Principal-level judgment for engineering teams shipping LLM and agentic systems.
I review your architecture and document the decisions your team needs to make.
Production patterns move through architecture reviews, PR feedback, and decision records.
Schemas, traces, evals, fallback paths, and cost models arrive before traffic.
Architecture choices, trade-offs, owners, and reversal costs, written down.
Add architecture judgment before the system becomes expensive to change.
I'm Igor Bobriakov, founder of ActiveWizards, a 10-year AI engineering studio. My advisory work comes from systems my team builds and maintains.
I lead advisory engagements; ActiveWizards provides engineering teams when implementation is needed.
I wrote Production-Ready AI Agents. Its Three Pillars — Observability, Reliability, Security — are the constraints I use when reviewing AI architectures.
I review schemas, state, evals, and code paths for silent failures: errors that pass tests but corrupt behavior, cost, or trust.
I connect architecture choices to staffing, roadmap pressure, vendor risk, and leadership funding decisions.
Advisory, embedded leadership, or a fixed-scope production audit. No long-term lock-in.
Prices are public so the first call can focus on fit, scope, and risk. These are specialist architecture engagements, not coaching packages or staff augmentation.
Your team is building. Principal review is missing.
You need AI architecture leadership inside the team's operating rhythm.
The system is stalled, fragile, expensive, or hard to explain.
2-5 AI engineers in Python, LangGraph, vector databases, and cloud infrastructure, deployed through ActiveWizards.
I own the architecture. The team builds against it. One review loop, one set of production constraints.
When AI work is moving from prototype to production, when architecture choices feel hard to reverse, or when leadership needs a written technical rationale before funding more work.
Architecture, state management, retrieval design, evals, schemas, API and MCP contracts, provider choices, observability, latency, cost, and the trade-offs your team has to operate.
I work inside the engineering loop: design reviews, PR feedback, vendor decisions, hiring screens, and decision records. I do not replace your engineering manager or product owner.
Igor reviews the submission for fit. If there is a match, the next step is a diagnostic call to map the system, name the riskiest decisions, and choose an audit, advisory, or build-team path.
Outline the system, current constraints, and decisions that need review.
Mutual NDA available before working sessions.