| name | Tyler Mayberry | ||||||||||||||||||
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| title | AI-Native Systems Builder | ||||||||||||||||||
| location | Tulsa, OK / Remote | ||||||||||||||||||
| summary | AI-native systems builder who turns messy workflows into practical software, internal tools, agent workflows, and product prototypes. | ||||||||||||||||||
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AI-Native Systems Builder | Tulsa, OK / Remote
tyler@animasai.co | GitHub | LinkedIn | Portfolio | Animas AI
I build practical AI/software systems for messy real-world workflows: internal tools, agent workflows, dashboards, prototypes, and product surfaces that make ambiguous work easier to execute.
My strongest fit is work that sits between product, operations, customer context, and implementation. I am not trying to sell myself as a conventional narrow specialist. I am useful where a team needs someone who can understand the workflow, talk to the people doing the work, use modern AI and software tools well, and ship something concrete.
Dec 2025 - present
- Work on NDA-sensitive internal AI-enabled operations tooling, described publicly only at a high level.
- Contribute across agent workflow tooling, monitoring, prototype pipelines, content/project workflow surfaces, Git/deploy support, and operational dashboards.
- Use AI coding agents as a core development skill: inspecting unfamiliar systems, shaping implementation paths, debugging, verifying behavior, and shipping practical improvements.
Aug 2023 - present
- Build AI-assisted products, workflow automations, and internal tools under the Animas AI umbrella.
- Focus on practical systems that turn vague user or operator needs into structured workflows, reliable handoffs, and usable interfaces.
- Public proof includes Pip, product prototypes, AI workflow experiments, and applied AI integrations.
Product site | App | Case study
Pip is an AI-native spending companion built around one daily spending signal: Spendable Cash Today.
- Built with Next.js, React, TypeScript, Supabase, Plaid, OpenAI agent tooling, Netlify, Zod, Vitest, Playwright, and API routes.
- Designed around a clear trust boundary: deterministic application logic owns account state and financial calculations; the agent explains, routes intent, helps with setup, and presents approved actions.
- Strongest proof of my product judgment: reducing a broad personal-finance behavior into a simple daily signal instead of another crowded dashboard.
- Public-safe framing: read-only account data, deterministic financial logic, agent-assisted explanation/action, no money movement, and no financial-advice claims.
Private agent workflow and durable memory infrastructure.
- Built around the idea that useful agents need durable, curated context instead of raw transcript dumps.
- Explores agent coordination, retrieval, task records, tags, links, project context, and operational dashboarding.
- Useful proof for agentic systems, memory design, internal tools, and AI operations.
NDA-sensitive internal AI operations platform work for Brander Group.
- Publicly described only at a high level.
- Relevant areas include agent workflow tooling, automation, monitoring, content/project workflow surfaces, prototype workflow surfaces, and deployment/process support.
- Strong proof that I can work inside a complex, evolving AI operations codebase and turn ambiguous requests into verified changes.
AI-assisted execution-planning product prototype.
- Built with React, TypeScript, Supabase, Stripe, Resend, Gemini, access-key auth, onboarding flows, checkout/customer portal flows, audio transcription, brain-dump processing, and deterministic scheduling logic.
- Strong proof of shipping a real product surface with onboarding, payments, email, and workflow logic.
- Useful lesson: building the product is different from distribution and ongoing maintenance.
Nov 2022 - present
- Lead customer-facing operations under pressure, including prioritization, service recovery, guest communication, and team coordination.
- Manage a team of 5 and work across hotel/bar/front-desk operational realities.
- Confirmed operating outcomes include guest satisfaction up 22%, service scores up 18%, loyalty recognition improved from below 50% to above 80%, 98% complaint resolution, and RevPAR up 15% year over year.
Sep 2020 - Dec 2021
- Supported automotive media/navigation testing through troubleshooting, issue diagnosis, electronics work, internal database updates, and cross-team status communication.
- Worked inside email and spreadsheet-heavy operational workflows, which shaped my interest in internal tooling and automation.
Entrepreneurial ecommerce and web experiments
- Built and operated an ecommerce marketplace business that reached approximately $15,000/month profit at peak and over $200,000 in revenue.
- Coordinated 4 contractors across customer service, product research, and listing work.
- Used marketplace tools, spreadsheets, supplier/order tracking, and workflow processes to scale beyond what I could do alone.
| Category | Tools |
|---|---|
| Frontend | React, Next.js, TypeScript, JavaScript, Tailwind CSS |
| Backend / Data | Node.js, Python, SQL, SQLite, Supabase, PocketBase |
| AI / Agents | OpenAI API, Anthropic API, Gemini API, AI coding agents, agent workflows, prompt/tool boundaries |
| Product / Ops | Internal tools, dashboards, workflow automation, implementation plans, testing, documentation |
| Integrations | Plaid, Stripe, Resend, Netlify, GitHub, Make, Zapier |
- I learn quickly in unfamiliar systems.
- I am strongest when outcomes are clear but the path is not.
- I care about useful shipped work, verification, and clean handoffs.
- I communicate well with nontechnical users and can translate messy workflow needs into software/product decisions.
- I use AI agents actively, but my value is judgment: deciding what to build, what the model should not own, how to verify behavior, and how to make the system usable.
Oklahoma State University - Bachelor's Degree, University Studies
Focus/coursework: Management Science and Information Systems | Minor: Japanese
Shinshu University, Matsumoto, Japan - Intensive Japanese Language Program