AI Systems
How to design AI agents that reduce operations without breaking your stack
Wasyra Lab
Copilots look good in demos. Useful agents survive handoffs, permissions, observability, and human fallback.
ArticleSeries
AI systems that actually reach production
A series on agents, copilots, and guardrails for bringing AI into real work without breaking trust or operations.
Posts in this series
AI Systems
Guardrails for B2B copilots: how to earn trust before automating
Wasyra AI Systems
A copilot is adopted only when the user understands what it knows, what it does not know, and when they should intervene.
ArticleAI Systems
Top 5 AI and product development news to watch now
Wasyra Lab
Five recent moves from OpenAI, GitHub, AWS, and Anthropic that change how teams design, build, and operate software.
ArticleAI Systems
MCP in production: the protocol standardizing your AI agents in 2026
Wasyra AI Systems
Model Context Protocol went from experiment to de-facto standard in twelve months. Why Gartner expects 40% of enterprise apps to use it by end of 2026.
ArticleStrategy
AI safety and EU AI Act 2026: why agent red teaming is no longer optional
Wasyra Lab
On August 2, 2026, the high-risk rules come into force. Fines of up to €35M or 7% of global revenue. What your agent needs to pass.
ArticleEngineering
LLM observability in 2026: why OpenTelemetry and evals must run together
Wasyra Engineering
Monitoring an LLM is not monitoring a microservice. Tokens, cost, variable latency, drift, and subjective quality. How to build the stack with OTel + GenAI semantic conventions + online evals.
Article