Ideas Weave Every Narrative with AI.
In 2010, millions of users opened their computers to a chilling ultimatum. Tencent, the maker of the ubiquitous QQ messaging app, forced users into a binary choice: keep our app, or keep the rival 360 security software. You cannot have…
Read More →/feed/json/wp-json/wp/v2/posts/sitemap.xml/feed/Cyberscript isn’t a better Lua—it’s a bet that developer frustration with quirks matters more than ecosystem depth. This article unpacks why most new scripting languages are really just pain relief tools, and what that means for your next project.
We’re heading toward a future where AI discovers new mathematics that no human can verify. Human intuition becomes irrelevant, and we become passive consumers of results we cannot question. This isn’t science fiction — it’s the silent revolution happening right now, and it will redefine expertise across every field.
US police departments are now producing true crime podcasts, framing them as transparency. But when the state controls the narrative—labeling the untried as ‘murderers,’ bypassing journalistic scrutiny, and leveraging audience trust—it’s not openness. It’s propaganda with better production value. Every episode becomes a closing argument before the trial begins.
In an AI startup, nobody tells you what to do. You survive by building information asymmetry, testing before analyzing, and treating your own career like an Agent architecture: define your profile, your skills, and your tools. These 10 lessons from my first week show how to turn chaos into influence.
DeepTutor isn’t just another AI chatbot. It’s an entire operating system for learning, designed to solve the one problem that no other AI tool has cracked: context continuity. But its ambition is a double-edged sword. The same complexity that makes it powerful makes it fragile. Is it worth the investment?
The biggest mistake in enterprise AI is treating LLMs as the brain of the system. They are the translator, not the decision-maker. Structured predictions need task-oriented models, deterministic constraints need rule engines, and complex relationships need knowledge graphs. Orchestration, not replacement, is the winning strategy.
AI coding speeds up implementation but also amplifies ambiguous requirements, turning unspoken assumptions into working features that must be torn down. The real bottleneck isn’t code—it’s clarity. Product managers must become intent maintainers, using SDD and TDD to create tight feedback loops that catch errors before they become expensive rework.
Belladonna of Sadness, a 1973 animated film of erotic horror and psychological collapse, survived through bootlegs and digital restoration. But today’s AI-driven content curation flattens its transgressive power into sterile data points. This article explores the tension between animation’s childhood coding and its capacity for radical shock, and warns that the very technology preserving the film is also erasing the human context needed to understand it.
Webhooks are a broken abstraction for data replication. They promise simplicity but deliver silent data loss and endless retry logic. The fix is simple: use cursor-based streaming instead. This article explains why every retry queue is a sign of a deeper design flaw, and how to build a truly reliable data replication system.
An AI-generated video about AI taking human jobs goes viral. The recursive irony is chilling: the very technology replacing us is now creating the content of our despair. We’re not just being replaced—we’re being forced to consume our own obsolescence, automated and packaged for engagement. This is the new normal.