What is Wasyra's App in 1 Week service?

It's our express program that delivers a functional MVP in just 7 days. It includes strategy, UI/UX design, full-stack development with integrated AI and production deployment. Day 1-2: Strategy and Design. Day 3-5: Intensive Development. Day 6-7: Testing and Launch.

What artificial intelligence services does Wasyra offer?

We offer 14 AI services: autonomous agents, RAG & knowledge base, LLM fine-tuning, chatbots, computer vision, NLP, generative AI, MLOps, predictive models, recommendation systems, enterprise AI copilots, prompt engineering, AI safety and voice AI.

Does Wasyra offer staff augmentation?

Yes, we offer 10 talent models: individual staff augmentation, dedicated teams (Dev + QA + PM), team as a service, build-operate-transfer, nearshore for US/Canada, CTO as a service, tech recruitment, talent vetting, on-demand experts and managed services.

Where is Wasyra located?

Wasyra has presence in Lima, Peru and Los Angeles, US. We offer nearshore services for companies in the United States and Canada, with teams in a convenient time zone.

Governance, security, and complianceSeriesAI systems that actually reach production

AI safety and EU AI Act 2026: why agent red teaming is no longer optional

A practical guide for CTOs and CISOs: what the EU AI Act requires, how to red-team an agent with authority, and which evidence you must keep for audit.

AI SafetyEU AI ActRed TeamingCompliance

Wasyra Lab

AI systems and operations architecture

Published: April 17, 2026
min read: 9 min read
Categoría: Strategy

On this page

4 chapters

01August 2, 2026 changes the game in Europe
02The agentic problem: authority without traceability
03How to red-team an agent, not just a model
04What to close this quarter before the deadline

ago 2026EU AI Act deadline for high-risk systems

Chapter 01

August 2, 2026 changes the game in Europe

If your product operates in the EU or serves EU citizens, you have until August to bring high-risk systems into compliance. This isn't theoretical — the top fine is €35 million or 7% of global revenue.

The AI Act has been partially in force since 2024-2025. What goes live in August 2026 are the obligations for high-risk (HR) systems: inventory, impact assessments, transparency, human oversight, continuous risk management, and training-data traceability.

For B2B teams that translates to an operational question: if your product includes an agent making decisions that affect employees, candidates, patients, or consumers, it likely falls under high-risk. And that requires artifacts that take months to produce if you start late.

AI system inventory with risk classification and designated owner.
Impact assessments before each significant deployment (not annually).
Continuous logging through the full lifecycle, not just production.
Demonstrable human oversight mechanisms, with clear override criteria.

Source: European Commission, AI Act regulatory framework Source: Wilson Sonsini, 2026 AI Regulatory Year in Preview

Chapter 02

The agentic problem: authority without traceability

An agent takes real-world actions: opens a PR, sends a customer email, runs a transaction. If you can't reconstruct what it did, with what authority, on what data, and why, you're not ready for an audit — or for responding when something breaks.

Per-agent identity: each one with its own service principal, not a shared API key.
Minimum scopes: the support agent can't touch billing; the billing one can't touch infra.
Structured logs: input, tools invoked, output, human identity behind it, justification.
Operational kill-switch, not just a feature flag toggle.

Insurers are now issuing “AI Security Riders” that require documented red-teaming evidence before underwriting. If you don't have it, it's not only an EU concern.

Chapter 03

How to red-team an agent, not just a model

Classic red teaming evaluates the model. Agentic red teaming evaluates the full system: model plus tools, permissions, context, oversight mechanisms. That is where the serious risks show up.

Prompt injection from external data (PDF, email, RAG): does the agent follow an injected instruction?
Privilege escalation: can it combine tools to do something no single tool permits?
Exfiltration: can it send one customer's data to an unapproved destination?
Oversight resistance: does it disable or trick the human-in-the-loop under pressure?
Cross-session persistence: does the agent retain state it shouldn't?

Source: HackerOne, EU AI Security Standard Source: AI News, Agentic governance challenges under EU AI Act

Chapter 04

What to close this quarter before the deadline

Start with the systems likely to fall under high-risk. Document. Limit. Measure. And keep evidence. What lands in August isn't solved by a memo; it's solved by artifacts.

Versioned inventory: each agent with owner, purpose, data, model, scopes, review date.
Pre-release evaluation pipeline with security and impact tests.
Internal or contracted red team at least once before any expansion into high-risk.
Incident response plan specific to agents (rollback, comms, forensics).

Written by

Wasyra Lab

AI systems and operations architecture

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