i was wrong about what marketers wanted.
built v1 of operator23 assuming marketers wanted more power. they wanted less risk.
three things they told me in interviews.
stop asking me to connect gmail before i know if it works.
stop giving me a blank prompt. tell me what other marketers automate first.
stop breaking silently. tell me when something goes wrong and what you did about it.
operator23 is plain english automation for gtm. describe a workflow, watch it run on fake data, deploy when you trust it. every wednesday pull meta ads spend and send me a ctr and cac report. done.
the lesson. marketers do not want more features. they want fewer reasons to hesitate.
i was wrong about activation.
Short: operator23 is plain english automation for non-technical gtm and ops teams. describe a workflow, watch it run in sandbox, deploy when you trust it.
Version 1 problems: thought our low numbers on https://t.co/kRLiwNah0K v1 were a ux problem. they were a trust problem.
20 signups. 2 activations. three weeks of interviews. three patterns.
blank canvas kills conversion. replace empty prompts with recommendations.
credential requests before value kill trust.
never ask for gmail or hubspot access
before the user has seen the product work.
silent failure in the category kills adoption.
if users have been burned before, they assume you are the same.
the lesson. if your activation is low, you are not solving the trust gap.
i was wrong. First version had 20 signups and 2 activations. Then spent three weeks interviewing people who stalled.
operator23 lets you describe a workflow in plain english and run it across your stack. hubspot, gmail, slack, and a few hundred more. Secure AI Agents in minutes.
three things killed it.
- blank canvas. a prompt that says describe a workflow freezes non-technical users.
- credentials before proof. no one connects gmail to a tool they have not watched work.
- fear of silent failure. everyone had been burned by zapier breaking quietly.
v2 fixes all three. recommendations instead of blank prompts. sandbox runs before any integration. self healing when apis change.
the lesson. activation problems in automation are trust problems wearing a ux costume.
@IndexVentures@crosbylegal The thought that lawyers havenβt started changing their own business model is crazy. Many Iβve spoken still bill by the hour.
The first that stop billing hour and start doing have the real MOAT.
Build an agent that notifies with a company report you when an new inbound customer
Takes 30 seconds, goes to gmail, hubspot, and uses any sales tool, and notifies you on slack.
https://t.co/4bOwWaAzKS
The real cost of broken automations isn't the rebuild time.
It's realizing your lead went cold 3 weeks ago because a workflow silently stopped. And you had no idea.
We talked to marketing/ops leads. Same story every time:
Setup takes hours, then you still don't trust it
When it breaks, you're blind
So you go back to doing it manually
Operator23: describe what you want in plain English. Review before it runs. If something breaks, it fixes itself.
Most automation tools work greatβ¦
until real life happens.
β’missing data
β’late replies
β’edge cases
β’things slightly off
Thatβs where workflows silently break.
Weβre building https://t.co/eGlymqnClV for that layer.
Automation that actually holds up.
for all marketeers, https://t.co/kRLiwNah0K lets non-technical operators describe a workflow in plain English and run it across their tool stack, hubspot, apollo, monday, google drive and others.
no builder, no if-then config, just a description and a review step before anything runs.
We talked to marketing ops people recently to validate whether we are solving the right problems. Three things came up every single time.
Setup complexity. People are not afraid of automation in theory.
They are afraid of spending two hours configuring conditions and field mappings, only to have something silently misroute.
The config layer is where confidence dies.
Debugging. When a workflow breaks there is usually no explanation. A trigger did not fire, data passed null downstream, a sequence stopped.
You find out three weeks later when someone downstream asks a question. Nobody knows where it went wrong so they delete it and go back to doing it manually.
No trust without control. Everyone wanted to keep a review step before the system acts on its own.
Not forever, but until it had proven itself across enough edge cases.
The unlock for automation adoption is not fewer steps, it is making it safe to delegate gradually.
What we are building is a system that addresses all three.
Plain English input so setup is fast, step-by-step explanations so debugging is readable, and staged autonomy so trust is earnable.
For founders who have built or managed GTM and marketing ops teams: does this match what you have seen. And is there a fourth problem we are missing.