Expertise
All Expertise Topics
Explore the full range of engineering expertise.
Agentic Architecture
System design for autonomous AI agents: orchestration, memory, tool use, evaluation, and production guardrails.
Software Engineering
Senior software engineering for teams that need a heavyweight contributor, not a delivery agency. 16+ years of production experience across backend, frontend, infrastructure, and AI-adjacent platform engineering.
Local LLM Deployment
Run open-source LLMs on your own hardware. Privacy, compliance, data sovereignty - no cloud dependency.
RAG Systems
Production RAG pipelines: chunking, embeddings, vector search, reranking, and evaluation.
MCP Servers
Production MCP servers built to spec: tool design, resource exposure, OAuth 2.1, Streamable HTTP, and the security boundaries enterprises actually pass.
AI Strategy & Roadmap
How senior teams build AI strategy: opportunity mapping, sequencing, ROI thresholds, board-ready artifacts, and the build-vs-buy decision.
AI Adoption Playbook
The change-management side of AI for mid-sized companies: rollout sequencing, team training, governance, and the cultural shifts behind real adoption.
AI ROI Measurement
Frameworks for measuring AI ROI that survive CFO review: baselines, attribution methods, total cost of ownership, payback periods, and the metrics finance teams actually accept.
AI Governance & Evaluation
Frameworks for governing and evaluating AI agents and LLM systems in production: NIST AI RMF, ISO 42001, EU AI Act, eval pipelines, drift detection, and oversight.
AI Cost Optimization
How to cut LLM and AI infrastructure spend by 50-85% without degrading quality: model routing, prompt caching, batch APIs, prompt compression, semantic caching, and the cost governance discipline most teams skip.
AI Team Scaling
How to build and scale an AI team from 2 to 20 engineers: roles, skills, hiring sequencing, organizational placement, and the patterns that actually ship.
Career Transition to AI Engineering
How experienced software engineers move into AI engineering in 2026: the real skill gap, the learning order that works, the portfolio projects that get interviews, the salary math, and what hiring managers screen for.
AI Team Workshops
AI team workshops that produce working code, not slide-deck literacy. Tailored curriculum, real codebase exercises, reference repositories the team owns after.
Corporate AI Training
Corporate AI training scoped by enterprise L&D: multi-team curriculum, role-specific tracks, governance focus, and the operational reality of AI at division scale.
Engineering Team Training
Deep, code-first AI training for a single engineering team working in their own codebase. Smaller class, deeper labs, working production patterns at the end.
Agentic AI Workshop
Focused workshop on agent orchestration, tool use, memory, and the durability patterns that keep agents stable in production. The team ships a working agent against their own data.
AI Strategy Consultant
Independent AI strategy work for executives: opportunity mapping, sequencing, board framing, and the decisions that determine whether AI spend pays back.
AI Implementation Consultant
AI implementation consulting that turns a strategy document into a sequenced delivery plan and gets the first wave of AI features into production.
AI Transformation Consultant
Multi-quarter AI transformation: operating model, governance, capability building, and the org design that decides whether AI sticks at enterprise scale.
AI Agent Builder
Hands-on AI agent builder for production-grade autonomous agents. Tool use, memory, multi-agent orchestration, evaluation, observability, and durability.
LLM Application Development
LLM application development for production. Claude, GPT, Gemini, open-source models. Prompt engineering, RAG, evaluation, observability, cost and latency control.
AI Automation Development
AI automation development for real business workflows. Process automation, decision automation, and human-in-the-loop systems delivered as working software, not advice.
Fractional CTO for AI Companies
Fractional CTO work specifically for AI-native companies: architecture, hiring, governance, and operating decisions in a fast-moving stack.
AI Leadership as a Service
Senior AI leadership delivered on a retainer: roadmap ownership, governance, hiring, vendor strategy, and the executive-level work that keeps AI honest. For CTOs and founders who need a fractional AI VP, not a consultant and not a full hire.
AI Engineer Coach
Coaching for engineers actively shipping AI features. Design reviews, decision sounding boards, code review on agent and LLM systems, and pattern transfer from a senior who has shipped it. For engineers paying for themselves and for managers funding the coaching for their AI teams.
Staff Engineer Coaching
Coaching for senior engineers preparing for the staff-to-principal jump. Scope, influence, organizational design, technical strategy, and the high-leverage work that defines the title. For ICs paying for themselves and for managers funding growth for senior engineers on their team.
AI Architecture Review
Focused senior review of your AI architecture. Surface the risks, name the trade-offs, and recommend the next moves before more is built on top.
AI Conference Speaker
AI conference speaker for keynotes, panels, fireside chats, and deep-dive technical talks. Topics across agentic systems, LLM engineering, AI strategy, and the engineering reality of shipping AI in production.
LLM Workshop
Hands-on LLM workshop for engineering teams. Prompting patterns, evaluation discipline, retrieval-augmented generation, fine-tuning, observability, and cost design. Built around your data and your stack.
LLM Consultant
Independent LLM consultant work: model selection, evaluation design, retrieval architecture, fine-tuning vs prompting decisions, and production reliability.
Machine Learning Consultant
Independent ML consulting: data pipelines, feature stores, labeling strategy, evaluation, MLOps, and the production engineering that keeps models honest.
Independent AI Advisor
Independent AI advisor work: senior counsel structured around your team, your data, and your runway, not a partner program or a hosting bill.
Chief AI Officer
Chief AI Officer role: dedicated executive leadership over the AI portfolio - model strategy, eval, safety, governance, and the boundary between AI and the rest of engineering.
Fractional Head of AI
Fractional Head of AI delivered on a monthly retainer: roadmap ownership, governance, hiring, and the executive-level work that keeps AI honest.
Part-Time CTO
Part-time CTO engagement: a senior technical leader who shows up two days a week, sets architecture and hiring direction, and gradually hands off to the team.
Software Engineer Mentor
One-to-one software engineer mentorship for working engineers. Backend craftsmanship, system design, code review, debugging, and career conversations from a senior who has shipped at scale. For developers paying for themselves and for managers funding mentorship for engineers on their team.
Tech Career Coach
Tech career coaching for engineers and engineering leaders navigating promotion, scope, role search, reorgs, and the senior-to-staff transition. For engineers paying out of pocket and for managers funding career development for high-potential team members.
AI Office Hours
AI office hours: a single focused hour with a senior AI practitioner. Bring stacked questions on evaluation, retrieval, agents, model selection, cost, and architecture. Get answers, not consulting theater.
Tech Advisor Call
A single-session tech advisor call for non-technical founders, marketers, and operators who need a translator for vendor proposals, candidate evaluation, and the technical decisions that shape their business.
Agentic AI Speaker
Agentic AI speaker for focused summits and conferences. Real architectures, real failure modes, real numbers from production agent systems. Keynote, deep-dive, fireside, hands-on workshop formats.
AI Evaluation Design
Designing AI evaluation frameworks that catch quality drift in production: rubrics, golden datasets, regression tests, LLM-as-judge, live sampling, and continuous evals.
LLM Model Selection
How to choose LLMs in 2026: capability tiers, cost curves, latency profiles, routing patterns, open vs hosted, and the criteria that actually matter at scale.
Prompt Engineering
Production prompt engineering: design patterns, structured outputs, prompt versioning, evaluation discipline, and the anti-patterns that hurt quality and cost.
LLM Fine-Tuning
When fine-tuning beats prompting and when it does not. LoRA, QLoRA, full fine-tuning, distillation, DPO, and the dataset work behind every option.
AI Product Management
Product management discipline applied to AI: probabilistic UX, evaluation as a product surface, model and infra constraints as roadmap inputs, and the PM role inside an AI engineering team.
AI Vendor Evaluation
Frameworks for evaluating AI vendors in 2026: lock-in risk, pricing exposure at 10x scale, integration depth, exit cost, compliance, and the questions sales decks never answer.