#learning

The article illustrates how producing many imperfect attempts leads to better results than aiming for perfection from the start. It argues that great ideas emerge through consistent practice and volume of work, not from waiting for inspiration. The key advice is to start before feeling fully ready and to embrace the learning process of repeated attempts.

Research explores how microorganisms like bacteria and protozoa demonstrate learning and memory capabilities without nervous systems. These organisms exhibit behaviors such as habituation, associative learning, and decision-making through molecular and cellular mechanisms. The findings challenge traditional views of cognition as exclusive to organisms with brains.

The article argues that access to knowledge is no longer the primary limitation for learning, as information is now widely available through the internet. Instead, the key challenges have shifted to developing critical thinking skills, filtering information, and applying knowledge effectively in real-world contexts.

Memory Machines explores whether large language models can generate effective flashcards from readers' highlights and annotations. The article examines the potential for AI to create lasting learning materials from reading materials.

Drip is a tool that displays educational content while users wait for AI responses. It aims to help people learn something new during the thinking time of AI assistants.

The article provides guidance on learning programming in 2026, covering recommended languages, learning resources, and practical approaches for beginners. It discusses modern tools and methodologies relevant to the current programming landscape.

Paul Graham argues that the most harmful lesson students learn in school is to treat problems as something to be solved quickly rather than understood deeply. He suggests this mindset prevents people from tackling ambitious, open-ended challenges where the solution isn't immediately apparent. The essay encourages unlearning this approach to enable more meaningful work.

The article discusses the experience of being a beginner or "noob" in any field. It explores how this state of inexperience is universal and temporary for everyone learning something new. The author examines the psychological aspects of being a novice and how this phase is essential for growth.

Andy Matuschak advocates for working transparently by sharing early-stage thinking and works-in-progress publicly, similar to leaving a garage door open. This approach enables feedback, collaboration, and reduces the pressure of polished final products.

Paul Graham notes that startups, like computer science, involve launching to discover what should have been built. He references Fred Brooks' observation that debugging specifications is central to programming.

The article describes an AI Tutor system that provides personalized learning assistance and educational support through artificial intelligence technology.

Paul Graham argues that reading is essential for thinking and that people who don't read are at a disadvantage. He suggests that reading helps develop ideas and that the internet has made reading more important than ever.

The article discusses using games as an engaging method to learn SQL, a programming language for database management. It presents interactive approaches that make SQL education more accessible and enjoyable for beginners.

A study on AI-assisted coding found that participants who used AI didn't complete tasks faster and performed worse on skill retention tests. However, when excluding those who manually retyped AI-generated code instead of copy-pasting, AI users were 25% faster. The research suggests that while AI can speed up work, relying heavily on it for coding reduces learning of specific skills.

The author argues there is no single "Bible" or best book for any topic, as learning requires multiple resources from different perspectives. They compare it to creating a 3D model from multiple photos, where each resource contributes differently based on individual compatibility. The key is to understand one's own learning preferences rather than relying solely on popular recommendations.

Dan Abramov, a React core team member, lists programming topics he doesn't know well as of 2018, including low-level JavaScript, CSS, and various web technologies. He emphasizes that admitting knowledge gaps doesn't diminish one's expertise.

The article discusses the challenges of understanding how a program is intended to work and provides guidance on approaching this process without having a mentor available.

The author describes a new workflow called "Teach me something" that uses Claude as an alternative to doom scrolling. The approach leverages large language models' strengths in non-determinism and text generation.

The article presents 11 notes on the process of transforming unknowns into knowns, discussing methods for uncovering hidden information and converting uncertainty into understanding through systematic approaches.

The article discusses learning KeyBee, a keyboard layout designed for efficiency and ergonomics. It covers the layout's design principles and the learning process involved in adopting it.

The article provides practical guidance for teaching children to ride bicycles, covering topics like choosing the right bike size, using balance bikes, and safety considerations. It emphasizes patience and gradual progression through different learning stages.

The author reflects on how skill development often occurs through sudden "phase changes" rather than gradual progress, drawing from their experience with running and programming. They explore whether these mental leaps can be accelerated or if it's more productive to motivate people to persist until the phase change occurs naturally.

The author reflects on learning Unity through trial and error without proper guidance, which led to inefficient practices and knowledge gaps. They eventually recognized the importance of structured learning and foundational concepts for effective game development.

Naval Ravikant states that the smartest people are all self-taught, even if they attended formal schooling.