Make your engineers
AI-native
Most companies are either moving too fast on AI hype or too slow on real adoption. I help engineering organizations close that gap — through training, agentic workflow design, and AI-powered data tooling that actually moves the needle.
Turn your team into AI practitioners
The biggest AI bottleneck isn't tools — it's adoption. I work directly with engineering teams to shift habits, build capability, and make AI-assisted development the default, not the exception.
Training & Seminars
Hands-on AI training programs designed for engineers, not marketers. Practical, tool-specific, immediately applicable.
- LLM fundamentals for software engineers
- AI-assisted coding workflows (Cursor, Copilot, Claude Code)
- Prompt engineering for developers
- Agentic tooling deep-dives
AI Adoption & Process Design
Embedding AI into engineering workflows where it creates leverage — not as a gimmick, but as a multiplier on existing skill.
- AI-augmented PR review and release pipelines
- Code generation standards and guardrails
- AI tooling evaluation and integration
- Velocity tracking before and after
Slow Adoption Recovery
When AI rollouts stall — often cultural, not technical — I diagnose the friction and fix it without mandates or top-down pressure.
- Adoption audit across the team
- Bottleneck identification (tool fit, trust, workflow gaps)
- Change management strategy
- Champion identification and peer-led rollout
Solve problems automation never could
Traditional automation breaks the moment inputs get messy or outputs get varied. AI agents don't. I design two complementary architectures that together let you handle unstructured complexity at both ends of your system.
Taming unstructured input
A convergence stack uses AI to interpret diverse, natural-language input and map it to your internal systems and structured data. The result: a "big diverse incoming signal" gets normalized into exactly what your downstream processes expect — without custom parsers for every variation.
- Intake processing (email, forms, requests)
- Entity extraction & schema mapping
- Intent classification without training data
- CRM, ERP, and ticketing system integration
Acting across diverse external systems
A divergence stack sends a single internal intent outward and adapts it to whatever the external system requires. Rather than building point-to-point integrations for each target, an AI agent interprets the goal and executes it appropriately — negotiating format, protocol, and interaction style on the fly.
- Multi-system task orchestration
- Partner & vendor communication automation
- Adaptive API interaction without rigid contracts
- Workflow automation across fragmented toolchains
Give every specialist a personal developer
Your analytics team shouldn't need to file a ticket every time they need a new data cut. Your operations team shouldn't be blocked on engineering to automate their workflows. AI-native data engineering changes that equation.
The shift: from data platforms to AI-generated code
Instead of routing all data requests through engineering, we give specialists — analysts, ops leads, product managers — access to code-like environments where AI generates exactly the data engineering they need. They describe what they want. The AI writes and runs it. Results are immediate.
Specialist Tooling Setup
Design and deploy AI-native environments for non-engineering teams — purpose-built for their actual workflows and data sources.
Engineering Capacity Audit
Identify where engineering time is consumed by specialist requests that AI could handle — and quantify the savings.
Guardrails & Governance
Data access controls, output validation, and audit trails so AI-generated queries stay safe and compliant.
Built for organizations that are serious about AI
Founders with AI FOMO
You know AI matters. You're not sure what to actually do. I cut through the noise and show you what moves the needle at your company's stage.
Engineering leaders with slow adoption
You've given your team access to AI tools. Usage is low. I find the friction, fix it, and get your team actually using AI as a lever.
Companies drowning in integration complexity
You have too many external systems, too many edge cases, and automation that keeps breaking. Agentic solutions handle what rule-based systems can't.
Data-heavy operations teams
Your analysts and ops leads are bottlenecked on engineering for every data question. AI-native tooling breaks that dependency.
Start With a Conversation
Every engagement starts with a free 30-minute call. We'll look at where your organization actually is with AI, and what would move the needle most. No pitch, no pressure.