The Ops Role Is Dead. Long Live the Ops Architect.
Why the shift from process execution to process design is the most important career pivot in operations right now.
cobey.io agent initialized
Building the world where people focus on work they love — and agents handle everything else.
This is a portfolio that works like an AI tool. Explore my career, projects, and research through interactive agents. Ask questions, dig deeper, and see how the future of operations unfolds.
Chat with my career
Ask questions about my work history, roles, and experience — the agent knows everything.
Explore active projects
See what I'm building right now — agentic systems, multi-agent orchestration, and more.
AI Deep Dive
Explore how intelligent systems think, build, and deploy — from agent reasoning to the full model creation pipeline.
The landscape — 12 months from now
40%
of enterprise apps will embed task-specific AI agents by late 2026 — up from under 5% today
67%
of executives expect AI agents to take independent action within their organizations by 2027
$300B
projected global spending on AI systems by 2026, reshaping how operations teams function
3×
high-performing orgs are 3× more likely to scale agents by redesigning workflows, not layering on tools
Career Agent
context: work history, roles, impact
Projects Workspace
Active builds, shipped work, and things in progress — the way an agent sees them.
Active
cobey.io — Agentic Portfolio
This website. A portfolio that functions as an AI exploration experience — interactive chat, agent-driven content, visible thinking.
Active
Multi-Agent Ops Framework
An orchestration layer that coordinates specialized agents across operations workflows — procurement, reporting, vendor management.
Building
AI Process Mapper
Tool that watches how teams actually work, then maps processes and identifies where agents can take over — without disrupting flow.
Shipped
RevOps Data Unifier
Integrated CRM, billing, and analytics into a single source of truth. Eliminated 40+ hours/month of manual reconciliation.
Building
Agent Collaboration Lab
Experimental environment where multiple AI agents negotiate, delegate, and solve operational problems together — in real time.
Shipped
Automated Reporting Pipeline
Built a zero-touch reporting system that generates executive summaries, KPI dashboards, and anomaly alerts daily.
AI Deep Dive
Explore how intelligent systems think, build, and deploy — from agent reasoning patterns to the full model creation pipeline.
0 / 5 modules explored
01
How an Agent Thinks
From prompt to plan — the reasoning loop inside every AI agent
›
An AI agent doesn't just respond — it reasons through goals. When given a task, it decomposes, plans, executes, reflects, and delivers. This loop is what separates an agent from a chatbot.
▸ agent reasoning loop
Input
Decompose
Plan
Execute
Reflect
Deliver
Click "Run simulation" to watch an agent reason through: "Prepare the quarterly ops report"
This loop — decompose → plan → execute → reflect — runs continuously. Production agents may loop through reflect → plan → execute multiple times before delivering, self-correcting along the way.
02
Capturing & Understanding Context
How agents ingest information and build working memory
›
Agents don't just read data — they build a working context from multiple sources simultaneously. Think of it as giving the agent the same situational awareness a senior ops person builds over years.
▸ context assembly
CRM records
Customer health + history
Slack threads
Team sentiment + blockers
Calendar data
Meeting load + priorities
Pipeline data
Revenue trajectory
Email threads
Pending decisions + actions
The Model Context Protocol (MCP) is the emerging standard that makes this possible — giving agents a consistent way to connect to any data source without custom integrations for each one.
03
Multi-Agent Orchestration
How specialized agents collaborate to solve complex problems
›
Real operational problems are too complex for one agent. Production systems use multiple specialized agents coordinated by an orchestrator — the same way a well-run team has specialists managed by a lead.
▸ multi-agent task routing
Orchestrator
standby
Data Agent
idle
Process Agent
idle
Comms Agent
idle
Each agent has a defined scope, its own tools, and clear boundaries. The orchestrator routes tasks, manages handoffs, and ensures the overall goal is met. This is how AI-native operations teams will function by 2027.
04
The Delivery Layer
How work actually gets done and shipped by agents
›
The last mile is where most AI tools fail. Thinking is easy — delivery is hard. Production agents need to take real actions: update records, send emails, generate reports, trigger workflows, and confirm results.
▸ delivery pipeline — "Close Q4 vendor reconciliation"
Pull invoices + payment records
Data agent → ERP + CRM query
Match & flag discrepancies
Process agent → reconciliation logic
Draft follow-ups to vendors
Comms agent → email generation
Compile summary for finance team
Orchestrator → report synthesis
Human reviews + approves
You → 2 min review vs. 4 hours manual
Agents don't replace humans — they compress time. A task that took a team 4 hours now takes an agent swarm 3 minutes, with a human spending 2 minutes on the parts that actually require judgment.
05
The Future: 12 Months From Now
What operations looks like in an AI-native company by early 2027
›
Based on current trajectories from Deloitte, McKinsey, Gartner, and IBM, here's what working at an AI-native company looks like 12 months from now:
Agent morning briefing
Your day starts with a synthesized briefing — what happened overnight, what needs attention, what was handled autonomously.
60% shorter meetings
Agents pre-compile context, generate agendas from open items, and draft follow-ups in real time. Meetings become decision sessions.
Digital colleagues on the org chart
Agents with defined roles, SLAs, and performance metrics. The vendor management agent handles 80% of procurement tasks.
Ops becomes architecture
Ops people don't run processes — they design them, train agents to execute, and optimize the human-agent collaboration model.
The role of "operations" has shifted from execution to architecture. You manage outcomes, not processes. Instead of overseeing 12 steps in a workflow, you define the goal and review the result.
↑ ↓ to navigate modules · Enter to expand · Esc to collapse
The full pipeline from raw data to deployed intelligence — decoded for your role. Choose your perspective and watch each stage translate in real time.
Capability Registry
Skills and certifications — presented the way an agent indexes its own capabilities.
AI Agent Architecture
Multi-agent systems, orchestration patterns, MCP, A2A
Revenue Operations
CRM design, pipeline architecture, GTM systems
Process Automation
Workflow design, Zapier, Make, custom scripts
Data Engineering
SQL, Python, ETL pipelines, data modeling
Systems Integration
API design, middleware, cross-platform data flows
Prompt Engineering
LLM optimization, chain-of-thought, tool use patterns
Product Strategy
Roadmapping, user research, GTM alignment
Team Leadership
Cross-functional management, hiring, mentoring
Frontend Development
React, HTML/CSS, interactive prototyping
Certifications
🤖
Salesforce Certified AI Associate
AI fundamentals within the Salesforce ecosystem · Dec 2023
💬
Slack Certified Consultant
Slack platform architecture, integrations, and deployment · Dec 2022
📊
Salesforce Certified Business Analyst
Requirements gathering, process mapping, stakeholder management · Aug 2022
🌐
Salesforce Certified Experience Cloud Consultant
Digital experience design, portals, and community architecture · Aug 2022
💰
Salesforce Certified Sales Cloud Consultant
Sales process design, pipeline management, forecasting · Aug 2022
🎧
Salesforce Certified Service Cloud Consultant
Case management, service automation, knowledge base design · Jul 2022
⚙️
Salesforce Certified Advanced Administrator
Advanced platform configuration, security, and data management · Dec 2021
🔧
Salesforce Certified Platform App Builder
Declarative application development, data modeling, business logic · Jan 2021
📋
Salesforce Certified Administrator
Core CRM architecture, automation, user management, reporting · Mar 2019
Education
🎓
Rutgers University · B.S. Information Technology & Informatics
Minor: Entrepreneurship · Graduated cum laude · Focus: IT project management · 2017–2018
🎖️
Naval Justice School · Certified Court Reporter
Naval Base Newport, RI · Legal reporting and administrative law · 2011
Community
🤝
TeamUP Mentor · Rutgers Business School
Mentored undergraduate students in professional development and business leadership · 2019–2022
🏆
ITI Showcase Judge · Rutgers University
Judged student innovation projects at the Spring 2019 ITI Showcase
Research Logs
Field notes from building at the intersection of AI and operations.
Feb '26
Jan '26
Multi-Agent Orchestration: Lessons from Production
What I learned deploying a 5-agent system for vendor management — the wins, the failures, and the patterns that emerged.
Dec '25
MCP Changed How I Build Agent Systems
The Model Context Protocol is the missing link between agents and enterprise data. Here's how it works in practice.
Nov '25
Why RevOps Teams Should Care About AI Agents
Revenue operations is the perfect proving ground for agentic AI. The data is structured, the processes are repeatable, and the ROI is measurable.
Oct '25
The Autonomy Spectrum: When to Keep Humans in the Loop
Not every process should be fully autonomous. A framework for deciding where agents should act alone vs. escalate to humans.
Let's build something.
I'm working at the intersection of AI and operations — helping teams design agentic systems that actually ship. If you're thinking about how your operations team works 12 months from now, I'd love to talk.
Message sent
Release Log
Deployment history — every version, every change, tracked automatically.
v0.8.0
Career Agent Voice — TTS Read-Aloud
AI-powered speech synthesis for career chat with streamed audio playback
2026-02-16
▸
Added text-to-speech read-aloud for Career Agent responses using OpenAI's TTS API with streaming audio delivery for near real-time playback.
+ Added
/api/tts endpoint — Serverless OpenAI TTS function with rate limiting and streamed audio response
Speaker icon — Inline TTS button on agent messages with loading, playing, and idle states
Audio streaming — Chunked transfer from OpenAI through server to client, eliminating buffering delay
Playback management — Single-audio control: starting a new read-aloud stops the previous one
✕ Fixed
Sidebar highlight — Skills and AI Deep Dive were swapped in sectionMap array
2 files
+200 lines
-3 lines
v0.7.0
Mobile Responsive & Interactive Logo
Full mobile layout with touch gestures, hamburger nav, and desktop logo easter egg
2026-02-16
▸
Complete mobile responsive layout with three breakpoints, hamburger navigation, and touch gestures. Added interactive Pulse logo easter egg on desktop with hover glow and hack mode.
+ Added
Mobile responsive layout — Three breakpoints: tablet (1100px), mobile (768px), small phone (380px)
Hamburger navigation — Slide-out sidebar with backdrop overlay for mobile
Touch gestures — Swipe left/right between sections on mobile
Interactive hero logo — Desktop-only Pulse logo with parent hover glow and click-to-activate hack mode
Portrait optimization — Eager loading with fetchpriority="high" for instant mobile render
~ Changed
Hero layout — Desktop grid collapses to stacked mobile layout with centered portrait
Context panel — Hidden on mobile, content accessible via main scroll
Command bar — Full-width bottom bar on mobile with simplified controls
2 files
+473 lines
-5 lines
v0.6.0
SEO Optimization & Favicon
Full SEO overhaul — meta tags, social cards, favicon, structured data
2026-02-16
▸
Complete SEO overhaul — proper meta tags, Open Graph & Twitter Cards, favicon from Pulse logo, robots.txt, sitemap.xml, and JSON-LD structured data.
+ Added
Meta tags — Title, description, author, canonical URL
Open Graph — Rich social previews for Facebook, LinkedIn, etc.
Twitter Cards — summary_large_image with @cobeyluke handle
Favicon set — 6 sizes generated from Pulse logo + web manifest
OG image — 1200×630 branded social sharing image
robots.txt + sitemap.xml — Crawler guidance and indexing
JSON-LD — Person schema with social links and skills
~ Changed
Page title — "Wireframe Prototype" → "Cobey Maynard — AI for Operations · cobey.io"
6 files
+52 lines
-1 line
v0.5.0
Section Consolidation — AI Deep Dive
Merged Learn + Model Creation into unified AI Deep Dive, removed Client Signals
2026-02-15
▸
Removed Client Signals section, merged Learn and Model Creation into a unified "AI Deep Dive" section with mode switcher, reducing from 10 to 8 sections.
+ Added
AI Deep Dive mode switcher — Toggle between "How AI Thinks" and "How Models Are Built" within one section
switchLearnMode() — Mode toggle with panel visibility and context panel updates
Dynamic pipeline embedding — Model pipeline now generates into unified section container
~ Changed
Navigation — 10 → 8 sections; Learn renamed to "AI Deep Dive"
Command bar — Model keywords now route to Learn section
− Removed
Client Signals — Section, CSS, sidebar nav, context panel, command routing
Standalone Model Creation — Merged into AI Deep Dive
4 files
+85 lines
-320 lines
v0.4.0
Model Creation Decoder, AI Chat, & Vercel Deployment
Persona-based pipeline decoder, live OpenAI Career Agent, production deployment
2026-02-15
▸
Added interactive Model Creation section with Engineer/Operator persona decoder, live AI-powered Career Agent via OpenAI API, and production-ready Vercel deployment structure.
+ Added
Model Creation section — 6-step pipeline with real-time Engineer/Operator persona decoder
Decode animation — Character scramble effect with sequential pipeline step reveals
OpenAI Career Agent — /api/chat serverless function with GPT-4o-mini and full career context
Vercel deployment — public/ directory, API routes, vercel.json configuration
Chat history — Multi-turn conversation with typing indicator
~ Changed
Career Agent — Now calls live OpenAI API with keyword fallback for offline use
Section count — 10 sections (added Model Creation)
8 files
+650 lines
-25 lines
v0.3.0
Release Notes & Agent Documentation
Agent-ready docs, release tracking system, cross-session continuity
2026-02-15
▸
Added comprehensive agent-ready documentation and a release tracking system for cross-session continuity. Any future agent can now read CLAUDE.md and the docs/ folder to get full context on design tokens, code architecture, content rules, and voice guidelines.
+ Added
CLAUDE.md — Master agent context file with project architecture, design tokens, and conventions
docs/DESIGN-SYSTEM.md — Complete color palette, typography, spacing, and component patterns
docs/ARCHITECTURE.md — Code structure, JS patterns, simulation architecture, and checklists
docs/CONTENT-GUIDE.md — Brand voice, real career data, testimonials, and content framing rules
CHANGELOG.md — Version-tracked release history
Release Log section — Interactive deployment log page in the wireframe
~ Changed
README.md — Updated with docs references and agent onboarding path
Navigation — Added Release Log to sidebar, command bar, and section map
6 files
+1,200 lines
-28 lines
v0.2.0
Interactive Learn Section & LinkedIn Banner
4 live simulations, progress tracking, social media banners
2026-02-15
▸
Transformed the static "How AI Agents Work" page into a fully interactive simulation experience with 4 runnable engines. Created LinkedIn and X/Twitter profile banners with safe-zone layouts.
+ Added
Reasoning Loop Simulation — 6-step animation (Input → Decompose → Plan → Execute → Reflect → Deliver)
Context Building Simulation — 5-source context map with animated particle effects
Orchestration Simulation — Multi-agent task routing with real-time message log
Pipeline Simulation — 5-step delivery pipeline with agent vs. manual time comparison
Module progress tracking — learnModulesExplored Set with visual progress bar
Keyboard navigation — ↑↓ to navigate modules, Esc to close
LinkedIn banner (1584×396) — Profile-photo-safe layout
X/Twitter banner (1500×500) — Agent network diagram
✕ Fixed
Critical JS forward-reference bug — Template literal in contextData.learn killed entire script block. Fixed with dynamic rendering pattern.
LinkedIn banner layout — Profile photo was blocking text. Redesigned with 380px safe zone.
~ Changed
Learn section CSS — ~130 lines static → ~450 lines interactive simulation styles
Learn section JS — 3-line toggleModule → ~330 lines of simulation engines
Home action card — "Learn how AI works" → "How AI agents work"
3 files
+780 lines
-135 lines
v0.1.0
Initial Release — Agentic Portfolio Wireframe
Complete interactive prototype with 8 sections, Career Agent, project briefs
2026-02-15
▸
Complete interactive wireframe prototype for cobey.io — a portfolio built as an agentic AI exploration experience. Single-file HTML with all CSS and JS embedded. Zero external dependencies.
+ Added
Three-column workspace layout — Sidebar + Main content + Context panel, mirroring AI tool interfaces
Design system — CSS custom properties, monochrome palette, #F24F36 coral accent, Inter + JetBrains Mono
The Pulse logo — Hexagonal core with concentric rings and Y-spokes (SVG + PNG, dark + light)
Mission Control — Stats dashboard, action cards, research-backed insight cards
Career Agent — Chat interface with real career data (6 roles), suggested questions, keyword response system
Projects Workspace — 6 projects with filters, click-to-generate briefs with build animation
How AI Works — 5 learning modules with ASCII architecture diagrams
Skills & Certs — 9 skill areas with proficiency bars, 9 certifications, education
Client Signals — 4 real testimonials with attribution
Research Logs — 5 blog entries with full-screen overlay reader
Connect — CTA page with email and social links
Command bar — ⌘K keyboard shortcut, keyword routing to any section
Dynamic context panel — Per-section agent thinking and source awareness
Brand style guide — Comprehensive .docx with design tokens and component specs
31 files
+8,666 lines