X Bookmarks

This page discusses a B2B masterclass focused on closing high-ticket deals. It emphasizes the importance of contextualizing price tags to help buyers understand their value in relation to potential outcomes.

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MIT has made a groundbreaking advancement in AI memory by teaching systems how to read, rather than simply increasing their capacity. This innovative research, released on December 31, 2025, by three CSAIL researchers, challenges existing paradigms in AI development.

A 1-month-old YouTube channel just crossed $60,000 in ad revenue. Each video takes 20 minutes, with the first upload sitting at 600,000 views and generating $15,000 a month from just 7 videos.

This page features a post by Levi Munneke on X, sharing a link to additional content. The link provided may lead to further insights or information relevant to the topic discussed.

This free 15-minute assessment turns cold conversations into $999 AI audit clients 30-50% of the time. No certifications, portfolio or technical skills required. Just two short calls and one framework. I broke down the entire playbook on the latest episode of the Build With AI.

In a 1-hour conversation, Jenny Wen, head of design for Claude at Anthropic, discusses the decline of traditional design processes and the emergence of machine-readable design systems. She explains why the discovery -> mock -> iterate loop is becoming obsolete and what designers should focus on instead.

Hung Vinh expresses frustration that a particular repository has fewer than 400 stars, highlighting the exceptional skills of /autoreview and /handoff. He thanks contributors @steipete and @openclaw for their work.

Corey Ganim shares how he generated 7 qualified leads from a single event for his AI business at no cost. He outlines 7 free methods that require only time and emphasizes the importance of a free 15-minute mini AI assessment.

This page discusses how the buyer's behavior has changed since 2022, emphasizing that current go-to-market (GTM) strategies may be outdated. It highlights the importance of adapting to new buyer preferences, such as conducting private research and using AI for vetting before engagement.

This page details how to set up a local LLM agent using a self-hosted SearXNG instance in Docker. It explains the configuration for Hermes' web search to utilize this metasearch engine for enhanced privacy and control.

This page provides an overview of inference engines and their role in running large language models (LLMs) locally at home. It discusses key concepts such as the differences between prefill and decode, VRAM and bandwidth, and the significance of KV cache and quantization.

This page discusses how to effectively leverage AI as a compounding asset by codifying best practices and democratizing knowledge across a company. It highlights common requests from businesses at the beginning of their AI journey.

Alex Lieberman discusses how he created a content machine that transformed him into a one-person media company, generating significant revenue for @tenex_labs. He highlights the impact on his employees, turning them into content creators, and hints at the possibility of open-sourcing the project.

A scientist in Denmark figured out how to make Claude prepare his job applications. He open-sourced the whole thing, built by PhD geophysicist Mads Lorentzen on top of Claude Code and released under MIT license.

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Corey Ganim shares his success in earning over $1,000 an hour through an AI service called the AI Concierge, which utilizes Claude Opus 4.8. He offers clients personalized support for building AI systems, charging $1,500+ per month for two live calls.

Matt Van Horn shares a concise summary of his new article detailing various Agentic Engineering hacks. He reflects on the evolution of his coding approach and introduces a planning method for implementing ideas.

James Meadlock shares insights on the importance of ecosystem in machine learning, highlighting his use of a 512GB Mac Studio and DGX Spark systems for LLM development. He emphasizes the maturity of vLLM and its effective features like tool call parsers and batching.

Dan Woods shares a link on X, providing insights or information relevant to his followers. This post encourages engagement and discussion among users.

This page discusses the capabilities of Qwen 27B running on a 3090 GPU, achieving over 70 TPS. It highlights the surprising performance of this six-year-old technology in the AI landscape.

The Hermes Agent features an impressive array of over 100 pre-enabled skills, aiming to provide users with a ready-to-use experience. However, the necessity of certain skills, like polymarket and multiple baoyu art skills, raises questions about user customization.

Muhammad Ayan shares insights on open-sourced AI tools, highlighting 11 GitHub repositories that are essential for developers and enthusiasts. Notable mentions include PilotDeck, an AI agent framework, and resources from Andrej Karpathy.

This page discusses the findings of a Stanford study that reveals Claude, an AI, is significantly more likely to agree with users than a human would, even when the user is wrong. It also introduces a new skill that utilizes multiple agents to challenge this behavior.

This page features a post by Hanako on X, sharing a link to additional content. The post includes a brief message and directs users to the provided link for more information.

This page features a post by Mike Piccolo on X, sharing a link. The content may include thoughts, updates, or discussions relevant to his followers.

Nainsi Dwivedi shares a link on X, directing users to additional content. The page features a tweet that may contain valuable information or insights related to the shared link.

This page provides guidance on how to locate public reports, white papers, and PDFs from top consulting firms using Google. By downloading the first ten results, users can gather valuable material for creating a high-value offer.

Prajwal Tomar shares a link on X, directing users to additional content. This page highlights the shared link and its relevance to the audience.

This page features a tweet by Akshay, sharing a link. The content is likely related to the shared link, providing insights or information relevant to the audience.

This page discusses the author's fine-tuning stack for small language models ranging from 2B to 15B parameters. It includes details on the cost of dataset generation and the tools used in the process.

This page promotes a weekend activity focused on mastering AI model fine-tuning. It provides a prompt for Codex/ChatGPT/Claude/Grok to guide users from beginner to advanced concepts in LLM engineering.

This page discusses the realization that AI coding agents often spend more time searching codebases than understanding them. It introduces a local knowledge graph developed for various AI coding tools, aiming to improve efficiency.

Angelica Parente shares her experience of using Claude to enhance chart visualizations by integrating Tufte principles. She highlights how this approach led to simpler and more aesthetically pleasing graphics.

Prajwal Tomar shares a link on X, directing users to additional content. The post highlights an external resource that may be of interest to followers.

This page shares a comprehensive guide for running large language models (LLMs) locally, now accessible online for free. It covers various setups including laptops, edge devices, and different GPU configurations, making it suitable for a wide range of users and hardware.

Dragan Bajcic shares insights on optimizing workflow through effective planning skills. He discusses his implementation plan process and how it has evolved to enhance feasibility in achieving goals.

This page discusses the open sourcing of Marlin-2B, a small VLM designed to extract structured information from videos. It is finetuned to answer two key questions developers have about their videos: what is happening and when, positioning it as a competitive model in its class.

Qwen is calling for ambassadors! Whether you're a developer with great technical taste or a local community leader who loves bringing people together, we'd love to have you join us. Visit the website for more details and to apply.

Eric Lancheres shares a link on X, inviting engagement and discussion. The post encourages followers to explore the content linked in the tweet.

Andrej Karpathy discusses the significant impact of context on Claude's performance, stating that 90% of its mistakes arise from missing context rather than a weak model. He presents a comparative analysis of mistake rates with different rule sets, highlighting the importance of structured guidelines for coding.

This page discusses the impressive speed of new MTP models and recommends installing llama.cpp for optimal performance. The author shares their experience using it on dual 3090 GPUs.

Joe Barrow shares a link on X that likely leads to additional content or information. This post may engage followers and spark discussions.

Claude Code feels completely different once you install this. Anthropic quietly released an official plugin called claude-code-setup that transforms Claude Code from 'pretty good' into an actual AI development environment, scanning your project and recommending hooks.

This page discusses the author's experience running various models on different hardware setups, specifically a 3090, a 5090, and a 128GB DGX Spark. It highlights three models that are deemed worth building upon, with a focus on the StepFun Step-3.5 Flash model.

Michael Guo discusses the considerations for selecting a reliable setup for the 128GB MacBook Pro. He shares his recommended local coding stack, including Qwen 3.6 and MLX server, to ensure effective performance.

This page provides insights and tips on how to effectively prompt engagement on the social media platform X. It includes strategies and examples to enhance user interaction and communication.

This page discusses an open-sourced app that effectively replaces ElevenLabs and WisprFlow, operating entirely locally. It highlights features such as voice cloning from just 3 seconds of audio, integration of 7 TTS engines, and support for 23 languages including Arabic, Hindi, and Japanese.

This page discusses the importance of initial setup steps for those involved with agentic systems. It emphasizes that getting these foundational steps right is crucial for maintaining flow, more so than the choice of models or frameworks later on.

0xSero shares the impactful contributions made through donations, including the provision of hardware and educational support. The post highlights donations of RTX 3090s, a laptop to a student, and the teaching of classes to both Algerian students and followers on X.

This page discusses dense models in AI, specifically highlighting examples like Qwen3.6-27B and Gemma-4-31B. It explains the process of tokenization and parameter activation in these models, providing insights into their functionality.

This page discusses how two Australian brothers, Daniel and Michael Han, significantly improved AI training efficiency, achieving a 30x speed increase with a modest investment of $500K. It highlights Daniel's background as an NVIDIA engineer and their innovative work on algorithms like t-SNE and SVD.

This page discusses a simple and cost-free hack for improving Google Maps rankings by leveraging employee actions. It highlights how a quick visit to a competitor's location can influence the algorithm that determines visibility in the Map Pack.

Joey (@aijoey) shares a tool calling benchmark run on NVIDIA DGX Spark using the Qwen3.6 35B model with Q5_K_M quantization and llama.cpp with MTP-enabled speculative decoding.

Andrej Karpathy wrote something that every Claude Code user has felt but couldn't articulate. The post highlights three quotes that emphasize how models can make wrong assumptions and fail to manage confusion.

Joey shares an update about successfully running llama.cpp MTP on his DGX Spark. This significant development allows Spark owners to utilize MTP for predicting multiple tokens ahead using built-in heads, enhancing model performance.

NVIDIA has solved the biggest trade-off in LLMs, delivering a 6x speed boost without losing quality. This page discusses the implications of this advancement for AI models like GPT-4, Claude, and Gemini, which are currently autoregressive.

Cody Schneider shares an SEO & AI search dashboard he built in Claude Code, which connects to Google Analytics (GA4) and Google Search Console. This tool can be set up in just 5 minutes, and a Notion document is also provided for further guidance.

Supertonic is a text-to-speech model that operates entirely on your device, eliminating the need for cloud services, API keys, or per-character pricing. With 2,700 GitHub stars, it boasts impressive performance metrics, being 167 times faster than real-time on an M4 Pro and only requiring 66MB of space.

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This page features a post by Ronin on X, sharing a link for further exploration. The content is likely to engage users interested in the topic linked.

This page provides practical strategies for selling AI services even when you lack a following or network. It outlines seven actionable steps, including hosting local meetups to connect with potential clients.

This page discusses a solution to reduce wasted code generated by Claude, highlighting that 40% of the code is unnecessary and leads to costly rewrites. A tested 65-line markdown file has reportedly decreased mistake rates from 41% to as low as 3% across 30 codebases, with significant developer interest indicated by 120,000 stars.

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This page provides tips for fine-tuning open-source models, emphasizing the importance of starting with smaller models like 1B to 8B. It also recommends using WebGPU providers, specifically Google Colab Pro, for efficient model training.

Michael Guo shares a link on X, providing insights or commentary related to the content. The page serves as a platform for engagement and discussion around the shared link.

This page discusses the common feelings of curiosity and anxiety people experience when exploring local LLMs. It addresses questions about hardware requirements and terminology associated with local LLMs, helping users navigate their options.

This page offers information about remote job opportunities for night-shift roles that pay $100 per hour. It highlights companies that are currently hiring and emphasizes the rarity of these positions, which many people may overlook.

Corey Ganim outlines a service that starts at $999 and can generate $5,000 to $10,000. The process includes a discovery call and AI analysis to identify potential tools for clients.

This page details Thanh Pham's experience in increasing the performance of his GX10 (DGX Spark) from 23 tok/s to 79 tok/s on Qwen3.6-35B-A3B. It highlights the configuration changes, parameter adjustments, and firmware upgrades he implemented, along with insights gathered from NVIDIA forums.

This page discusses the findings of a 10-week study on local SEO, revealing that the Google Business Profile is struggling and many consultants are unaware. The study analyzed 420,000 AI query responses across 80 local business niches in 30 cities, contributing to the largest local AI citation dataset known.

This page discusses a coding prompt aimed at cleaning up unnecessary files in a project repository. It highlights the issue of random files being committed during development, which can clutter the project and hinder efficiency.

This page shares essential tips for optimizing local SEO, emphasizing nine key elements that can help rank web pages effectively. It highlights the importance of placing target keywords in specific areas of a webpage to improve search engine visibility.

This page discusses the importance of using Stripe and PayPal for payments and billing in SaaS businesses. It highlights user expectations for ease of use and the streamlined services these companies provide.

Alex shares insights on the best coding model for a MacBook Pro with 128GB M5max, recommending Qwen3.6-27B-UD-Q6_K_XL. This tweet provides a direct link for further exploration.

This page provides a straightforward guide for non-technical individuals and non-designers on how to create visually appealing content using AI. It addresses common issues with AI-generated designs and offers practical solutions.

Ahmad addresses the misconception that the DGX Spark or any Unified Memory machine competes meaningfully with GPUs. He urges for a balanced discussion on the pros and cons of each technology without spreading misinformation.

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Jeffrey Emanuel discusses the impact of his open-source dcg tool, which has been available for four months. Users have reported significant improvements in performance and safety from coding errors caused by Claude Code agents.