Manish Singhmanishsinghkumar.in
Manish Singh
Manish SinghManaging Consultant, Wipro Consulting

Product and transformation leader with fourteen years of building things that did not exist yet, from connected medical devices to procurement programmes. I now build working AI tools for real operations problems, and help organisations adopt them at a pace people can absorb.

See the work Get a CV for your role

Try the engine. Launch six at once, then press Pace the rollout. That is the whole thesis.

Live The absorption engine absorbed 0 · spilled 0

Absorbing nicely. Someone even read the SOP.

14years building things that did not exist yet
120people in a programme function I built from 16
11working apps in the lab, sources checked
60logged sprints of a business run by an AI agent

Systems I run with AI

AI does the recurring work. A human keeps the decisions. The guardrails matter as much as the build.

Live
AI-operated business · AI literacy and brain health

An AI-run course business

An AI agent operates a live course site in logged sprints while every business decision stays with me.

60sprints logged
31posts live
4paid courses
Read the case Visit unai-labs.com

Three calls that kept it safe

  1. The agent never touches money or logins. It will not enter credentials or place an order. Payment setup waits for me, even when that blocks revenue.
  2. The live site is the source of truth. Every sprint begins by comparing the real site with the log, so drift is caught instead of assumed away.
  3. Decisions are separated from tasks. Pricing, ISBN, naming and gateway activation sit in my backlog. The agent does the work; I keep the calls.
Live
Procurement · Self-publishing library

The Procurement Codex

A reference library that builds, checks and publishes itself, one source-to-pay step per episode.

15episodes
$0running cost
1publish gate
Read the case Open in the lab

Three calls that kept it safe

  1. Nothing ships without a self-check. Automation without a gate is just faster mistakes.
  2. Build the engine once. Shared components keep quality consistent across all fifteen episodes.
  3. Say what it is. Every page states it is generated and directional, and asks readers to verify against primary sources.
Demo in preparation
Consulting diagnostics · Private build

DISCERN

Turns stakeholder interviews into an engagement brain: problems, hypotheses, levers and value cases, each traceable to what people actually said.

4domain packs
4build sprints
0fees set by the model
Read the case

Three calls that kept it safe

  1. Fees are computed by rules, never by the model. Commercials must be reproducible. The model proposes scope; deterministic logic prices it.
  2. Every claim traces to a verbatim quote. Insights carry the exact interview words behind them.
  3. It is tested blind. A synthetic client with deliberately planted contradictions checks whether the pipeline catches what a partner would.

All 5 case studies →

From the lab

Simulators for the mechanisms leaders keep getting wrong. Side effects may include sudden clarity in steering committees. All 11 apps →

No.01 · SUPPLY CHAIN

The Telephone Effect

Nudge a retailer's forecast error and watch it grow as it travels up the chain.

±5% at the store → 37% at the factory
Deterministic modelRuns in browser
No.04 · AI AT SCALE

AI Fleet Economics

Four levers a FinOps team pulls on a GPU fleet, with the monthly bill reacting live.

4 levers → live monthly bill
Deterministic modelRuns in browser
No.07 · AI AT SCALE

One Rulebook

Four AI agents with four levels of autonomy. Apply one policy to all of them and watch what breaks.

4 agents · 1 policy
3D · WebGLRuns in browser
No.09 · LEADERSHIP & CHANGE

The Pressure Line

Load your team's quarter with changes and watch the capacity gauge redline.

initiatives × disruption vs capacity
Illustrative modelRuns in browser

How I work

Three habits, one rule: if a prototype can answer the question, nobody needs a deck.

Evidence first

Every number traced to where it came from. When a source does not hold up, the claim goes, however good it sounded.

Casualties so far: three statistics.

A call, not a menu

Options are cheap. A recommendation with the evidence behind it is what a decision-maker actually needs.

"It depends" is allowed once per meeting.

Prototype over slides

A working model settles in ten minutes what a deck debates for ten weeks. Everything in the lab started that way.

No slides were harmed in the making of this site. None were made.

Writing

All essays →

AI operationsI gave an AI agent a business and told it never to touch the moneySixty sprints of an AI-operated course business, and why the guardrails matter more than the automation.AI infrastructureThe AI buildout is a stack of mismatchesVelocity, economics, value capture and capital risk are each manageable alone. Together they explain why capacity sits idle while bills climb.CapabilityCertified is not the same as changedCertification counts are easy to manufacture. The real test is what people do differently afterwards.

Hiring? Take the CV that fits the role

Same career, same dates, different emphasis. Pick the lens closest to your role.

LensAI and dataRecent AI systems in full, earlier years condensedLensProduct0-to-1 builds and regulated platformsLensProgramme and deliveryTeams scaled, portfolios governedLensStartup and scale-upMany hats: product, teams, structureLensAgile coachingFrom one scrum team to release trainsLensSupply chainProcurement, planning and operations

Curious, hiring, or ready to argue about AI adoption?

All three are welcome. The assistant answers questions about my work in seconds. I answer the rest myself.

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