Notes from the lab: agents, sovereign infrastructure, data, visibility and PropTech.
Page 6 of 9 · 102 posts
Which GPU and hardware to choose for local LLMs in your company? Comparison of VRAM, memory bandwidth, models, and costs for self-hosted deployments in 2026.
Small AI model vs large LLM: when a specialized 7B outperforms a general GPT-4-class model, the cost difference, and how to choose correctly for your business.
MCP (Model Context Protocol) is an open standard for connecting AI models to external tools and data. How it works, what it offers businesses, and what security risks it entails.
Migrating from OpenAI API to your own AI model: when self-hosting LLM pays off, how the process works, and what to keep from your existing architecture.
Reasoning models excel at tough decisions—but they're slow, expensive, and empty when forced into simple tasks. When thinking pays off.
How to monitor an AI agent, which KPIs make business sense, and how to build a quality dashboard before deployment spirals out of control.
When Make and Zapier are enough, and when do you need a custom AI agent? Comparison of capabilities, costs, and limitations of no-code vs dedicated architecture.
Don’t start with the tool—start with the process. How to choose the first AI implementation that delivers measurable results and pays off in months, not promises.
Responsible AI innovation isn’t a values statement—it’s concrete design decisions: guardrails, human-in-the-loop, explainability, and AI Act compliance. How to implement it in your company.
AI agent memory in 2026: types of session and vector memory, context isolation between clients, retention, and the right to be forgotten under GDPR.
Concrete AI implementation plan for the first 30 days: from process audit through pilot to measurable results. No hype, just numbers.
The AI black box problem poses real legal and operational risks. How XAI, guardrails, and human oversight address it in production systems compliant with the AI Act.
Concrete takeaways on AI agents, sovereign infrastructure and visibility in AI models — no spam.
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