FluidVoice Review: Free, Local, Open-Source Mac Dictation
FluidVoice runs speech models on-device: free, open source, macOS only. Setup, privacy trade-offs, how it compares to Wispr Flow, and where Windows stands.
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AI Tools This Week: NotebookLM Short Videos, Voice Agents, Agent Battles, and Mobile Coding
Andrew Warner and Corey Ganim break down 16 AI launches from The Next New Thing: NotebookLM Short Video Overviews, June, xAI Voice Agent Builder, BoringMarketing, open Slack agents, Arena42, Fable 5, Cursor iOS, OpenClaw mobile, Gemini Spark, Hermes context usage, and more.
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Robert Greene's AI Law: Make Yourself Hard to Replace
Robert Greene tells Calum Johnson that AI changes the tools, but not the power game. Here is the practical JQ AI SYSTEMS version: create dependence, build rare judgment, use AI as leverage, and stay useful when work gets automated.
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How to Get People to Pay You With No Audience: The Post For Me Playbook
Chris Koerner interviews Caleb Panza on how Post For Me crossed $10K MRR with no big audience: transparent MRR updates, customer-question SEO, AI-search visibility, pricing, churn, and the lean SaaS stack behind it.
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GLM-5.2 at Home: What 0xSero's Local Inference Bet Teaches Builders
David Ondrej interviews 0xSero about GLM-5.2, custom compression, LM Studio, rented GPUs, local tokens, and why open-weight models need better distribution and tooling.
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Cloud GPU vs Home AI Hardware: When Local Models Stop Bleeding Money
A practical comparison of cloud GPUs, hosted AI APIs, and home AI hardware for local models: cost, privacy, latency, maintenance, electricity, and when a hybrid setup wins.
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The Best Hardware for Local AI Models: Mac, Windows, Ollama, GLM, Qwen, Llama, and Agent Boxes
A practical local AI hardware guide with prices and buy links for Ollama, LM Studio, Qwen, Gemma, Llama, DeepSeek, GLM, Mac mini, Mac Studio, RTX PCs, DGX Spark, and cloud GPUs.
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Learn AI Is Bad Advice. Build This Skill Stack Instead.
Greg Isenberg argues that "learn AI" is too vague. The durable move is to build a skill stack: agents and local models, distribution, robotics, curation, builder-distribution, and real-world community.
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7 Hermes Agent Use Cases That Actually Work
Seven Hermes Agent use cases that hold up in practice: computer control, competitor research, memory, Linear and Notion handoffs, Slack, crons, and skills.
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How Shashank Runs a $100K AI-Agent Business With OpenClaw
Shashank Agarwal showed Andrew Warner how API.market runs with OpenClaw agents for PR, LinkedIn, seller outreach, finance, hiring, and chief-of-staff work. Here is the practical agent operating system behind it.
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Sakana Fugu Ultra Explained: The Multi-Agent Model That Routes Other Models
Sakana Fugu and Fugu Ultra are not normal frontier models. They orchestrate multiple models through one API. Here is how they work, what the benchmarks mean, what it costs, and when builders should try it.
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AI Makes Building Easier. Distribution Still Decides Who Wins
Andrew Warner and Hiten Shah reviewed real AI businesses making money. The lesson is clear: AI makes products easier to build, but distribution, margins, churn, and deployment still decide who wins.
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Local AI Models Are the Generator in the Garage
The Fable 5 access pause is a reminder that cloud AI is rented intelligence. Local models give builders a private, offline, resilient fallback layer for everyday work.
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Hermes Agent Desktop: What to Configure, What to Ignore
Which Hermes Desktop surfaces actually matter, why profiles are not security sandboxes, and what to get right before you schedule anything. Judgment, not docs.
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The Deployment Gap: 3 One-Person AI Businesses That Are Actually Plausible
A practical JQ AI SYSTEMS breakdown of three one-person AI business ideas: Microsoft Copilot training, paid AI communities, and vibe coding agencies built around the deployment gap.
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AI Plugins Are Becoming the New Workflow Layer
AI plugins, MCP tools, and work plugins are becoming the workflow layer around AI agents. Here is how businesses should think about permissions, tools, review, and rollout.
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The AI Rollout Bottleneck Is Not the Model. It Is the Services Layer.
AI deployment services are becoming the missing layer between model access and real business impact: workflow mapping, data, tools, controls, training, and implementation.
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AI Deployment Is Becoming the Real Model Race
AI deployment is where AI starts becoming useful: choosing repeatable workflows, connecting models to data and tools, adding controls, and getting teams to use the system.
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Run Hermes Agent Safely on a Rented VM: Docker, Hetzner, Risks
Hermes Agent is powerful, but running an autonomous AI agent on a remote server raises real questions about safety, isolation, and cost. Here is exactly how I am setting mine up on a Hetzner CPX22, what Docker does to contain it, and what risks remain.
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Hermes Agent + ChatGPT 5.5: My Next AI Employee Runs on This Stack
Hermes Agent with ChatGPT 5.5 as its brain: an open-source agent that builds its own skills, schedules tasks, and runs unattended. Why I am adopting the stack.
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GPT Image 2 Is Here: What Changed, What It Costs, and What Builders Should Know
OpenAI launched GPT Image 2 on 21 April 2026. 99% text accuracy, native reasoning, up to 4K resolution, and full API access. Here is what actually changed, what it costs, and what it means if you build with AI.
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What Is Prompt Engineering? A Working Definition for 2026
A clear, practical definition of prompt engineering in 2026: what it is, what it is not, and what good prompt engineering looks like compared to writing a clever prompt.
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What Is an AI Agent? Definition, Examples and How They Differ from Chatbots
A clear, practical definition of AI agents in 2026: what they are, how they differ from chatbots and traditional automation, and what they look like in real production systems.
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What Is AI Workflow Automation? Definition, Examples and How It Differs from RPA
A clear definition of AI workflow automation in 2026: what it is, how it differs from traditional workflow automation and RPA, and what it actually replaces inside a business.
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