I build AI systems that actually work in production.
Not demos. Not slide decks. Production-grade agentic workflows with deterministic gates, adversarial review loops, and structural enforcement.
Conductor
Orchestrates AI agent swarms to turn GitHub issues into merged PRs. Adversarial dual-AI review, portfolio orchestration, 81-89% token optimization, fail-closed phase gates. 100+ issues processed in production.
Full breakdown →Amara
Always-on AI assistant that monitors your channels, triages 90% of messages autonomously in under 200ms, and delegates to specialist agents. Digital chief of staff, not a chatbot.
Full breakdown →AI Knowledge Engine
Distills 176+ documents into structured knowledge, builds self-learning profiles from interaction data, and delivers real-time contextual guidance grounded in source material.
Full breakdown →AI Sales Pipeline
8-stage automated pipeline: company discovery, leadership identification, enrichment, priority scoring, and personalized outreach generation. Territory research in hours, not weeks.
Full breakdown →AI Patent Workflow
6-gate dual-AI patent pipeline with adversarial red-team review, automated Section 112 compliance validation, and filing-ready bundle generation. 2 patents drafted and filed.
Full breakdown →Claude PM Toolkit
PM intelligence layer for AI coding agents. 49 MCP tools, adversarial reviews, parallel development with worktree isolation, persistent memory, and Monte Carlo sprint forecasting.
Full breakdown →Multi-Agent Orchestration
Swarm architectures with specialized agents, phase gates, and fail-closed verification. Agents that plan, implement, and review with structural enforcement.
AI Process Engineering
Deterministic skill systems with mode detection, ledger-based convergence, and evidence-backed decision loops. Processes that scale without degrading.
Adversarial Review Pipelines
Automated code review with test-as-evidence methodology, pattern propagation, and mechanical write-scope verification. Quality gates that cannot be bypassed.
Workflow Automation
End-to-end AI-driven workflows: issue management, implementation planning, parallel development, patent drafting, and portfolio orchestration.
Building AI Systems That Learn: Self-Improving Profiles and Knowledge Bases
Most AI systems are stateless. Every conversation starts from zero. The most valuable AI systems get smarter with every interaction. The architecture behind document distillation, self-learning profiles, and knowledge bases that evolve.
Why Fully Autonomous AI Is a Trap
The AI industry is racing toward full autonomy. Remove the human. Ship faster. It sounds efficient. It's actually a trap. The organizations that win will design progressive autonomy with explicit trust levels, not black-box agents with no guardrails.
The Hidden Economics of AI at Scale
AI at prototype scale costs nothing. AI at production scale can cost more than your engineering team. Intelligent compression, model routing, two-tier retrieval, and the architecture patterns that control the bill.
From Chatbot to Control Plane: The Three Stages of Enterprise AI Maturity
Most companies think they're "doing AI" because they plugged in a chatbot. They're at Stage 1. There are three stages, and the gap between each is enormous. Here's what separates a chat wrapper from an autonomous control plane.
Adversarial Review: Why Your AI Needs a Second AI Checking Its Work
Single-AI review is the rubber stamp of the AI era. The adversarial review pattern (dual-AI pipelines with review ledgers, instance-verified severity, and seven review principles) is how you build AI output that deserves trust.
AI By Itself Isn't Enough: What Enterprises Actually Need to Make AI Work
The model is the easy part. Most enterprise AI fails because of missing systems architecture: structural enforcement, adversarial review, audit trails, and cost control. Here's what production AI actually looks like.
Privacy-First AI: Why Model Selection Is Your Most Important Architecture Decision
When you send your source code to a cloud API, you've made an architecture decision whether you meant to or not. A practical guide to the privacy spectrum, model routing, and building for optionality.
Hourly Consulting
Deliverables
- Architecture review of your current AI approach with written findings
- Technical feasibility assessments for proposed AI features
- Agentic workflow design sessions with system diagrams
- Code review of AI integration points with specific recommendations
- Tool and model selection guidance tailored to your stack
Weekly Embedded Advisory
Deliverables
- 20–30 hours/week of direct collaboration with your engineering team
- Production-ready agent architectures designed for your codebase
- Knowledge transfer through pairing, code review, and documentation
- Weekly progress reports with architecture decision records
- Runbooks and operational docs so your team owns the system after I leave
Project-Based Build
Deliverables
- Requirements workshop and system design document
- Production-deployed agentic workflow (multi-agent orchestration, gates, audit trails)
- Integration with your existing tools (GitHub, CI/CD, databases, APIs)
- Test suite with adversarial review coverage
- Operations manual, architecture docs, and 30-day post-launch support
Fractional Head of AI Engineering
Deliverables
- AI strategy and roadmap aligned with your business goals
- Architecture standards, review processes, and quality gates for all AI work
- Hiring support: interview design, technical screening, team structure planning
- Monthly executive briefings on AI capabilities, risks, and opportunities
- Hands-on technical leadership: design reviews, critical-path implementation, vendor evaluation
Discovery
Free 30-minute call. We identify what you need and whether I'm the right fit.
Scope
I define the system architecture, deliverables, timeline, and cost. No surprises.
Build
I design, implement, and test. You get visibility at every stage with working demos.
Ship
Production deployment with documentation, runbooks, and post-launch support.
Let's build something real.
Tell me what you're trying to automate. I'll tell you if AI is the right answer.
chris@swenor.us