Follow one real job or decision.
We look at what arrives, what changes, where people lose time, and which choices still need judgment.
Practical AI consulting · Roanoke, Virginia
Make the right AI decision before you spend.
I help leaders and small teams work out where an agent can help, whether their information is ready, which model or vendor makes sense, and what to test before committing further.
Bring one recurring job, a model or privacy question, or a proposal you need to evaluate.
Before selecting a toolDecision desk
Questions worth answering
What keeps slowing down? WORK
What information can we trust? DATA
What must stay private or human? LIMITS
compare what can actually work
Useful result
Your next moveA practical recommendation backed by evidence.
Sometimes the right answer is no new system.
Find your starting point
Where do you need help?
Choose the closest starting point. We can narrow the question together.
If a cleaner process, a checklist, or software you already own solves it, that should be the recommendation.
How I work
Start with the work. Test before committing.
We use a real example—not a polished vendor demo—to see what the problem actually requires.
See what can actually work.
We compare your current tools with simpler process changes, available products, vendors, models, or a focused build.
Test the smallest useful next move.
You leave with evidence, a named owner, and a clear next step—not a larger commitment built on assumptions.
See how I build
Watch an agent work through what changed.
Try three invented situations involving a request to revise a quote, a field measurement, and conflicting client feedback. Watch the agent gather what changed, update one current record, handle agreed follow-up, and stop when someone needs to decide.
Try the interactive demoServices
What I can help you do.
Start with the need, not a service label. These areas often overlap, and we can open each one for practical examples.
Operations & agent implementation
Build an agent around a recurring job, with clear access, memory, tools, and places where a person still decides.
Data & knowledge foundations
Make scattered documents, records, and operating knowledge easier to find, trust, and maintain.
Technical AI systems
Choose and test the model and deployment setup that the task actually requires.
Product & vendor advisory
Turn a product or vendor decision into requirements, representative tests, and visible tradeoffs.
Workshops, coaching & team enablement
Help leaders and teams understand agents, evaluate options, or complete a useful first build.
Operations & agent implementation
Build an agent around the work that keeps coming back.
A useful agent has a defined job: gather approved context, prepare work, use the right tools, and stop when a person needs to decide.
How I can help
- Follow one representative job from arrival through completion and identify the smallest useful agent role.
- Design what it may access, which tools it may use, what it remembers, when it calls a specialist, and how it recovers from failure.
- Build and test an operations partner, executive-assistant agent, or job-specific agent against representative work.
- Define ownership, retained human decisions, operating measures, and a practical rollout plan.
Illustrative business uses
Executive work desk
Gather meeting and correspondence context, track commitments, prepare follow-ups, and organize daily priorities for an owner or principal.
Client or project operations
Keep notes, revisions, approvals, deadlines, and next actions in one current record and prepare the next update.
Quotes, jobs, and field changes
Compare drawings, measurements, customer changes, supplier notes, and due dates before estimating, fabrication, or scheduling moves.
You keep deciding: priorities, relationships, strategy, price, quality, safety, schedule, and every consequential promise.
Talk through your work
Start with one recurring job, not a platform shopping list.
Data & knowledge foundations
Make business knowledge usable and current.
When documents, records, and operating knowledge conflict or go stale, people—and agents—repeat the confusion. We make the current answer easier to find, trace, and maintain.
How I can help
- Inventory and aggregate approved documents, notes, records, databases, and system context.
- Clean, normalize, deduplicate, label, and structure information around the work people need to perform.
- Design clear names, labels, source history, ownership, permissions, and update rules.
- Build or improve shared knowledge systems and search that return current, traceable answers.
Illustrative business uses
Client and project history
Bring agreements, notes, decisions, revisions, and deliverables into a maintained context source for service teams and agents.
Policies and operating know-how
Turn scattered procedures and expert knowledge into answers that cite the current source and expose uncertainty.
Product and technical knowledge
Organize specifications, support history, release notes, and documentation so teams can find the right detail faster.
You keep deciding: which sources are authoritative, who may access them, how long information is retained, and how policy or professional judgment is applied.
Discuss your knowledge problem
We can start with one question people repeatedly struggle to answer.
Technical AI systems
Choose the model and deployment that the work requires.
Fine-tuning, access to current information, local models, and hosted services solve different problems. I compare them against your task, privacy needs, quality bar, speed, operating cost, and ability to maintain the system.
How I can help
- Build task-specific evaluations and compare language, vision, audio, embedding, and tool-use models.
- Test whether better instructions, access to current information, fine-tuning, or a combination produces the strongest result.
- Design local or offline model use and self-hosted cloud models for privacy-focused environments.
- Plan how data moves, who has access, what gets logged and retained, how models are routed, and which APIs, containers, or applications support the system.
Illustrative business uses
Private internal agent
Keep model endpoints and business context inside infrastructure the organization controls rather than a general shared consumer service.
Specialized model behavior
Test whether fine-tuning improves a repeated classification, extraction, tone, terminology, or structured-output task beyond better instructions or access to current information.
Offline or field use
Run a smaller model where connectivity is limited and define what synchronizes when the device or site reconnects.
You keep deciding: acceptable privacy and security risk, quality thresholds, infrastructure ownership, budget, and the maintenance your team can support.
Review your technical options
Bring the task, data sensitivity, and deployment constraints.
Business, product & vendor advisory
Compare the options before a contract sets the direction.
I turn the work you need done into requirements and representative tests, then compare vendors and internal options against the same evidence.
How I can help
- Define the use case, approved data, required integrations, retained human decisions, constraints, and measurable success.
- Create vendor shortlists, scorecards, demonstrations, reference questions, and focused pilot plans.
- Compare build, buy, fine-tune, self-host, and mixed approaches across capability, cost, deployment, lock-in, and maintenance.
- Prepare negotiation and procurement questions covering service levels, data terms, pricing assumptions, support, portability, and exit.
Illustrative business uses
Vendor selection or renewal
Compare products against representative tasks before signing, expanding, or renewing a platform commitment.
Agent pilot design
Choose one defined job, agree on what success means, and gather evidence before a wider rollout.
AI product strategy
Clarify the user’s work, model and data requirements, product boundaries, costs, revenue model, and a practical order of work.
You keep deciding: the commercial commitment, contract and legal terms, security acceptance, procurement authority, product direction, and final vendor choice.
Prepare your decision
Bring the products, proposal, renewal, or build question you are weighing.
Workshops, coaching & team enablement
Help people understand agents by working with one.
Sessions move from what agents are and how they work to the practical choices behind context, tools, memory, models, vendors, deployment, and a focused pilot.
How I can help
- Deliver product-independent executive talks on agent capabilities, limits, types, vendor choices, and pilot design.
- Run hands-on agent workshops, Operations Agent Build Days, and team bootcamps around recognizable work.
- Teach context, instructions, tools, memory, how multiple agents work together, evaluation, fine-tuning, and deployment choices.
- Coach individuals or teams through a first build, private-model question, vendor comparison, or rollout plan.
Illustrative formats
Leadership briefing
A clear introduction to agents, product options, risks, deployment choices, and what a useful pilot should prove.
Team build session
Follow one real job, build the part an agent can prepare, test it together, and leave ownership and next actions clear.
Technical workshop or coaching
Go deeper on agent construction, how agents work together, business data and search, model strategy, private model use, or vendor evaluation.
You keep deciding: team policy, budget, how quickly the team moves, production readiness, and which jobs or technical paths deserve further investment.
Plan a session
Start with the audience, the decision or job, and what people should leave able to do.
Ways to work together
Choose the format that fits the question.
Some questions need a working build. Others need a focused review or a room of people to get on the same page.
01 / Team buildFlagship
Operations Agent Build Day
For a small team ready to build and test one internal operations agent around recurring work.
- 01Short discovery using a real work sample.
- 02Focused in-person build with the people who know the job.
- 03Working first version, named owner, approval points, and rollout plan.
- 04Follow-up to review use, corrections, and blockers.
Also available one-to-one
Talk through one taskFocused implementation for an owner, executive, principal, or independent professional with one agent use in mind.
02 / Information readiness
Data & knowledge readiness
For teams dealing with conflicting versions, scattered files, unclear ownership, or answers that change depending on where someone searches.
Useful outcome
A source inventory, the important gaps and conflicts, clear update ownership, and a prioritized cleanup or search plan.
03 / Decision review
Technical or vendor advisory
For a model, privacy, deployment, build-versus-buy, product, vendor, pilot, renewal, or negotiation decision.
Useful outcome
A side-by-side evaluation grounded in representative work, with tradeoffs, terms, costs, and the next decision clear.
04 / Enablement
Briefing, workshop, or coaching
For leaders or teams that need shared understanding to make a decision, evaluate an option, or complete a first build.
Useful outcome
A session built around one audience and real examples, with working notes or exercises and agreed next actions.
Hi, I’m Shawn.
Builder enough to care how it works. Operator enough to care if it helps on Monday.
I build practical agent systems and help people make the decisions around them. That means understanding the work first, being honest when a simpler tool is enough, and leaving you with something your team can inspect, correct, and own.
I work across agent implementation, business knowledge, model and deployment choices, and product or vendor evaluation. My advice comes from systems I have built, tested, operated, and had to fix when the real world disagreed with the plan.
Based in Roanoke, Virginia. Available for local in-person work and selected remote engagements.
Start with one useful conversation
Bring one problem worth solving.
We’ll use twenty minutes to see whether I can help and what the smallest useful next step might be.