features do not disrupt current usage.
3. Technical Implementation:
   • iText has developed a way to read and write Brotli-compressed PDFs using their SDK.
   • The process involves creating a new interface for compression strategies, allowing different algorithms to be used without changing the core PDF writing functions.
4. Separate Encoder Module: While the Brotli decoder is implemented in pure Java, the encoder requires native code. To avoid complications with native dependencies, iText has created a separate module for Brotli compression.
5. Future Compatibility: Currently, PDFs using Brotli may not be compatible with all readers, but they will be future-proof as the PDF Association finalizes the new standard.
6. Benefits of Early Adoption: Users who start using Brotli compression now can reduce storage costs and prepare for future updates when the compression becomes standardized.

Overall, iText's implementation of Brotli compression represents a significant advancement in making PDFs smaller and more efficient, while also contributing to the development of PDF standards.

Qwen3-TTS is an advanced speech generation system developed by Qwen, which offers features like voice cloning, voice design, and high-quality human-like speech synthesis. It uses a unique speech encoder called Qwen3-TTS-Tokenizer-12Hz, allowing for efficient speech processing and natural-sounding output.

Key features include:

• Multiple Models: There are two model sizes (1.7B and 0.6B), with the larger model providing peak performance and the smaller one focusing on efficiency. Both support ten major languages and various dialects.
• Fast Processing: The system can generate audio very quickly, with the first sound output occurring after processing just one character.
• Natural Language Understanding: It can adjust voice attributes like tone and emotion based on user instructions, providing a lifelike experience.

The models have been open-sourced and demonstrate state-of-the-art performance in tasks such as voice design, control, and cloning across multiple languages. They are capable of adapting to different contexts and user needs, making them versatile for various applications.

Qwen3-TTS is accessible on GitHub and via the Qwen API, allowing developers to integrate these speech capabilities into their projects easily.

Capital One has announced that it will acquire Brex. Both companies have released statements about this partnership. For more details, you can visit the links provided for Capital One's and Brex's official announcements.

The article discusses the high number of packets sent during an SSH session when a single keystroke is made, specifically noting that around 100 packets can be generated for just one keypress. This is primarily due to SSH's new feature introduced in 2023 called keystroke timing obfuscation, which sends extra "chaff" packets to obscure the timing of keystrokes and protect user privacy.

The author, who is developing a high-performance game that uses SSH, noticed that during testing, CPU usage dropped significantly when the game stopped sending regular game data and only sent a message about screen size. This led to an investigation using tcpdump to analyze packet behavior, revealing that the majority of packets were 36 bytes in size, with many being TCP ACKs.

To improve performance, the author disabled the keystroke obfuscation feature by not advertising a specific SSH extension, leading to a significant decrease in CPU usage and bandwidth. This approach, while effective, raises concerns about maintaining the modified library.

The author reflects on the debugging process, incorporating language models like Claude Code, which aided in analyzing the packet data and provided insights, although there were some challenges in interpretations.

In summary, the text highlights the impact of SSH's packet behavior on performance in real-time applications and discusses solutions for optimizing data transmission while maintaining user experience.

On January 23, 2026, Ryan Donovan interviewed Michael Parker, VP of Engineering at TurinTech, about AI-generated tech debt and how it affects developers. They discussed that while AI tools have potential, their productivity results are inconsistent. Experienced developers can be 19% slower when using AI due to varying codebases, especially in legacy systems where AI lacks context.

TurinTech's platform, Artemis, aims to help teams manage code better while addressing the challenges of AI. Michael highlighted the emergence of new roles in development, such as "developer coaches," who focus on optimizing AI interactions rather than writing code. He also noted the need for better AI tools that can understand context, improve maintenance, and automate mundane tasks.

The conversation emphasized the importance of planning in software development, suggesting that AI could assist in gathering requirements and providing context. Michael expressed hope for AI tools to evolve into proactive agents that collaborate effectively with human teams.

For developers feeling nervous about AI's impact, Michael advised staying updated with new tools and learning continuously, stressing that foundational skills in problem-solving will always be valuable. He encouraged developers to engage in discussions across different viewpoints on AI to better prepare for future changes.

Summary of Docker's Journey and Current State (2026)

Docker Inc, originally a pioneer in application deployment through containerization, faces challenges in 2026 as it seeks a sustainable business model. Despite creating a widely-used technology, Docker has struggled to monetize it effectively since the technology has become commoditized and open source.

Key points in Docker's evolution include:

1. Identity Crisis: Docker is trying to find its market position after the core technology became a standard, but the company hasn't figured out how to generate revenue from it.

2. Swarm Exit: Docker attempted to compete with Kubernetes in orchestration but ultimately sold its Swarm product, indicating a shift away from being a full-stack platform.

3. Focus on Developer Tools: Docker pivoted to enhance developer experience, leading to the creation of tools like Docker Scout (for security) and the acquisition of Testcontainers (for better testing capabilities).

4. AI Integration: The company then shifted to AI, introducing products like Docker Model Runner and expanding Docker Compose to support AI models, along with partnerships with major cloud providers.

5. Hardened Images: Docker made over 1,000 secure images free and open source, a response to competition from Chainguard, raising questions about its business strategy.

6. Leadership Changes: A new CEO has led to speculation about a possible acquisition by a larger cloud provider, suggesting Docker may be preparing for sale rather than long-term independence.

In conclusion, while Docker's technology remains essential in software development, the company's future is uncertain. Its series of strategic pivots reflects a search for identity and revenue in a market it once dominated, emphasizing the difficulties of monetizing highly successful open source innovations.

Discover 3D Maps that let you explore exciting locations like golf courses, trails, and properties with interactive fly-through experiences.

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No summary available.

Hello HN! We are Kamran, Raaid, Laith, and Omeed from Constellation Space. We have developed an AI system that can predict satellite link failures before they occur. You can watch a video about our system here.

Our team has extensive experience in satellite operations from companies like SpaceX, Blue Origin, and NASA. We noticed that by the time problems with satellite links are detected, data is often already lost.

Satellite links are influenced by many factors, such as weather conditions and satellite positioning. Traditionally, operators react to issues when they occur, but this method is not effective as the number of satellites increases.

Our solution processes telemetry data from various sources at a high speed and uses physics-based models along with machine learning to predict link failures. We can foresee most failures 3-5 minutes in advance with over 90% accuracy, allowing operators to reroute traffic to prevent data loss.

We are currently testing our system with defense and commercial partners, providing real-time health monitoring and forecasts. Our technology is designed to operate securely in different environments.

We are seeking feedback from those experienced in satellite operations or related fields. We want to know how we can improve our system for practical use. Please feel free to ask any technical questions!

The article discusses recent research on how exceptional human performance develops across various fields, including sports, science, and music. Key findings include:

1. Talent Development Patterns:

   • Young exceptional performers tend to peak quickly but focus on one specific area, while adult top performers usually achieve success more gradually and often engage in a broader range of practices.

2. Discrepancy in Populations:

   • The research shows that young prodigies and adult elite performers are often different individuals, with around 90% of top youth performers not becoming top adults in their fields.

3. Practice Differences:

   • Early success is linked to intensive, specialized practice, whereas adult excellence often comes from varied, multidisciplinary experiences and gradual skill development.

4. New Hypotheses:

   • The authors suggest new theories to explain these patterns, which could help improve training and educational practices for aspiring top performers.

Overall, the findings challenge traditional beliefs about talent and emphasize the importance of a diverse practice and gradual development in achieving world-class performance.