I built 440 ChatGPT protocols for $1M–$10M founders looking for 5 beta testers before full launch.
Spent 2 years mapping every operational failure that kills businesses between
$1M and $10M.
The result: 440 protocols across 5 vaults.
Each one is a structured ChatGPT prompt that produces institutional-level output in 4 minutes. No fluff. No theory. Paste and deploy.
Here is what founders are running right now in beta:
OPERATIONS:
→ Founder Dependency Audit maps every decision routing through you and transfers ownership to your team same day
GROWTH:
→ Whale Fast Track Sequence compresses your top 1% prospect to first meeting in under 15 minutes
STRATEGY:
→ Competitive Moat Audit maps your defensible positioning against every
major competitor in one session
TALENT:
→ High Friction Gateway eliminates B-players before the first interview
CREATIVE:
→ Content Atomization Blueprint turns one asset into 20+ platform pieces
with full distribution calendar
Zero code. Zero API. Zero technical setup. Open ChatGPT. Paste. Read the output.
Running a 2-day beta before full launch.
Day 1: I send 3 protocols mapped to your exact problem. You run them.
Day 2: 3 questions. 2 minutes. Done.
What you get:
→ 3 protocols to keep forever
→ Zero pitch. Zero call. Zero cost.
What I get:
→ Honest feedback before I scale.
If you run a business with a team comment SEND IT below.
First 5 only.
That’s a solid asset to have built out — especially for that level of founder.
From what I’ve seen, once something like this exists the real challenge becomes less about building more and more about getting it consistently in front of the right people.
A lot of setups stall there even when the offer itself is strong.
Out of curiosity — are you leaning more on inbound right now, or actively pushing outbound to land those first beta users?
Actively outbound right now LinkedIn primarily, direct to agency founders at the $1M–$10M stage. The inbound side is just starting to build.
The distribution problem you named is exactly right. Most setups stall there. That's actually why I'm running a beta fewer users, more direct feedback on which protocols land hardest for which founder stage, before I push volume.
If you want to run it, happy to send it directly. What's the biggest decision that still routes through you that shouldn't?
Interesting that you’re targeting the $1M–$10M stage. That seems like the stage where companies usually aren’t struggling with product anymore, but with scaling, processes, positioning, and acquisition.
Out of curiosity, what do you see as the most common bottleneck at that stage? Is it usually distribution, internal processes, positioning, or something else?
The distribution bottleneck shows up inside companies too, not just in customer acquisition. I’ve seen teams where growth stalls because too many operational decisions still go through one or two people.
Wouldn’t be surprised if in many small teams 50%+ of decisions could be systemised or delegated but just haven’t been documented properly yet.
At that stage it's almost always the same thing wearing different masks: the founder is still the system.
Not the product. Not the market. The founder hasn't been replaced by documented logic yet so every process that looks like it's running independently is actually one founder-absence away from breaking.
Distribution stalls because the founder is the one who knows which clients to prioritize. Hiring slows because only the founder can evaluate culture fit. Client escalations pile up because no one else has the authority or the criteria to resolve them.
Your point on 50%+ of decisions being systemizable is exactly right. In my experience auditing these, it's closer to 70%. The decisions that genuinely need the founder are fewer than they think but nobody has written down the criteria that would let someone else make the other 70%, so everything routes up by default.
That's the gap the protocols fill. Not automation for its own sake just decision logic that exists outside the founder's head for the first time.
This is a strong concept — the positioning around “protocols” instead of generic prompts is smart.
I’m currently running an electronics marketplace, so we’re right in that messy stage between traction and scale where systems start breaking.
A few of these immediately stand out:
Founder Dependency Audit (this is very real — too many decisions still route through me)
Competitive Moat Audit (we’re in a crowded space, so positioning matters a lot)
Content Atomization (we’re pushing social but consistency is a challenge)
What I’d be most curious about:
How tailored are these protocols to different business models?
For example, marketplaces have very different dynamics compared to SaaS:
supply vs demand balancing
trust + buyer protection
conversion friction on high-ticket items
If the outputs can adapt to that level of nuance, this could be very powerful.
Also, how do you prevent outputs from being too “generic ChatGPT”? That’s been the biggest issue with most prompt packs.
Happy to test if you’re still selecting — this is right in line with problems we’re actively working on.
The protocols adapt to the business model through the input layer you paste your actual context, not a generic description. A marketplace has completely different decision bottlenecks than SaaS, and the output reflects that because it's working from your real data, not a template.
On the generic ChatGPT problem the architecture is what prevents it. Role, context, constraints, and output format are all locked before you add your data. The model doesn't wander because it has no room to.
You mentioned Founder Dependency Audit, Competitive Moat, and Content Atomization. Those are three different vaults. Start with Founder Dependency it's the most immediately deployable and you'll see within 4 minutes whether the output quality matches what you need.
Sending it to you directly on email check your inbox in the next few minutes. Start with the Founder Dependency Audit. You'll see within 4 minutes whether the output quality matches what you need.
Interesting approach. Curious how you’re deciding which protocols to map to each founder’s situation. Is it based on a short intake, or more general patterns you’re seeing across businesses?
Both actually there are patterns that show up consistently across every $1M-$5M service business (decisions that always bottleneck at the founder regardless of industry), and then there's a one-question intake: what type of decisions still land on your desk every week that shouldn't. That answer maps directly to one of 5 vaults. Takes about 30 seconds. The protocols do the rest. Are you running a team right now?
Not running a team at the moment, but I’ve seen that bottleneck pattern a lot. Decisions tend to accumulate around the founder without anyone really noticing until it slows everything down. Interesting that it maps so consistently across different businesses.
That accumulation pattern is exactly it and most founders don't catch it until a decision they should never be touching lands on their desk at 11pm.
The protocols were built around that moment. The ones that matter most aren't about having a team yet they're about building the decision logic before you need one.
Curious what kind of decisions are still routing through you.
Mostly the ones that feel small at the time but keep repeating. Prioritisation, what not to do, when to stop something.
They don’t look like bottlenecks individually, but over time they stack and slow everything down. That’s usually when you realise it’s not a one-off, it’s a pattern.
Interesting approach. I’ve noticed something similar while exploring AI tools for WorkflowAces — a lot of the real value isn’t in the model itself, but in how the prompt and workflow are structured.
How long did it take you to build all 440?
Ryan exactly right. The model is commoditized. The architecture around
it is where the leverage lives.
2 years. Built them by mapping real operational failures across businesses
hitting the $1M–$10M wall decisions that should not route through the founder,
delivery that depends on judgment that was never documented.
Each protocol went through multiple iterations until the ChatGPT output was specific enough to deploy same day.
What are you building with WorkflowAces?
Totally agree with that. Mapping real operational problems first and then designing the prompt around them sounds like the right way to do it.
With WorkflowAces I'm basically exploring and reviewing AI tools that help automate everyday workflows — things like content creation, research, lead discovery, and small automations that save founders time.