Forward Deployed

adoption-and-scale

Help an enterprise put AI to work through broad fluency, role-specific practice, workflow redesign, and reusable methods. Use for enterprise chat, coding and workspace adoption, AI training, frontier-user programs, stalled use, and expansion across teams.

capability-exploration

Discover and test what current AI products, models, runtimes, and enterprise tools can accomplish on a meaningful task. Use for capability exploration, platform choices, buy/adapt/build decisions, proofs of concept, and finding a better way to deliver an AI workflow.

context-design

Design the information an AI workflow uses to investigate, create, and act. Use for enterprise knowledge, RAG and retrieval, tool results, long-running work, task memory, or failures caused by missing, misleading, or poorly organized context.

discovery

Discover how enterprise work could change with AI. Use for adoption discovery, operator research, capability exploration, workflow redesign and investigating why an AI pilot has stalled.

enterprise-engagement

Develop an enterprise AI adoption proposition, customer conversation or engagement. Use for opening decks, technical pursuits, adoption proposals, collaborative scoping and changes to an ongoing AI engagement.

enterprise-integration

Connect AI work to enterprise systems through meaningful business objects, usable tools, identity, and reliable actions. Use for integration design, MCP and API tool contracts, asynchronous operations, or diagnosis of a workflow that cannot complete its work.

evaluate-and-improve

Evaluate and improve enterprise AI on completed tasks, useful capability, and operating economics. Use for evals, experiments, bounded optimization, model or harness comparisons, release decisions, and diagnosis from agent traces.

executive-communication

Create an enterprise AI adoption deck, solution walkthrough, executive decision memo or technical narrative. Turn substantive work into a clear recommendation and a finished artifact the audience can use.

field-productization

Turn enterprise AI deployment learning into reusable skills, context, tools, evaluation sets, harness capabilities, or products. Use to choose what should travel across teams or customers and make the next deployment easier to deliver and maintain.

get-started

Advance an enterprise AI adoption or forward-deployed engineering (FDE) assignment and choose the relevant Forward Deployed skills. Use for work spanning customer discovery, AI opportunity and solution design, delivery, workforce adoption and value.

meeting-synthesis

Turn enterprise AI adoption meetings into useful findings, decisions and follow-through. Use for discovery synthesis, engagement readouts, use-case updates and changes to an AI solution or deployment plan.

opportunity-design

Develop enterprise AI opportunities and use cases that change how work gets done or create new services. Use to expand an automation request, discover work the organization could not previously afford, or turn a business ambition into a concrete first build.