Who I Am
Deep AI technical expertise with an uncommon understanding of the disconnect between what's technically possible in AI and what actually gets adopted in the messy reality of enterprise organizations.
My journey has been about recognizing patterns early—from building a 50+ person data consultancy to exploring AI's frontiers. I've learned that every organization has its own unique fingerprint, and success comes from understanding their specific culture, constraints, and enabling the change-seekers to succeed.
Work Together
I partner with organizations through flexible fractional engagements—from hands-on technical leadership to strategic advisory. Whether you need someone to architect your AI initiatives, guide your team through the implementation maze, or serve as a thought partner who's actually built these systems, I bring real experience and know what works (and what doesn't) from actually building things myself, and never assuming I know everything.
Fractional CTO/Technical Leadership
Hands-on architecture, team mentorship, bridging the gap between vision and implementation
AI Strategy & Advisory
Navigate the landscape, avoid the pitfalls, build what actually works
Implementation Partnership
Roll up sleeves, build together, transfer knowledge, leave you stronger
Currently taking on select engagements with organizations trying to make sense of the AI landscape. I've spent way too much time exploring this space since early 2022 (my GitHub and LinkedIn tell that story), back when it felt like another tech fad. Now I help teams figure out what's worth paying attention to versus what's just noise. We'll work in whatever format makes sense (strategy sessions, vendor evaluation, hands-on building). The goal is always the same: focus on what actually works and help your team get stronger along the way.
Discuss an EngagementPattern Recognition
Built Aptitive
Founded Aptitive in 2013 and built it to a successful exit via acquisition. We helped mid-market enterprises turn data into business outcomes, learning that technology is just one piece—understanding people and processes matters more.
Spotted Snowflake Early
Partnered with Snowflake in 2015 when cloud data was just emerging. Started working with LLMs in early 2022, prior to ChatGPT launching and changing the global landscape.
Building & Researching
Always building, listening, and experimenting with new ways to help enable people with their own personalized command and control centers, applications, new untapped sources of data, and practical solutions that can be applied to real-world problems rather than just chasing hype.
Enabling Change-Seekers
But more importantly: enabling leaders to put these capabilities in the hands of domain experts who can actually use them, and feel confident in taking a risk to push ahead the change most organizations, teams, and individuals need.
What's Worth Paying Attention To
The Mishype
- Another chatbot for your website
- "AI will replace all developers"
- Fully autonomous anything
- Single LLM solving everything
Actually Working Now
- Code generation that speeds you up 3-5x
- Turning unstructured docs into structured data
- "Vibe solutioning" - domain experts building their own tools
- Synthetic data generation
What's Coming (Pay Attention)
- Personalized command & control centers
- On-device AI for real privacy
- Compound AI systems
- Golden era of custom apps
"The landscape shifts weekly; your strategy shouldn't."
The Journey
20+ Years in Data
Building and experimenting to understand what would actually deliver value. Now focused on the convergence of AI modalities and hybrid architectures—because that's where enterprises need to go.
Early Builder Across AI & LLM Landscape
Since the first Llama model came out, I've been hands-on helping organizations best leverage the technology for today and for the future. Through my open source projects, I've met some incredible people working at the frontier of the technology.
Understanding Where LLMs Work (And Where They Don't)
From Apple's MLX working on on-device inference, to exploring the intersection of AI and the creative industry via video and image generation. At an AI-driven search startup, I built LLM-driven pipelines that turn unstructured video content into queryable knowledge.
Compound AI Systems
What I've come to believe: focusing on a single LLM might be limiting. The organizations I've seen succeed are building compound AI systems, modular pieces of software working together. These tools can be incredibly powerful, but they have real limitations and don't come with manuals.
Take prompt injection: if you're not careful about untrusted inputs and external data entering your system, what seems like a helpful assistant can become a security risk. I'm not a security expert, but I've learned through the years how this unsolved problem can best be mitigated.
The Best Use Case for AI - A Golden Era of Personalized Applications
AI-driven coding ("vibe solutioning") opens the door to a golden era of custom applications - every knowledge worker should have their own command and control center—a personalized interface into compound AI systems that works the way they think.
We're watching new clouds being born with AI-native infrastructure, built for the AI era rather than awkwardly retrofitted as an afterthought.
The power of modern AI isn't another chatbot. It's enabling people across all levels of an organization to leverage untapped data previously trapped in unstructured documents, videos, slide decks, and conversations. It's about building personalized tools that understand context, automate the mundane, and amplify human capability.
Domain experts without coding experience can build their own tools that fit their very specific, niche needs. Organizations that understand this can escape stagnant platforms and build durable competitive advantages.
The future belongs to those who can enable their teams to take advantage of this paradigm shift by supporting, educating, and deploying the right capabilities across every level of the organization.
What I Focus On
I help organizations navigate the practical realities of AI implementation. That means understanding that enterprise AI success requires top-down executive permission combined with bottom-up domain expert execution. It means meeting organizations where they are, not where vendors think they should be. With how quickly the AI landscape changes, the best approach is to have a solid vision and thesis, while also staying flexible and open to exploring new ideas and technologies.
My approach is about listening and asking questions that help you build trust that I can help you achieve what's actually possible - direct, transparent, and collaborative - as a true partnership. The best solutions emerge from understanding each organization's specific reality, whether that's a tech startup trying to build a product, or an enterprise unable to leverage the best AI has to offer due to strict data privacy requirements.
Let's Connect
I'm always interested in conversations about what you're seeing in AI adoption, what's working, what's not. Happy to share perspectives on:
AI Implementation
- • Building personalized apps, interfaces, and command centers with AI
- • Building entirely new forms of pipelines for previously untapped data
- • Unraveling the mishype of AI and bridging the gap between possibilities and realities
Technical Strategy
- • Why we're in a golden era of custom developed applications
- • Hybrid approaches—local models for privacy, cloud for scale
- • Making retrieval and RAG work effectively
- • Where AI is heading beyond the current hype cycles
Based in Chicago, happy to meet up or jump on a call.
Builder and advisor • Chicago-based • Taking on select fractional engagements in 2025