Co-founder & CEO
Samuel Mirpuri
Samuel is a co-founder of flowscope. He spent his career at McKinsey, leading digital-transformation programs for PE-backed portfolio companies and large enterprises, holds an MBA from Harvard, and is a graduate of MIT. A former Platoon Commander in the Singapore Armed Forces, he writes flowscope's posts on process redesign, the economics of professional services, and where enterprise AI value actually lands.
Posts by Samuel Mirpuri
26 June 2026
How to baseline a process well enough to stand behind a result
An outcome-aligned engagement is only as honest as its baseline, and most baselines are self-reported and wrong. Here is the measurement machinery that makes a before-and-after comparison defensible.
22 June 2026
When not to automate, and what an honest engagement does when the savings don't show up
A clear-eyed account of the workflows that make bad automation candidates, why first principles predict it, and what a vendor actually does when the projected hours never appear.
2 June 2026
How to tell an AI delivery vendor that ships from one that demos
A buyer's procedure for separating vendors that put working software on your data from vendors that sell decks, built on the base rates that explain why most enterprise AI pilots never reach production.
31 May 2026
Why services-as-software firms scale where AI consulting cannot
A services firm that ships software, prices against outcomes, and reuses agents across customers is not the same business as a consulting firm with AI bolted on. The unit economics diverge from inception.
29 May 2026
What an aligned AI engagement actually looks like
An engineer in the customer's environment from day one. Discovery in days. Redesign before automation. Pricing against measured savings. This is what an aligned AI engagement looks like end to end.
27 May 2026
There's a third layer of consulting that nobody has named yet
The consulting market has had two layers for fifty years. A third has been forming as AI spreads: teams that wire AI into live systems, govern them in production, and stay accountable six months after the platform vendor moves on.
25 May 2026
The 80-to-99% problem
Foundation Capital named the ratio: eighty percent of capability with twenty percent of effort gets you to a pilot, and the remaining nineteen percent requires roughly one hundred times more work. That work is engineering, in the customer's environment.
23 May 2026
The unbillable hour
Professional services firms still selling time are watching their revenue base compress into the technology. The unbillable hour is the structural P&L problem at the center of every consulting firm in 2026, and outcome pricing is the only way out.
21 May 2026
Services-as-software is the right frame. AI roll-ups are the wrong one.
Two competing strategies are bidding for the post-SaaS opportunity. They are not the same bet. The roll-up plays for multiple arbitrage. Services-as-software builds the firm with software economics from inception.
19 May 2026
The discovery phase costs three months because it has to, not because it does
Process discovery via interview takes twelve weeks and produces an authored map that stays accurate for about three months. Observation-based agents produce a more accurate map in days. Discovery was the artifact that justified the rate, not the bottleneck.
17 May 2026
The customer all four delivery models leave behind
There are four ways to buy enterprise AI in 2026. Each assumes a customer profile. Each leaves the same business behind: the mid-market operator with no AI team and a manual workflow consuming a meaningful share of payroll.
15 May 2026
Don't automate. Obliterate.
Michael Hammer's 1990 essay is more correct in 2026 than it was then. AI is automating cow paths instead of obliterating them, and the seventy-five-percent reduction nobody captures is the cost.
13 May 2026
Your AI consultants left you a deck. Here's why.
Across thirty engagements with named AI consulting firms, the deliverable at month six is a deck, not software in production. The model serves the customer it was built for. Most operators are not that customer.
11 May 2026
Where this goes next: the system of action
Systems of record are not going anywhere. What changes is the layer above them: the system of action that reads, acts, writes, and stays accountable for the result.
9 May 2026
The state of enterprise AI in 2026: a map
Five delivery models are bidding for enterprise AI budgets in 2026: Big-4 transformation, AI boutiques, SaaS copilots, in-house teams, and AI roll-ups. None serves the largest segment.
7 May 2026
SaaS is dead: long live services-as-software
Two trillion came off the software index in six months. The repricing names what comes after SaaS: services-as-software, where the customer buys the outcome and AI delivers it.