I built a support team of AI agents
so I could get my time back
BUILD 1�The job-search
system
$$$$�People
bought it
TIME�People needed
help
BUILD 2�A chat support
for the fix
Laid off in December, then built an AI job-search system and sold it.
Then supporting the buyers started eating the time it was supposed to give.
So I built a second system to carry the load.
Renee Romero . AI Systems Designer . 2026
SECTION 01
The problem
What support looked like before this build.
THE TURNING POINT
“My Claude doesn’t know what your Claude knows.”
A buyer said this on a support call. He suggested I build a custom GPT.
That was key.
The people who bought my job search system had a 64-page setup guide and to use their own AI.
The fix was NOT more documentation.
It had to be something that already carried the knowledge.
Renee Romero . AI Systems Designer . 2026
3
THE PROBLEM, IN NUMBERS
Supporting buyers ate my time
64 - page setup guide
9 → 64
pages the Setup Guide grew, and still did NOT close the gap
13
paying customers across 4 product-packages
Call after call
live support, each one straight out of deep work
The guide told buyers to upload the workflow files to their own LLM.
Fine on paper.
In practice the questions kept coming.
Renee Romero . AI Systems Designer . 2026
4
THE PLAN
What the support would need to do
I knew the problem, not the build.
So I brainstormed with Claude: what would this thing have to do to support any buyer, no matter how they set it up?
Know every workflow�by node name, not by guess
Know the Notion setup�field mappings and all
Know what the buyer owns�which package, what it includes
Fetch the answer�hand off cleanly when one agent can’t solve it
Say when it doesn’t know�instead of making something up
Cost less than my time�so most questions never reach me
Renee Romero . AI Systems Designer . 2026
5
SECTION 02
The system
13 agents, 1 production Worker, 4 KV namespaces.
THE ARCHITECTURE
The stack it runs on
Claude said multi-agent was the right shape and to use these parts to build it.
Cloudflare Workers
one production Worker, entry point and routing
Claude API
Sonnet 4.6 for most, Opus 4.6 for the hard cases
Gumroad webhook
a purchase creates the buyer token
Resend email
escalations to me plus the daily gap digest
TypeScript
one file, 4,378 lines, the entire system
Renee Romero . AI Systems Designer . 2026
7
THE MULTI-AGENT ARCHITECTURE
Multi-layered escalation
Renee Romero . AI Systems Designer . 2026
9
THE ARCHITECTURAL FLOW
How the pieces connect
Renee Romero . AI Systems Designer . 2026
8
WHAT THE BUYER SEES, 1 OF 2
The routing happens in the open
The buyer is on a hosted URL link in their browser.
They ask about WF08 cost.
The orchestrator routes → checks with WF08 specialist.
1 Routing
2 Checking
Renee Romero . AI Systems Designer . 2026
10
WHAT THE BUYER SEES, 2 OF 2
What the buyer gets: pulled from the real files
WF08 specialist → answers.
Renee Romero . AI Systems Designer . 2026
11
THE COST ARCHITECTURE
30 free, then 3 prepaid tiers
30 free / day
reset on a daily timer, never touches paid balance
$5 / $15 / $25
optional prepaid credit after the free tier, never expires
2 hard caps
a 30-message buyer gate and a workspace ceiling, nested
2 stores, never crossed
free count and paid balance live apart
Renee Romero . AI Systems Designer . 2026
12
THE BOUNDARIES IT ENFORCES
Scope and security: 2 things it refuses
Scope refusal�off-topic ask,
it declines and
points to a general assistant
Leak guard�asked for the workflow file,
it won’t hand back the paid product,
even to a buyer
Renee Romero . AI Systems Designer . 2026
13
LAUNCHED
Live on 05-28-2026
13 buyers, 1 production system.
Everything that follows happened after it went live, in front of real customers.
THE CATCH BEFORE LAUNCH
The data didn’t match the notes
Before I sent the email announcement to my buyers, I checked production directly.
I didn’t trust the handoff notes.
THE NOTES SAID
PRODUCTION ACTUALLY HAD
Verification caught a silent failure.
Renee Romero . AI Systems Designer . 2026
15
THE CATCH AFTER LAUNCH
The morning-after email digest
The digest flagged a 30-message session.
Claude checked the logs.
Found the specialist guessed its replies.
No red dot and no error notifications.
This = silent failure.
The fix
Renee Romero . AI Systems Designer . 2026
16
SECTION 03
How it was built
5 weeks, a non-engineer, and 1 phase table.
HOW IT GOT BUILT
Claude frustrated me, so I built a table to track everything
I didn’t know how many agents this needed. I knew overloading one agent backfires, so it had to be split, but how many?
Early on I hit frustration. I’m not technical, and I couldn’t hold all the “not yet” pieces across chats that reset between sessions.
So we built a phase table that carried the plan forward, similar to lesson planning from my former career as a teacher.
PHASE & STATUS TABLE
A Auth + token lookup
Done
B Orchestrator routing
Done
C Specialist grounding
Done
D Hedge cascade
Half-wired
E Cost caps + tiers
Done
F Digest + gap logging
Half-wired
G Backfill + launch
Not started
H Buyer announcement email
Not started
Renee Romero . AI Systems Designer . 2026
18
BEFORE VS. AFTER
What changed
BEFORE
AFTER
Support
64-page PDF, ad-hoc calls, self-serve
on-demand chat, gated, knows the codebase
Time
15 min to 3.5 hrs per call, unpaid
~$0 of my time, asynchronous
Knowledge
whatever the buyer’s AI guessed
grounded in the real JSONs and schema
System
none, buyers recreated it
13 specialists hold the knowledge
Build effort 80+ hrs over ~5 weeks Live 13 buyers as of 05-28-2026
Renee Romero . AI Systems Designer . 2026
19
WHAT THIS BUILD TAUGHT ME
The takeaways
01
The user names the real problem, not the designer
The 64-page guide wasn’t the problem. The problem was the gap between where the knowledge lived and where the buyer needed it. The buyer told me. I listened.
02
Both failures pointed to human judgment in the loop
The records that weren’t loaded and the ungrounded answers were both caught by me, not the system. That is where the trust belongs.
03
This build added a new toolkit
The vocabulary: scope refusal, leak guard, grounding, hedge cascade, backfill. The stack: Cloudflare Workers, Resend, TypeScript, and a Gumroad webhook.
Renee Romero . AI Systems Designer . 2026
20
I’m an AI Systems Designer, not an engineer.
The skill is naming the real problem, then building only what solves it.
Specification Precision . Evaluation Design . Multi-Agent Decomposition . Failure Pattern Recognition�Trust and Security Design . Context Architecture . Cost and Token Economics
reneeromero326@gmail.com . linkedin.com/in/renee-romero . muralderomero.com