Building the AI Company
01
Teaching Session
Getting more DONE with AI
01 / 12

Building an AI Company.

I turned an idea into a profitable business in 4 weeks.
Now running and scaling the entire company and its operations with AI agents.

Siva Darivemula
Founder, PilotPrep
PilotPrep
faacogscreen.com
Background
02
Practitioner
ABOUT ME
02 / 12

A practitioner, tech enthusiast, product & GTM leader.
not a coder.

I tried solving a personal problem using my enterprise AI skills.
Ended up building a company.
Now onboarding, managing, and orchestrating an AI agent team to help me run and scale the company.
My child needed to pass a CogScreen-AE evaluation to keep flying. I searched for something — anything — to help them prepare. There was nothing.
15+
Years in product and growth marketing leadership — enterprise & startup
4 weeks
Zero to profitable — PilotPrep, solo, Jan 2026
8+
AI agents onboarded and operating today
Siva Darivemula
Founder, PilotPrep / faacogscreen.com
faacogscreen.com
The Problem
03
Operations
The operational challenge
03 / 12

The product is good. Demand is there.
The operations needed to scale.

Growing a one-person company means every function falls on you — content, engineering, SEO, marketing, product, QA, analytics. I needed a system to offload the manual and routine work so I could focus on what matters most.

The scaling problem
Content needs daily publishing and SEO and AI discovery optimization
Outreach requires consistent, personalized follow-up
Every release needs QA; every week needs analytics
No budget for freelancers or employees
The agent system
Each role gets a specialized agent with a job description, skills, onboarding, and resources
Persistent knowledge base per role — context and institutional memory is never lost
Human-in-the-loop for quality, evaluation, and approval. Keeping the AI and agents focused/honest
Feedback & collaboration loops make agents and outputs more valuable (just like highly skilled employees)
The Operating Model
Identify a time-consuming need → define scope and skills → build the agent and load the knowledge base → operationalize → complement with MCP tools and feedback loops → iterate.
Siva Darivemula
Founder, PilotPrep / faacogscreen.com
faacogscreen.com
Case Study
04
The Proof
Case study — PilotPrep / faacogscreen.com
04 / 12

From pilot to production.
Road ahead: Building Distribution and removing the outreach guardrails

PilotPrep launched in January, hit profitability in 4 weeks, and shipped an iOS app in March — built entirely by agents. Weekly usage is growing 22%. Zero paid marketing. Zero headcount. The system keeps running.

4 weeks
Launch to profitability — Jan 2026
22%
Weekly usage growth — organic, no paid marketing
~$0
Customer acquisition cost — SEO-driven
8+
Agents in production — and growing
Business results — March 2026
  • 65 paying subscribers — growing weekly
  • $1,820 MRR this month
  • $5–$10/month operational cost (not incl. sunk costs like AI subscriptions)
  • 100+ features shipped since January
AI integrations shipped — built by agents
  • Claude (Anthropic) — product planning, content generation
  • Perplexity — technical expert & knowledge enrichment
  • Google Vertex AI — Development, Security, Hosting, and ML infrastructure
  • iOS app released March 2026 — end-to-end design and delivery by agent staff
Siva Darivemula
Founder, PilotPrep / faacogscreen.com
faacogscreen.com
The Approach
05
The Lab
The approach — a live lab
05 / 12

PilotPrep is now an AI-first laboratory to automate business workflows.
Limited only by my imagination and ability/time.

How far can every business function be automated or enhanced with AI — at $0?

The answer is still developing. Latest tools and updates keep raising the bar.

The experiment — how it runs
  • Identify a function that costs time or money to run manually
  • Automate or enhance it with the best available AI tools
  • Keep costs at or near zero — maximize free tiers, open source, headless APIs
  • Iterate as new tools emerge — the stack evolves constantly
What this revealed
  • The real bottleneck is awareness, knowledge, and imagination — not technology
  • Costs can stay low even at meaningful scale
  • Each new tool unlocks new experiments, ideas, and workflows
  • The scope for automation is huge — any structured process or method can become a "skill"
💭
"We have enterprise tools, approved vendors, AI pilots, and security guardrails. So — how does a large organization actually operationalize this?"
🧪
Start small — one experiment, one workflow, one measurable outcome
🏗️
Culture first — experimentation mindset has no enterprise license requirement
🚀
Build a sandbox — push your tools to the limit; let the gaps reveal your roadmap
→ Let's explore — Q&A
PilotPrep
Siva Darivemula
Founder, PilotPrep / faacogscreen.com
faacogscreen.com
The Team
06
Agent Org
The agent team
06 / 12

Every role. Every function.
Agent-operated.

👤
Siva Darivemula — Founder
Human-in-the-Loop · Strategy · Direction · Final Approval
↓ leads
🤖
Dave — COO
Operations · External comms · Approvals
📣
Marcus
SEO & Growth
Keyword research · AEO · Analytics · Exa.ai
✍️
Elena
Content Strategy
Blog writing · Brand voice · Editorial calendar
📧
Dixie
SDR & Customer Success
Outreach · Email campaigns · CRM · Follow-up
🎓
Dr. Keller
Aviation Content Lead · AI Persona
FAA domain · Content authority · Authorship
👩‍💼
Annie — Engineering Mgr
Product & Engineering Lead
🎨
Maya
UX & Design
Wireframing · Components · User research
👨‍💻
Bob
Full-stack · Firebase
React · TypeScript · Google Vertex AI
🧪
Olga
QA & Test Automation
Playwright · Bug tracking · Release QA
Every blog post. Every feature shipped. Every outreach email. Every operation. Orchestrated by agents.
👤
Agent-operated.
Human-managed.
Daily or every-other-day 1:1s with Dave & Annie — reviewing team performance, KPIs, product and business metrics, roadmap, and priorities. Every agent has goals, improvement targets, and reports on them.
KPIs & Goals Performance Reviews Strategy Alignment
PilotPrep
Siva Darivemula
Founder, PilotPrep / faacogscreen.com
faacogscreen.com
Daily Operations
07
The Loop
A day in the AI company
07 / 12

Autonomous by default.
Human in the loop.

1
Trigger
Scheduled task fires. Agent wakes with its full knowledge context already loaded.
2
Read Context
Agent reads its knowledge base — domain expertise, prior history, protocols, constraints.
3
Execute
Agent runs the task — scan, draft, analyze, route — and produces a structured output.
4
Siva Reviews
I review, approve or modify the outputs. Then AI publishes or acts on it. On to the next priority.
PilotPrep
Siva Darivemula
Founder, PilotPrep / faacogscreen.com
faacogscreen.com
Key Insight
08
The Shift
The big question
08 / 12
"The question is not how to use AI for your team. The question is how do you become an AI-native team."
Before — individual experimentation
Teams using AI independently, no coordination · Innovative but no governance or innovation at scale · No compound learning across the org · Each team staying within company-approved tools, security, and sandbox boundaries
After — automating workflows at scale
Automating and improving workflows and outcomes with AI · Persistent memory and institutional knowledge · Operating within governance, risk, and IT guardrails — but pushing the limits · Real challenges surface real ideas that make the org adapt and evolve faster
PilotPrep
Siva Darivemula
Founder, PilotPrep / faacogscreen.com
faacogscreen.com
For Your Org
09
Framework
How organizations adopt this
09 / 12

Key criteria.

  1. 01
    Define roles, not tools
    What job needs doing consistently? Write a job description — not a prompt. Give it scope, outputs, and constraints.
  2. 02
    Build the knowledge base first
    Domain expertise, history, and institutional memory live in files — not chat context. Agents read before they act.
  3. 03
    Design the approval workflow
    Human judgment where it adds most value. Define what "done" or "good" or "better" looks like. Who approves? What's the escalation path?
  4. 04
    Measure by output quality
    Not usage, completions, or token count. Did the agent produce a usable output your team would have been proud of? That's the metric.
  5. 05
    Build a culture of experimentation
    Innovation at scale requires permission to fail fast, learn openly, and iterate. Leverage deep expertise where it matters most — humans set the bar, AI meets it.
PilotPrep
Siva Darivemula
Founder, PilotPrep / faacogscreen.com
faacogscreen.com
What's Next
10
Open Floor
The conversation continues
10 / 12
PilotPrep

This is reproducible.
The blueprint exists.

Everything shown here — the agent roles, the knowledge base architecture, the approval workflows, the ops loops — was built from first principles. None of it requires special infrastructure, a large team, or a long runway. It requires clear thinking about roles, outputs, and where human judgment actually matters.

A mental model to take with you
Roles over prompts · Knowledge over context · Workflows over features · Human judgment where it matters most · Culture of experimentation over perfection
There is no best answer — yet
The organizations winning are doing, learning, and adapting. There's no playbook — only what you discover by trying. Hopefully some of this opened a few ideas about what you could do differently, and how you might evolve.
Email siva@faacogscreen.com
Web faacogscreen.com
LinkedIn linkedin.com/in/darivemula
X / Twitter @SivaDarivemula
Siva Darivemula
Founder, PilotPrep / faacogscreen.com
Thank you
Agent Profile
11
Deep Dive
Agent deep dive — Marcus
11 / 12

Meet Marcus.
Always-on SEO & community discovery agent.

M
Marcus
SEO & Community Intelligence
Reports to Dave · COO
Core Skills
🔍 Forum & social thread discovery (9 platforms)
✍️ Forum reply drafting — under 200 words, humanized
🧠 Aviation domain validation via expert skill
📊 SEO + AI/LLM citation optimization
📌 Deduplication — persistent engagement history
🎯 Blog angle identification for Coach Keller
Tools
Exa.ai Aviation Expert Humanizer Search Console Ahrefs
⏰  Tue & Fri · 09:00 UTC · automated run
🔴  Event mode: 3× daily during live conferences
How Marcus Works
1
Load context first
Reads latest.md + engagement history before anything else — never resurfaces already-reported threads
2
Run Exa across 9 platforms
Reddit (r/flying, r/FAAHIMS, r/aviationmaintenance), pilotsofamerica.com, airlinepilots.com, LinkedIn, Twitter/X — all with 14-day freshness gate
3
Apply the freshness gate
Original post ≤21 days AND last activity ≤7 days. Threads outside the window are excluded — no stale engagement
4
Draft → validate → humanize
Raw reply → Aviation Expert skill (accuracy check) → Humanizer skill (strips AI tone, em dashes, corporate phrasing)
5
Deliver & wait for approval
Report saved to latest.md + dated archive. Elena polishes into an engagement brief for Siva. Nothing posts without approval.
🔁 How Marcus learns: Every run appends to the engagement-history dedup register. Failed reports are committed with a documented post-mortem — e.g., the March 20 overhaul hardened freshness gates and added mandatory LinkedIn/Twitter drafts.
Live Output — March 27 Report
Forum Intelligence Report · 2026-03-27
3 HIGH · 2 MED · 11 backlog
HIGH r/flying · posted 5h ago
Letter from FAA Regarding 1st Class Medical + PTSD VA Disability
No replies yet. PTSD → HIMS pathway → CogScreen-AE requirement. High-intent keyword cluster.
"The type of letter the FAA sent matters more than the diagnosis at this stage. PTSD cases in the HIMS pathway typically require a neuropsychological workup including the CogScreen-AE…"
HIGH r/FAAHIMS · posted 15h ago
ADHD Disposition Table — 4-year off-stimulants threshold
Pilot approaching evaluation window. Disposition table questions attract others at same planning stage.
"Four years off stimulants is a significant milestone. The non-medicated ADHD pathway typically includes the CogScreen-AE as the FAA-approved cognitive battery…"
MED r/FAAHIMS · posted yesterday
Non-HIMS Neuropsychs for Medical Clearance — recommendations?
Underserved question — most replies point to HIMS AME directory, not the neuropsych specifics.
Also delivered this run
1 LinkedIn company post draft · 1 Twitter/X post draft · 2 blog angle flags for Coach Keller · Brand mention log · Competitor activity update
PilotPrep
Siva Darivemula
Founder, PilotPrep / faacogscreen.com
faacogscreen.com
The Opportunity
12
Discussion
Q&A — ideas from Peter
12 / 12

Where can you use AI agents?

Peter shared this list. We can discuss any one or all of them, time permitting. But I'd love to hear your questions, comments, and what you would add to this list.

🔍 Research & Analysis
Review Site Agent
Monitoring customer feedback on G2, Capterra, and review platforms — surfacing themes, sentiment, and gaps
Brand in the News
Watching product and brand mentions across media, analyst coverage, and press — daily digest to leadership
Competitive Watch
Monitoring competitor websites for messaging changes, feature launches, and positioning shifts
SEO / GEO Agent
Tracking search and generative engine optimization performance — keyword rankings, AI citation analysis
Audience Intelligence
Defining and updating ideal customer personas, key pain points, and buying triggers from live market signals
✍️ Content Generation
DOC
→
Messaging Agent
Cross-checks content against brand narrative and strategy — flags drift, suggests aligned copy
→
DOC
PPT
→
Layout Agent
Converts presentations to brand-compliant format — fonts, colors, slide structure, logo placement
→
PPT
IDEA
→
Blog / Writing Agent
Drafts articles, thought leadership, and social content from a topic brief or outline — on brand, on message
→
DOC
Think about your team
Which of these workflows happens manually today — on a recurring basis — and produces a predictable, structured output? That's your first agent.
PilotPrep
Siva Darivemula
Founder, PilotPrep / faacogscreen.com
faacogscreen.com
Appendix
A
Tech Stack
Appendix — how it's built
A / 12

Production stack.
Agent-operated infrastructure.

Technology Stack
⚛️
Frontend
React 19 · TypeScript · Vite 7 · Framer Motion
🔥
Backend
Firebase Functions (Node 22) · Firestore · Auth · App Check
🤖
AI / ML
Gemini 2.5 Flash · Gemini 2.5 Pro · Claude · Perplexity · Google Vertex AI · Imagen 4 · Exa.ai · GraphRAG
📱
Mobile
Capacitor · iOS App Store · CogPilot
💳
Payments & CRM
Stripe Checkout · Customer Portal · Brevo
Agent Tools (MCP)
🧠
Claude Code + Agent SDK
Anthropic · Multi-agent orchestration framework
🔍
Exa.ai
Neural web search for research agents (Marcus, Elena)
📚
context7
Live library docs for Bob and engineering agents
📁
GitHub + Google Drive
Source control · knowledge base · shared docs
⏰
Scheduled Tasks MCP
Cron-driven autonomous operations and reporting
🔄
Hindsight MCP
Agent memory, context replay & decision auditing
Networking
🔒
Tailscale
Zero-config secure mesh VPN between agent nodes and infrastructure
Playwright E2E Vitest Firebase Emulator GA4 · Looker Studio Firebase App Check
PilotPrep
Siva Darivemula
Founder, PilotPrep / faacogscreen.com
faacogscreen.com