DevNeuroX Journal
Blog
Claude Mythos / Fable 5: what this model changes for AI agent security
Claude Mythos / Fable 5 scored 73% on expert cyber tasks. We examine 10,000+ vulnerabilities found and practical access rules for AI agents.
A founder's AI assistant: memory, tasks, and action control
A personal AI assistant connects project memory, Telegram, email, documents, and schedules. Learn how digests, permissions, and action control work.
AI agents for routine work: where a small team should start
An AI agent combines a model, tools, memory, and process rules. Learn how to choose a first workflow, limit permissions, approve actions, and control errors.
When a local AI model makes sense for business work
Gemma 3 shows which workflows can already run close to company data. We examine privacy, quantization, infrastructure costs, and hybrid deployment.
How to write prompts that produce useful results
A working prompt defines context, task, format, constraints, and quality criteria. Learn how to structure requests, iterate, and verify AI output.
How to work with AI models: choosing the tool and context
A practical guide to choosing an AI model, preparing useful context, and managing long chats, with examples from Gemini, Claude, and local models.
What people want from AI: lessons from 80,508 interviews
Anthropic's study shows that people want AI to support professional growth, reliable answers, and human control instead of replacing them outright.
AI agent memory: why vectors need graphs and PostgreSQL
Vectors retrieve similar fragments, graphs store relationships, and PostgreSQL keeps exact facts. Digital Shadow shows how hybrid AI-agent memory works.
Digital Shadow: an AI assistant for founder tasks and context
Digital Shadow connects a founder's projects, meetings, documents, and decisions. This article covers daily planning, reflection, memory, and context graphs.
RAG and vector databases: semantic search for business
RAG retrieves answers by meaning from PDFs, catalogs, and manuals. This guide covers the architecture, database choice, limits, and implementation mistakes.
Prompts, RAG, or LoRA: what should a business choose?
Prompts, RAG, and LoRA solve different problems. This guide shows when instructions are enough, when you need a knowledge base, and when tuning is justified.
Why AI without memory starts from zero every day
AI without memory makes teams repeat context. I added RAG and vector search to Digital Shadow so the agent retrieves projects, facts, and decisions by meaning.
Why I automated crypto trading instead of trading by hand
I built an AI crypto trading pet project for signals, risk, stops, and trade reviews. Its early win rate was 53%, which does not prove profitability.
Digital Shadow v1.0: personal AI memory for a founder
Digital Shadow keeps a founder's tasks, people, files, and decisions in one context. A Gartner survey found 47% of digital workers struggle to find data.