Workflow Integration and Solution Design

Knowledge of

• Using Claude itself as a thinking partner to clarify requirements: restating a fuzzy ask, listing stakeholders and constraints, surfacing edge cases, and drafting acceptance criteria
• The AI Fluency ideas of Delegation (deciding what to hand to Claude) and Description (framing the work clearly) as the frame for this clarification step
• The traits of a good use-case fit: language- or knowledge-heavy work, output that can be reviewed and verified by a human, and value in speed/consistency/first drafts rather than a guaranteed-correct final answer
• Poor fits: tasks needing guaranteed factual precision without review, or requiring capabilities outside Claude's scope
• That not every step of a process needs to be automated -- the goal is augmenting the steps where Claude adds the most value

Skills in

• Using Claude to restate a fuzzy request, list stakeholders/constraints, surface edge cases, and draft acceptance criteria before starting work
• Applying the Delegation and Description AI Fluency concepts to decide what to hand to Claude and how to frame it
• Judging whether a task's output can be reviewed and verified by a human before treating it as Claude-ready
• Distinguishing good-fit tasks (language/knowledge-heavy, reviewable) from poor-fit tasks (guaranteed precision without review, out-of-scope capability)
• Choosing to augment specific high-value steps of a process rather than defaulting to automating everything

Knowledge of

• Research as gathering and synthesizing information, comparing options, and summarizing long material, always paired with verification for factual claims
• Planning as turning a goal into an ordered plan: drafting project outlines, timelines, and checklists, and stress-testing assumptions
• Process optimization as mapping an existing workflow, identifying bottlenecks and repetitive steps, and proposing where Claude or automation can streamline it
• That the goal across all three is compressing the time from question to a reviewable draft or plan, not replacing judgment

Skills in

• Using Claude to gather, compare, and summarize information while pairing factual claims with verification
• Using Claude to turn a fuzzy goal into an ordered plan, outline, timeline, or checklist, and to stress-test assumptions
• Mapping an existing workflow before proposing where Claude or automation can streamline it
• Treating Claude's research and planning output as a reviewable starting draft rather than final truth

Knowledge of

• The Building Effective AI Agents guidance to prefer the simplest approach that solves the problem, even for non-developers -- many tasks are handled well by a single well-structured prompt or a short chain
• The iterative design loop: propose an approach, review it against needs, refine, and re-check
• Using Claude as a design collaborator by asking it to compare options and list tradeoffs, or to poke holes in a plan, while the human keeps decision authority

Skills in

• Choosing a well-structured single prompt or short chain over an elaborate multi-step system when the simpler option solves the problem
• Running a propose-review-refine-recheck loop with Claude instead of accepting a first draft
• Asking Claude to compare options, list tradeoffs, or poke holes in a plan while retaining decision authority

Knowledge of

• Augmenting a step (Claude drafts, a human edits and approves) versus redesigning the workflow around new capability (e.g., a Project standardizing client updates)
• Claude Cowork as a tool for running multi-step work on real files and projects, which is how day-to-day workflows get reshaped
• Standardizing repeated work in a Project so a whole team benefits from the same instructions and knowledge
• Keeping the workflow observable and reviewable so quality stays under control
• That incremental augmentation is usually safer and easier to validate than a wholesale redesign, and that removing all human checkpoints is where quality/governance risk creeps in

Skills in

• Deciding whether a given integration should augment a step or redesign the workflow around Claude
• Recognizing when to standardize repeated team work in a Project rather than leaving it to ad hoc individual prompting
• Using tools like Claude Cowork for multi-step work across real files and projects
• Designing integrations that stay observable and reviewable, keeping human checkpoints where quality or risk matters
• Preferring incremental augmentation over wholesale workflow rebuilds

Knowledge of

• Value: where Claude saves time, improves consistency, and enables new capacity
• Limitations: hallucination risk, the need for verification, context limits, data-sensitivity constraints, and the need for human review of high-stakes output
• That setting realistic expectations prevents both over-trust (shipping unverified output) and under-use (ignoring genuine gains)
• The connection between honest stakeholder communication and responsible adoption (Domain 6)

Skills in

• Articulating concretely where Claude saves time, improves consistency, or enables new capacity for a given audience
• Articulating Claude's limitations -- hallucination risk, verification needs, context limits, data sensitivity, human review for high-stakes output -- without downplaying them
• Balancing value and limitations in the same conversation so stakeholders neither over-trust nor under-use Claude
• Framing stakeholder communication as part of responsible adoption rather than a sales pitch or a disclaimer