Posts by Samuel Mirpuri
- 21 September 2026
Why a frontier-model company is not the natural home for this work
The large AI labs are building forward-deployed services arms in 2026, and the structure of those arms is the answer to whether they should do this work themselves. - 16 September 2026
How enterprise AI procurement is changing
Buyers are moving from evaluating advertised AI capability to validating production results on their own data. The shift is a rational response to the gap between AI spending and results, and it favors providers that can show a running result over a demonstration. - 14 September 2026
Process redesign inside a freight broker or third-party logistics provider
A freight broker is one instance of the horizontal back-office pattern, in an industry where thin margin makes every transaction-level touch consequential. Here is what the redesigned back office actually does, load by load. - 11 September 2026
How a forward-deployed engineering organization is actually built and staffed
The hard part of delivering working AI on a client's systems is staffing a role that combines production engineering, client elicitation, and judgment about exceptions, and that combination is what limits the model's scale. - 4 September 2026
Process redesign inside an accounting firm
Inside an accounting firm, the binding constraint is people, not budget. That turns automation into a capacity question, and the redesigned workflow is how a firm takes on more work without hiring people it cannot find. - 2 September 2026
The consulting industry under AI, in the data of its own restructuring
The repricing of consulting is no longer speculative. The 2025-26 layoffs and the slow move toward outcome-based fees expose a mechanism: the major firms sell human hours, and AI reduces the hours each piece of work requires. - 21 August 2026
Process redesign inside an IT managed services provider
An MSP runs on technicians clearing tickets, alerts, and reports, and its margin tracks how much each one can carry. Here is the redesigned internal workflow, and why the buyers rolling these firms up care. - 14 August 2026
Build, buy, or hire an AI capability: the decision an operator actually faces
Before you evaluate any AI vendor, you face a prior decision: build the capability in-house, buy a working result, or hire for it. The choice turns on three quantities you can estimate. - 12 August 2026
The AI adoption gap by company size, and the mid-market's advantage in time to production
Adoption rises with firm size, not the reverse. The mid-market starts behind on the headline rate and can close it fast, because the path from decision to a working deployment is short. - 7 August 2026
Process redesign inside a wholesale distributor
In distribution, the labor sits in order entry and pricing exceptions, not the catalog. Walking order-to-cash at the line level shows why transaction efficiency decides where thin margins land. - 31 July 2026
What the operator's role becomes after the manual work is automated
When an assistant compresses the experience curve, the residual human work moves toward judgment, exceptions, and oversight. The labor economics says this is measurable, and it tells you who to hire and how to train. - 27 July 2026
Process redesign inside an insurance brokerage
A brokerage controls its margin through administration expense, not commission, and that expense concentrates at renewal. We walk the renewal workflow and show what an agent does and what stays with a licensed broker. - 17 July 2026
Process redesign in healthcare revenue-cycle management
Revenue-cycle management is one organization moving claim data between systems, and the denial benchmarks are public enough to redesign the work against. Here is the rebuilt workflow, and why the recoverable share of a denied claim falls the longer it sits. - 15 July 2026
What changed in model cost that makes this work now
The make-or-buy math on automating a document-heavy process flipped because the unit cost of running a model collapsed, not because any one capability arrived. Here is what a non-technical operator should take from the cost curve. - 10 July 2026
Access is the moat, not the algorithm
When any competitor can generate equivalent agent code, the scarce asset is permission to write into a customer's production systems and the accountability that earns it. Why outcome-aligned pricing and embedded delivery are the structures that win and keep that access. - 8 July 2026
The context flywheel: how each engagement makes the next one cheaper and the agents better
In AI services, code is becoming copyable and cheap, so it cannot compound into a moat. What compounds is accumulated context: the library of exceptions, document variants, and write-back patterns that each deployment teaches the shared agent infrastructure. This post states that loop literally and argues why it is a context flywheel a new entrant cannot buy. - 6 July 2026
Where value accrues when the code is free: the cost anatomy of an AI services engagement
When model inference and code generation cost almost nothing, the dominant terms in an AI services engagement become context acquisition and the human-in-the-loop exception tail. A line-by-line walk of which costs fall toward zero and which stay. - 3 July 2026
Why an agent does discovery and delivery better than a consultant does either
A consulting engagement loses information at every handoff between discovery, redesign, build, deployment, and monitoring. One agent holding the whole arc removes the self-report gap and the handoffs at once, which is where the accuracy and the speed come from. - 1 July 2026
Forward-deployed agents, not just forward-deployed engineers
The third-layer story has centered the scarce human forward-deployed engineer. The next move is that agents do most of that work, observing, mapping, building, and monitoring, while a small human core keeps the judgment and accountability that model capability relaxes but does not remove. - 29 June 2026
Code was never the moat: context is the only durable asset in AI services
The deliverable a services-as-software firm sells and the asset that makes it defensible are two different things. As model inference collapses in price, the code an agent runs commoditizes, and the durable moat moves to the observed, accumulated context of how a specific business actually runs. - 28 June 2026
A map of who else sits in the third layer
The forward-deployed services model has gone from a Palantir curiosity to a contested category with labs, vertical startups, and services firms all in it. Here is who's in it, and where an independent mid-market implementer sits. - 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 rate that most organizations have not yet scaled AI beyond pilots. - 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 length of the discovery phase is a business-model decision
Interview-based process discovery produces an authored map that starts going stale the day it ships. Observation-based agents produce a more accurate map in days and keep it current. The duration of discovery is set by the engagement model rather than by the work. - 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
Why your AI consultants left you a deck
By month six of a typical Big-4 AI engagement, the deliverable is a deck and a pilot proposal, with nothing written to a system of record. 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 dollars came off software stocks, the steepest non-recession drawdown in decades. The repricing names what comes after SaaS: services-as-software, where the customer buys the outcome and AI delivers it.