Independent advisory

Why

Teams often need a credible technical voice that bridges models, software, and governance — without a full-time hire before the mandate is clear.

Pain points

• Roadmaps packed with AI demos but thin on evals, cost, and operational ownership.
• Vendor and model choices made without a clear migration or exit strategy.
• Engineering and product misaligned on what “good” means for an intelligent feature.

Overview

A focused practice partnering with startups and product orgs on intelligent assistants, retrieval stacks, and agentic workflows — with emphasis on thin vertical slices, observability, and handoff so internal teams own what ships.

Architecture

Engagements typically start with outcomes and risk: user promise, failure modes, and compliance boundaries. Delivery is structured as milestones with shared dashboards for quality, latency, and cost — architecture documentation doubles as the handoff artifact.

What I did

• Lead discovery workshops with product, security, and platform stakeholders.
• Produce reference architectures and phased rollout plans tied to measurable signals.
• Embed with engineering for critical slices; coach on evals and incident response patterns.

Outcomes

• Clearer alignment between leadership and engineering on what to build first.
• Fewer science-fair prototypes; more paths to owned, operable systems.
• Documentation and runbooks that survive team changes.

Engagement-specific; references available under NDA.