Tag
A staff engineer's playbook on finding high-impact problems: absorb problems rather than requests, wait for recurring patterns, find the common shape, and pressure-test before building — best suited to bottom-up teams with roadmap influence.
OpenAI's AI agents have solved the Navier-Stokes existence and smoothness problem, a decades-old mathematical puzzle, challenging traditional artistic approaches to math problem-solving.
The article explores how first principles thinking helps senior engineers adapt to changes, particularly in the agentic era of AI, by focusing on momentum and understanding core problems through small learning loops.
The post discusses how most people use AI superficially for trivial tasks, while the real advantage comes from building systems that solve problems effectively.
a16z announces The Horowitz Andreessen Academy in San Francisco, an elite educational institution for young high school graduates focusing on AI-driven problem-solving and building things.
A property insurance claims professional describes how he used AI to start from a simple question and build a multi-agent insurance claims system over five weeks, emphasizing problem-solving skills over coding.
The article questions what it means when reports state that OpenAI is close to solving a Millennium Prize problem, highlighting the challenge of knowing progress on complex unsolved mathematical problems.
Boris Cherny shares his iterative problem-solving framework for product development in the AI era, emphasizing the value of being wrong to refine problems and solutions based on new data.
FrontierMath has successfully solved its first 'Major Advance' problem, marking a significant milestone in mathematical research and AI collaboration.
OpenAI conducted a private experiment with 10,000 agents on a Millennium Prize problem, and now a new public platform, solveathome.org, enables collaborative agent pooling with transparent verification and review.
Astra is a service built with GPT-6 that solves long-standing problems faced by medical students by providing an integrated tool.
The tweet proposes using 10,000 AI agents to tackle hard problems quickly, aiming to settle data center debates by November and criticizing GPU waste on trivial content, while suggesting tests for repeatability.
Daniel Griesser shared a personal experience of using Astra to solve a real-world problem by recording a video and analyzing measurements, describing it as a 'touch of AGI' moment.
Terence Tao discusses concerns about solving mathematical problems prematurely using purely AI-powered methods, a sentiment the author believes also applies to programming.
Mathematician Eric Harshbarger and his colleagues have invented a set of dice that guarantee no ties when determining who goes first in board games, solving a longstanding mathematical problem.
This article discusses the 4E framework for architectural work, focusing on the 'Evaluate' and 'Examine' steps to identify trade-offs and understand the problem holistically.
Kent C. Dodds emphasizes the importance of teaching users to utilize AI agents effectively by communicating their goals, allowing agents with proper tools to overcome obstacles.
The XY problem describes a scenario where individuals ask about their attempted solution rather than the underlying problem, leading to inefficiency in tech help-seeking. It provides guidelines to improve communication by sharing broader context and details.
A tweet recommends a video where @poteto shares her journey from skepticism to systematic problem-solving with AI agents, and includes a quote from a SpaceXAI engineer about using agents for automation.
The author discovered that improving an AI feature required focusing on user trust by providing source links and flagging uncertain outputs, rather than just enhancing model accuracy.