Consulting & Advisory

Most advisory pages promise “strategy” or “AI expertise.” What I offer is different.

I bring nearly two decades of quota-carrying enterprise sales, ecosystem and GTM design, and math-first AI architecture into a single operating view. I don't just help you ship a feature or a demo—I help you design systems: technical systems, revenue systems, and organizational systems that can't afford to fail in mysterious ways.

If you need an AI system you can explain and prove, a revenue engine that actually scales, or a way to align math, architecture, and GTM so they stop fighting each other, this is where I can help.

Who this is for:

Founders, CROs, and GTM leaders who need their sales organization, partners, and product to behave like one system—not a collection of silos and side deals.

What we do together:

• Design or repair your end-to-end GTM architecture (direct, partner, marketplace).
• Map your product into AWS/Azure/GCP and key ecosystem partners in a way sellers can actually use.
• Build an NTT-style cross-sell engine if you're multi-business-unit or multi-product.
• Create incentive models, service matrices, and internal playbooks so teams stop fighting the structure.
• Align product, sales, ops, and leadership around a single, coherent revenue system.

What you walk away with:

• A GTM and sales architecture your team can actually run, captured in a one-page architecture map.
• Organizational alignment instead of friction between sales, product, and partners, backed by clear rules of engagement.
• A proven pattern capable of generating 9-figure pipeline (as I did at NTT), adapted to your context.

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Who this is for:

Founders, CEOs, and execs building in AI or infrastructure who need someone who can think across tech + business + architecture + GTM.

What we do together:

• Pressure test your product and technical strategy
• Avoid costly early architecture mistakes
• Build the narrative that resonates with investors and customers
• Act as a fractional Chief Architect + Strategy Partner during critical phases

What you walk away with:

• Clarity captured in decision memos and alignment notes.
• Direction with explicit next steps, owners, and risks called out.
• A deeply senior thought partner who sees around corners.

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Who this is for:

Teams stuck in experimentation mode—trying prompts, patching behavior, chasing failures—instead of building systems that can be trusted.

What we do together:

• Train your team on the Mathematical Autopsy pipeline
• Idea → Math → Proof → Tests → Code
• Rebuild one critical component (memory, routing, scoring, agents) using MA
• Teach your team how to design AI systems with invariants, not intuition
• Leave behind a repeatable playbook they can apply anywhere

What you walk away with:

• A team that designs AI like scientists, not prompt jockeys.
• One fully re-architected component as a living reference implementation, with annotated code and tests.
• A repeatable, enforced pipeline: Idea → Math → Proof → Tests → Code, documented for your team.
• Less chaos, fewer "ghost" failures, and a shared language between research and engineering.

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Who this is for:

CTOs, VPs Engineering, Heads of AI, or Principal Architects who need an AI system that is explainable, stable, and provable—not a pile of wrappers, agents, and vibe-coded glue.

What we do together:

• Audit your current AI, LLM, memory, and orchestration stack.
• Identify structural fragility, hidden failure modes, and architectural debt.
• Redesign the system using math-first, field-based principles (RFS, VFE, MAIA, TAI).
• Define clear boundaries between memory, inference, intent, orchestration, and governance.
• Produce an architecture blueprint and migration path your team can actually execute.

What you walk away with:

• An AI system designed like a scientific instrument, not a prototype, with current vs. target architecture diagrams.
• Deterministic, explainable behavior grounded in clear guardrails and governance notes.
• A path from "it works sometimes" → "it works because we can explain and prove it," captured in a migration plan.

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Who this is for:

Companies building copilots, agents, or multi-model systems who need something better than "prompt → vector DB → LLM → pray."

What we do together:

• Redesign how your system handles memory (beyond naive vector stores).
• Define orchestration rules, agent coordination, and gating logic.
• Map out intent flow, state, feedback loops, and behavioral controls.
• Build the conceptual foundation for a cognitive OS inside your product.

What you walk away with:

• A more intelligent, predictable system.
• Behavior that can be logged, replayed, audited, and controlled, backed by a logging/replay approach.
• A roadmap to move beyond brittle agent chains into real orchestration, with clear next steps.
• A concrete, minimal starting point if you want to adopt RFS/TAI concepts without a full rebuild, including flow diagrams.

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