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.
Review schemas, traces, evals, fallback paths and cost assumptions before launch.
Architecture choices, trade-offs, owners, and reversal costs, written down.
For founders, engineering leaders and enterprise AI teams with a decision to make.
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.
Read my approach to agent control flow and validation boundaries.
Resolve one consequential decision, or review recurring trade-offs with your team.
Prices in USD. Scope and start date agreed before work. Implementation is separate.
Before shipping, scaling or funding the next change.
Your team is building. Principal review is missing.
Need broader AI architecture leadership? Discuss your needs.
Illustrative format, not a client case or a promised finding.
2-5 AI engineers in Python, LangGraph, vector databases, and cloud infrastructure, deployed through ActiveWizards.
Build work is scoped separately with ActiveWizards. Architecture responsibility, delivery ownership and review cadence are agreed for that engagement.
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.
Your technical lead owns delivery. I review architecture, code and trade-offs, then document recommendations. We agree priorities within the engagement's scope. Implementation, ongoing operations and incident response are separate.
I review your submission for fit. If there is a match, we discuss the decision, available evidence and scope before agreeing a fee and start date. This form does not book paid work. A readiness review is not required before every advisory engagement.
Outline the system, current constraints, and decisions that need review.
Mutual NDA available before working sessions.