Not many know this about me, but I am a huge fan of the gilded age and what America stood for in those times and what those great humans accomplished.
Before electricity was the steam engine. It was located in a separate floor/building but with a central shaft transferring energy required for work. All the work had to be concentrated around this line. Initially with electricity, people changed the source from steam to electricity but kept the same design and then soon people started realizing electricity can be distributed, different parts can be operated at different speeds and a whole different production form is possible - modern assembly line was possible.
Similarly, the internet made it possible to ship software everyday, you could just change a file - not having to sell CDs in a retail shop or through complex distributed channels and a patch will take complex delivery mechanisms. Mistakes were expensive, shipping was expensive. With the internet → Agile became the standard, soon the modern PM function was born and whole work was reorganized. Agents are changing the way we work. It is not about just saying - we will put a version of our CD on the internet or replace the steam engine with electricity, but redesigning work.
What is changing
The communication doesn’t require a human node: If my cofounders needs to do pipeline analysis - he just asks salesforce MCP connected to Claude - no finance, sales leader, sales ops comm. If my product person needs to know what happened across all sales calls, she has a claude code instance which helps her. This is all scratching the surface but not redesigning the org for the new electricity, the new internet → Agentic AI and MCPs which can coordinate agent-agent interactions.
I don’t want us to just ship an AI agent product - I think we have to step and truly be the most forward AI company in our category from how we run and think. This is how we will authentically improve our customers' AI journey, our partner’s AI journey and ship at a velocity and learn at a pace that our customers can only dream of.
I think just like new functions were born in the previous shifts
Distributed power → industrial engineer, production floor supervisor
Internet → Product Managers (vs product marketers or program managers), Growth Engineers
AI → AI operators
What is an AI operator?
It is the start of a new role which I believe will exist within all good companies within one year. This person will spend time with the CEO and individual departments to understand
Which are the processes which are most repetitive and time consuming
Which processes are the most labor intensive
Stack rank them in impact on efficiency or velocity
Then work on super short sprint cycles to build AI tools/buy if needed to automate this.
Work with ICs responsible on implementation and education on how to use them
This person will rotate every function every quarter at least once
P.S: Walmart has an AI person in senior leadership whose salary is 2x of the CEO of Walmart.
If successful, we will have this person probably bring on 1-2 people in a year to scale this function.
Metric to track:
$ per employee
AI usage per employee
Tasks fully automated by AI
Eventually, it will show up in $ per employee.
Who will be the best AI operator?
The AI Operator is not an engineer who dabbles in business, or a business person who dabbles in AI. They are a distinct profile.
The industrial engineer was neither a worker or craftsmen, but someone who sat in between and understood time and motion studies and how things were built. A product manager was neither an engineer nor a marketer, but someone who sat in between and understood what needs to be build and how engineers need to be communicated and projects scoped to ship faster.
The strongest AI operator candidates have done at least two of the following: shipped an AI product to real users, run or significantly improved a business function (sales ops, customer success, product), worked at an early-stage startup where they wore multiple hats, or built internal tools for themselves on the daily. The common thread is that they have been close to both the work and the technology, and they have shipped.
The type of person you need - the skill stack if you may: The role requires three layers working together.
Technical: Proficient in Python, comfortable with LLM APIs, prompt engineering, agent frameworks, and workflow tools (n8n, Retool, Zapier, custom scripts). Can build internal production-quality solutions, not just prototypes but working internal tools (doesn’t need to scale to 100s of users yet - forget 1000s of users)
Business: Understands how a function operates—its inputs, outputs, metrics, incentives, and failure modes. A good systems and detailed thinker.
Can identify the 20% of work that drives 80% of a team’s time and determine which of it is automatable. Behavioral: High EQ, low ego. Earns trust quickly. Gets excited by helping others.
They ask a question, from first principles (not best practices) of “Why does this exist” “Does a human need to do it” - the more nodes you remove from organizational coordination - the faster the system moves and learns and grows.
They also default to building over analyzing for days. They treat a two-week sprint the way a founder treats cash runway, every day matters, and the goal is a working system, not a slide deck.
The things that will make them truly great.
An absolute visceral Impatience with process theater. They viscerally dislike work that exists to satisfy a process rather than produce an outcome.Dog and pony shows of coporate world don’t have a place in fast moving AI start-ups.
Domain speed: high intelligence, high IQ [you can’t cheat this part] They can go from knowing nothing about revenue recognition or support ticket routing to understanding the core mechanics in 48 hours.
Taste for the mundane. The highest-leverage automation targets are often boring—data entry, report generation, manual triage. This person finds those problems interesting because the impact is obvious.
Builder: They don’t file tickets and wait. They build the thing themselves, even if it’s scrappy.
Instinct for adoption: They design for the user from the start and obsess over whether people actually adopt what they build.
Comfort with impermanence. They build, hand off, and leave. They don’t need to own the thing forever. Their satisfaction comes from the before/after delta, not the ongoing relationship.
Pattern recognition across domains. After a few sprints, they start seeing that the bottleneck in Sales is structurally similar to the one in Customer Success etc. they learn that most functions are basically humans and information organizing themselves. They find patterns like a chess board and design superior systems.
Their working model
New function every 2 weeks and rinse and repeat every quarter. Their job
Parachute and learn: Spend two days with functional leaders ruthlessly understand key processes, time sucks and efficiency movers. They are NOT order takers from functional leaders, but rather DRIs who will colloborate with functional leaders.
Day 3: Present top most impactful projects to CEO and functional leaders - debate and approve 2 projects with the highest impact
Day 4-5-6-7-8 : Build and iterate till it does its job
Day 9: Full Working Demo to CEO, Functional leader and team
Day 10: Educate team and hand off.
Examples of projects
Sales
Inbound leads response and follow-ups
Pre-call Sales Training - time blocked, agent and AE interaction to educate on everything agent has learnt from org structure (zoom info), to competitive dynamics, case studies, previous call summaries, etc.
Post call salesforce entries and pipeline management and notes to sales leadership
Finance
Using GC.ai or harvey for legal reviews and faster turn-aorund and cheaper
Using AI to train on how to dissect our sales order for our revenue order team
Better tool for understanding revenue ageing, revenue collection and invoicing.
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