Forward-deployed AI skills
Develop valuable AI use cases and carry them from customer discovery into design, engineering delivery and adoption. Forward Deployed provides 16 skills for FDEs, deployment leads, consultants and builders, covering workflow redesign, solution architecture, enterprise integration, context engineering, evaluation, engineering handoffs and value measurement. More
MCP connector Server URL https://forward-deployed.unsol.dev/connect/mcpCopy Login OAuth Tools Reads data10 export_ fetch get_ get_ list_ observe_ open_ prepare_ search search_
Changes data15 act_ add_ create_ define_ define_ experiment_ finish_ fork_ plan_ propose_ review_ review_ save_ shape_ start_
Skills 16 in the ChatGPT listing
Adoption and scale Help an enterprise put AI to work through broad fluency, role-specific practice, workflow redesign, and reusable methods. Capability exploration Discover and test what current AI products, models, runtimes, and enterprise tools can accomplish on a meaningful task. Context design Design the information an AI workflow uses to investigate, create, and act. discovery Discover how enterprise work could change with AI. Enterprise engagement Develop an enterprise AI adoption proposition, customer conversation or engagement. Enterprise integration Connect AI work to enterprise systems through meaningful business objects, usable tools, identity, and reliable actions. Evaluate and improve Evaluate and improve enterprise AI on completed tasks, useful capability, and operating economics. Executive communication Create an enterprise AI adoption deck, solution walkthrough, executive decision memo or technical narrative. Field productization Turn enterprise AI deployment learning into reusable skills, context, tools, evaluation sets, harness capabilities, or products. Get started Advance an enterprise AI adoption or forward-deployment assignment and choose the relevant Forward Deployed skills. Meeting synthesis Turn enterprise AI adoption meetings into useful findings, decisions and follow-through. Opportunity design Develop enterprise AI opportunities that change how work gets done or create new services. Solution design Design an enterprise AI workflow from user experience through reasoning, context, tools, state, and operation. Technical delivery Deliver an enterprise AI capability from a working slice to operation and team ownership. Use case portfolio Choose and sequence enterprise AI investments across integrated workflows, reusable capabilities, and employee practice. Value case Build and test the economic case for an enterprise AI investment or service. 