---
title: Offers
description: AI adoption for engineering and product organizations - with technical implementation and delivery leadership as supporting capabilities.
image: "https://wavepillars.com/og-image.jpg"
url: "https://wavepillars.com/offers/"
---

# Offers

Offers I serve. AI adoption for engineering and product organizations - with technical implementation and delivery leadership as supporting capabilities.

## Engagements

Clear first steps with duration and deliverable up front.

- [AI Adoption Diagnostic](/offers/#ai-adoption-diagnostic) - Current-state assessment, blockers, maturity score, and roadmap (2 - 3 weeks)
- [AI Workflow Pilot](/offers/#ai-workflow-pilot) - Use cases, workflows, enablement, and measurement for 1 - 2 teams (8 - 12 weeks)
- [AI Adoption Management](/offers/#ai-adoption-operating-model) - Governance, champions, metrics, and scaling (3 - 12 months)

Discuss via [/contact/#message](/contact/#message). Comparison of what each package includes is on [/offers/#engagements](/offers/#engagements).

## AI Adoption & Transformation

Core offer. AI adoption and organizational change so tools and licenses turn into durable capability - people, processes, governance, and measurement, not one-off demos or slide decks.

**Technologies:** AI Governance, Change management, Adoption playbooks, Enablement, Productivity metrics, Operating cadence

**Use cases:**

- Production AI adoption programs from pilot to scaled use
- AI governance: policies, risk reviews, guardrails, and an operating cadence stakeholders can defend
- AI team adoption processes: playbooks, training, pairing, and maturity rituals
- Measurement of productivity and workflow outcomes tied to AI usage
- AI transformation for eng and product orgs that already have tools but lack measured adoption

## Technical Implementation

Supporting capability. Production AI systems an adoption program needs - agents, copilots, RAG, and MCP integrations where they create leverage - so teams can run, measure, and scale what they adopt.

**Technologies:** OpenAI, Anthropic, MCP, Python, LLM, RAG, .NET, Azure, Next.js, REST API, SQL, Docker, GitHub Actions

**Use cases:**

- Hands-on delivery of production AI systems - agents, copilots, MCP integrations, and RAG
- Custom solutions that unblock adoption workflows your team can operate
- Full-cycle build: backend, API, frontend, and deployment when the program requires it
- CI/CD and launch readiness for production systems
- MCP and LLM integrations into CRM, ERP, and internal workflows

## Delivery Leadership

Supporting capability. Delivery leadership so AI adoption programs execute - planning, unblocking, product-engineering alignment, and the rhythm that turns pilots into predictable scaled use.

**Technologies:** Team leadership, Sprint planning, Backlog refinement, Release coordination, Product alignment, Roadmap planning, Program governance, Stakeholder communication

**Use cases:**

- Fractional delivery lead inside an AI adoption program
- Embedded leadership when adoption stalls on execution, not tooling
- Product-engineering alignment during critical adoption phases
- Sprint planning, release coordination, and stakeholder updates
- Delivery roadmap and milestone planning for adoption workstreams
- Program governance and review cadence
- Metrics, reporting, and stakeholder visibility

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