- sunpower_tracked
- $12.36M
- olly_olly_goal
- 143%
- saas_tenure
- 18 months
Try a command: · ·
TECHNICAL FLUENCY · BUILT FOR SALES IMPACT
Sales-first. Technically fluent on purpose.
14 shipped builds since 2025, made alongside a full sales quota.
14
Shipped Builds
7 public · 7 private sales tools.
5
Core Technologies
Next.js, React, TypeScript, Tailwind, Python.
2025
Building Since
In parallel with carrying quota.
Since 2025 I have built hands-on technical projects to understand product workflows, front-end and back-end concepts, AI-assisted tools, and the systems behind the products I sell.
Resume downloads as a PDF. GitHub and LinkedIn open in a new tab.
Technical Proof Snapshot
Four data points that define the technical profile — all grounded in shipped portfolio work.
Daily AI stack
- Claude
Daily development workflows, code assistance, and research
- ChatGPT
Automation systems for content, ops, and CRM workflows
- Gemini
API integrations and prompt-library workflows
- Notion AI
Content, ops, and CRM systems inside Notion
Claude
ChatGPT
Gemini
Notion AIFeatured Builds
Three builds a stranger can open right now — each framed around technical fluency and sales relevance.
MetraNode
No-code widget builder with live preview and branded HTML embed export.
Proves I can build for the same non-technical audience I sell to — with firsthand understanding of embed workflows, API integrations, and brand-consistency UX.
2 visual references available in case study
STR Command Center
Operational CRM prototype modelling a small business across 18 routes.
Demonstrates pipeline thinking and CRM design from the inside — I modelled how operators track reservations, tasks, and workflows across a full operational surface.
FL Studio Master Hub
Searchable plugin database, workflow chains, and AI assistant for FL Studio producers.
Shows user-journey thinking and complex catalog UX — directly relevant to demo design for documentation platforms and educational SaaS.
3 visual references available in case study
High-level sketch
How MetraNode moves from configuration to embeddable output.
I Built the Software I Sell
Seven private builds aimed squarely at the job: a CRM with outbound calling, a quoting engine with discount governance, a lead pipeline, and the territory data underneath them.
Single-Operator Sales CRM
A working CRM with an integrated outbound calling workflow — the category of software I sell.
24 API routes · 17 SQL migrations · 18 row-level-security policies · 9 test files · 2 CI workflows · 123 files, ~16,700 lines
Pipeline stages, call logging, and consent handling were design decisions I made, not features I read about in a datasheet.
Guided Selling & Quoting
A configure-price-quote engine with real discount governance, plus an 18-step demo runner with objection branches.
A 2,503-line pricing core · 15 test files · 80 TypeScript files, ~10,046 lines
Floor enforcement, concession routing, and approval thresholds are the mechanics behind every discount conversation I have had.
Outbound Lead Engine
A Python demand-generation pipeline: scrape, enrich, score, store, review, sync.
Six trades · two-axis scoring separating profile fit from a 0–100 buying signal · SQLite and FastAPI
I wrote the ideal customer profile as a thesis and then implemented it. That is the discipline behind a prospecting decision.
Territory Intelligence
Building-permit and census data normalised to projects per 1,000 residents, with a mapping app for territory exploration.
130 Python files · ~21,571 lines
It lets markets of different sizes be compared directly, which is the whole question behind where to spend a quarter.
Industry Research Library
Industry and job-type profiles on a 15-section template, with per-record provenance and a self-reported completeness grade.
295 profiles sourced with citations · 320 still drafts · the library audits and reports its own coverage
A 15-section template is a battlecard structure. The provenance grading is why I know which parts I can quote.
US Geographic Reference Data
The validated canonical dataset underneath the territory and sourcing work.
50 states · 3,101 counties · 19,623 municipalities · 40,371 ZIP codes · six validation reports
Territory design starts with geography you can trust, including the ZIP-versus-ZCTA distinction most tools get wrong.
Sales OS Consolidation
An architecture for consolidating five separate repositories into one sales operating system.
Architecture decision records, interface contracts, and a staged migration plan — structure rather than running code
Boundaries, contracts, and staged migration are the vocabulary of an implementation conversation with a real buyer.
These seven are private repositories, so there is nothing to click. Every figure above was measured directly from the source, and I am happy to walk through any of them on a call.
Real Code, Real Repository
One excerpt from this site's own codebase. It is here because the standard it holds is the same one applied to a pipeline.
Real code from this site
CountUpValue.tsx — the component rendering the four numbers above
// Server-renders the FINAL value, so no-JS visitors and// crawlers always read the real number.const [display, setDisplay] = useState(value); useEffect(() => { if (target === null) return; if (window.matchMedia('(prefers-reduced-motion: reduce)').matches) return; // …animate from 0 once the element scrolls into view}, [target, durationMs]); // One text node. The accessible name is pinned to the final// value, so it never announces a mid-animation number.return ( <span ref={ref} role="img" aria-label={value}> {display} </span>);Why it matters: a counting animation is decoration, and decoration must never change the number someone reads. This renders the final value on the server, skips the animation entirely under prefers-reduced-motion, and emits a single text node so the figure survives being scraped, summarized, or read aloud. An earlier version paired a visible span with a screen-reader-only one; both were correct in a browser, but anything flattening the page text read 7 as 77.
This site is part of the proof
The portfolio you are reading is itself a shipped build — held to the same standards it describes.
- 376 Playwright e2e tests across 12 suites, run in CI on every push (desktop + mobile)
- Covering routing, navigation, accessibility, responsive layout, SEO metadata, and every published metric
- Axe accessibility gate — zero critical or serious violations, build-blocking
- Three hand-written audit scripts gate the build before lint, typecheck, or compile
- Next.js 16 + React 19 + TypeScript strict, managed with pnpm
- Fully self-hosted assets — fonts, icons, and images bundled locally, no CDNs
Built and verified with
- Playwright
- TypeScript
- Next.js
- React
- pnpm
- ESLint
Proof-of-Work Timeline
Learning in parallel with quota-carrying roles — not in isolation, not on a sabbatical.
2025 — Foundation
FocusFrontend basics: HTML/CSS, JS, React, TypeScript
OutputsFirst Next.js portfolio iteration · early Notion systemsSales whyMade me literate in modern web product structure
2025 — Builds
FocusReal projects: STR Command Center, FL Studio Master Hub, Studio Writing Hub
OutputsOperational tools and content systems shippedSTR Command Center → case studyFL Studio Master Hub → case studyStudio Writing Hub → case studySales whyProves I can ship — not just learn — in parallel with quota
2025 — AI Workflows
FocusClaude / ChatGPT / Gemini API integrations, prompt libraries
OutputsAI-assisted dev workflows · content automation pipelinesStudio Writing Hub → case studyPalattes → case studySales whyLets me talk about AI adoption with grounded, firsthand examples
2025 → 2026 — Productization
FocusMetraNode, portfolio v3.0, deployment and user-facing polish
OutputsPublic sites at jaydrivesrevenue.comMetraNode → case studySales whyDemonstrates product thinking, deployment discipline, and user-facing judgment
| Phase | Focus | Outputs | Sales Why |
|---|---|---|---|
| 2025 — Foundation | Frontend basics: HTML/CSS, JS, React, TypeScript | First Next.js portfolio iteration · early Notion systems | Made me literate in modern web product structure |
| 2025 — Builds | Real projects: STR Command Center, FL Studio Master Hub, Studio Writing Hub | Operational tools and content systems shippedSTR Command Center → case studyFL Studio Master Hub → case studyStudio Writing Hub → case study | Proves I can ship — not just learn — in parallel with quota |
| 2025 — AI Workflows | Claude / ChatGPT / Gemini API integrations, prompt libraries | AI-assisted dev workflows · content automation pipelinesStudio Writing Hub → case studyPalattes → case study | Lets me talk about AI adoption with grounded, firsthand examples |
| 2025 → 2026 — Productization | MetraNode, portfolio v3.0, deployment and user-facing polish | Public sites at jaydrivesrevenue.comMetraNode → case study | Demonstrates product thinking, deployment discipline, and user-facing judgment |
AI-Assisted Build Workflow
The same four tools from the snapshot, in the order they earn their keep: scope, scaffold, verify, ship.
- Notion AI
Step 01: Scope the workflow
Map triggers, states, and edge cases before any code — constraint-based prompt systems designed as multi-step workflows.
- ClaudeChatGPT
Step 02: Scaffold with AI assistance
Agent-assisted build workflows: Claude for daily development and code assistance, ChatGPT for content and ops automation.
- Gemini
Step 03: Verify & refine
Review and iterate on generated code by hand; Gemini API integrations power the automation pipelines that survive review.
- Vercel deployment
Step 04: Ship & document
Vercel-first deployment, with the habit of documenting builds, decisions, and patterns as they ship.
Technical Skills
Skills grounded in shipped builds, not course completions or tutorial code.
Core Technical Skills
Frontend / UI
Next.js · React · TypeScript · Tailwind CSS · accessible CSS motion. Built shipped UIs, not tutorial clones.
Used in 6 shipped builds
AI-Assisted Workflows
Prompt libraries, agent-assisted build workflows, content automation, and reference systems used in active portfolio and workflow contexts.
CRM / Automation / Process
CRM design from the inside. Pipeline thinking. Forecast accuracy. Automation across Notion + Python.
Used in 2 shipped builds
Product & Buyer Fluency
Can trace a feature to user value, then to revenue impact, in real demos and discovery.
Supporting Capabilities
Deployment & Documentation
Vercel-first deployment mindset. Habit of documenting builds, decisions, and patterns.
Workflow Architecture
Thinks in triggers, states, edge cases, and rollback paths — applied to both code and sales process.
API & Integration Literacy
Hands-on with REST patterns, rate limiting, validation, and end-to-end form/data flows.
Used in 2 shipped builds
Self-Directed Learning
Learning velocity proven by shipped builds while carrying full sales quota.
Where the Line Is
Technical fluency is the multiplier here, not the headline. Here is exactly what that does and does not mean.
What I can do
- Build and ship functional UIs and prototypes in React, Next.js, TypeScript, and Tailwind
- Integrate AI APIs (OpenAI, Gemini) and automate ops with Python scripts
- Read codebases, follow architecture decisions, and build custom demonstrations
- Design CRM automation and workflow systems (Salesforce, HubSpot, Notion)
What I don’t claim
- Professional engineering credentials — these are hands-on learning projects, not an engineering résumé
- A repositioning into traditional software engineering — this work exists to serve sales outcomes
- Hands-on blockchain / Web3 implementation — that area is research and documentation only
Still learning
- Node.js + Express and Next.js API routes (foundational)
- React Native + Expo mobile development (foundational)
- Docker and containerization (awareness level)
- Solidity and Layer 2 architectures (research phase)
How Technical Fluency Translates to Sales Results
Four things this work changes about how I sell — each one backed by a build above, not asserted.
Sharper Technical Discovery
I have built the dashboards, integrations, and AI workflows technical buyers ask about, so discovery goes to implementation detail instead of surface questions — and real blockers surface earlier.
Stronger Demos
I demo product in workflow rather than feature by feature, because I have built the workflows — and I can move from API rate limits to revenue impact without losing either side of the room.
Implementation Confidence
I think in triggers, states, edge cases, and rollback paths, so I can talk credibly about timelines, integration risk, and onboarding without over-promising.
RevOps / Sales Ops Fluency
I can reason about CRM schema, automation, and reporting rather than only requesting reports from RevOps — I built a working CRM to learn where those decisions get made.