AI is a Toolkit, Not a Magic Wand. I Help You Master the Skill to use Tools.
AI is a Toolkit, Not a Magic Wand. I Help You Master the Skill to use Tools.
I’m Jitin Kapila. I help executives move past the “GenAI” noise to build a business architecture that actually ships. No hype. No magic. Just engineering logic applied to the P&L.
[My Story]
I’m an engineer by training and
an AI strategist by practice.
I don’t start with tools and prompts.
Neither I start with Data or Departments.
I start with business logic, constraints, and
economics — then design the simplest system that works.
Because a system built without business
is sure shot recipe for disaster.
Over ~15 years, I’ve worked across complex
environments (including large enterprises)
helping teams translate operational
problems into deployable systems.
Eventually when I see the current state of AI,
nobody tell’s what to use, when to use and where to use.
And we see millions, if not billions getting lost in this chaotic state of AI hype.
So now I am on a mission
To help leaders become AI architects.
→ Choose the right problem.
→ Map a feasible solutions.
→ Quantify ROI before execution.
Why Smart Leaders Get Stuck
Most teams hire people who only know their industry or vertical.
They fall prey to what I call a “Plier Trap”. They forget to look around and keep using age-old techniques to perform modern jobs.
I teach leaders to look sideways. Using proven models from manufacturing and power plant, we have solved to solve business problems that others treat as “magic.”
At the core I operate with a 70/30 Rule:
- 70% of enterprise value comes from “Deterministic Logic” — predictive analytics and optimization.
- GenAI is the interface that helps in making the rest 30% looks smooth.
- Use AI only when it’s the best lever — not because it’s trendy.
Let’s fix the P&L first, then we’ll layer the tech.
The problem I keep seeing
The “AI hype cycle” is pushing smart leaders into one of three traps:
- Confusion: GenAI vs ML vs automation—what actually matters?
- Fear: “I’m not AI-native; I’ll fall behind.”
- Unclear ROI: pilots launched without a measurable business case.
The solution isn’t more prompting tutorials.
You don’t need to be a coder. You need to be an architect.
A short story
Predictive Physics in the Sales Pipeline.
An automotive giant was stuck at a ~4% lead conversion rate.
They were treating it as a binary “buy/no-buy” prediction.
I treated the sales cycle like a Manufacturing Line under stress.
Then we applied a “Time-to-Failure” lens to predict exactly when an interaction would stall.
By treating customer behavior as a physical process rather than a random event, we improved conversion from 4% to 11%—a 2.7x lift in revenue without adding a single “magic tool.”
If you’re a VP/CXO/Leader asking:
- “Does this problem actually need AI?”
- “What is the simplest solution that will move the P&L?”
- “How do I prove the ROI to a CFO/Business before we build?”
You’re in the right place.
Choose Your Level of Implementation
The Intelligence Diagnostic
2-3 week “Red Team” logic audit for enterprises.
The AI Profit OS
3-day strategic sprint for leaders to master my framework.
The Weekly Breifings
Deep-dives into the physics of business. Stay sane in AI hype.
Final note
If you’re serious about operationalizing AI, the fastest path is CLARITY:
the right problem, the simplest solution, and ROI you can defend.