AI

Spectre Mnemonic: Memory for Agents That Actually Forgets Correctly

The third article in the Spectre series introduces Spectre Mnemonic, an Elixir-first memory layer for agents with scoped recall, lifecycle governance, observations, mental models, and forgetting.

Spectre Lens: Giving Agents Eyes Without Handing Them the Whole Browser

The second article in the Spectre series introduces Spectre Lens, an Elixir-first browser perception layer that turns pages into agent-readable context.

I Wanted My Own Agent Library, So I Built One

The first article in the Spectre series introduces Spectre Kinetic, an Elixir-first planning layer for agents that lets models express intent while the runtime keeps control.

AI and the Open Web: The Dark Internet, the Dead Internet, and the Bot Problem

I think the public web is turning synthetic: bots flood content, trust drops, and humans retreat into private spaces. ClawBot shows how identity hijacks scale. Next platforms may chase proof of human, with privacy tradeoffs.

AI in Software Testing: The Promise, Pitfalls, and Pragmatic Use

AI offers speed and coverage in software testing but presents risks like hallucinations, bias, and security vulnerabilities. Effective use requires human oversi

Why Your Content Needs Generative Engine Optimization

The internet is shifting to an AI-first web. Generative Engine Optimization (GEO) is crucial for content to be visible and preferred by AI assistants, driving b

Reddit's AI Reckoning: Why Communities Are Banning Generative Content

Reddit communities are banning generative AI content due to declining quality, misinformation, and erosion of trust. This protects authenticity, expertise, and

The Illusion of Control: Edge vs. Cloud LLM Inference

An AI explains LLM inference on edge vs. cloud, detailing trade-offs, specific risks, and persistent AI flaws. It stresses human oversight and accountability.

Developer Jobs Marketing in 2026: How AI Changes Hiring, Pay, and What “Good” Means

AI makes software output cheap, but it makes trustworthy engineering more valuable. In 2026–2027 expect heavy AI-driven code churn and market noise;