There is an algorithm.

An algorithm to launch a new product idea—or spot fatal flaws early and pivot or kill it before you burn money and years.

An algorithm to grow faster than competitors. To create unique value and real moats. To save a dying product. To ship a feature—or get the evidence to kill it. To win market share on purpose, not by luck.

And, most importantly, to build disruptive products.

It’s more than an algorithm. It’s a product operating system for every decision: strategy and tactics, go-to-market and landing page copy, pricing and business model, which market to enter and which to leave.

I call it Advanced Jobs To Be Done.

It is validated in the real world—used in hundreds of companies, with an online course for 10k+ PMs and founders, plus dozens of case studies.

You may not have heard of it—most of the work happened in my home country with zero English content. This book and the course are my way to share it with the world.

AJTBD brings clarity. It can help you you see customers, product, and market through a sharper lens—and do real product work that feels like magic because it’s causal, not lucky.

Founders who truly get AJTBD launch and grow 2x, 3x, even 10x. Product Managers escape the feature factory and create value. Marketers get a repeatable way to build funnels and sharp messaging. Owners see real strategic options.

Let’s begin.

Core ideas of AJTBD

Customer jobs come first. Everything in product flows from knowing the specific jobs of specific people—and helping them do those jobs more effectively.

Needs are primary in theory, but most people aren't aware of their needs. The brain translates needs into jobs—the things we intend to do—and people can describe those. So we work with jobs, not needs.

We can talk to people and learn their jobs.

The brain is always seeking a more energy-efficient way to do jobs. Surprise from a more efficient way = value. Surprise from a less efficient way = problem. Value and problems are prediction errors in relation to predicted energy efficiency by the brain.

Jobs form a graph. Higher-level jobs hold the motivation. Lower-level jobs are the necessary evil you do to achieve higher-level goals.

Anything with a verb is a job. An infinitive verb is a job someone intends to do.

Our product competes to get the customer’s jobs done. We create value by pleasantly surprising customers with a more energy-efficient way to do their jobs.

We create value by lowering cost and simplifying the job graph. There are 20+ value mechanics. Fixing problems and making it cheaper are only two—important, but not the only ones.

“If I had asked people what they wanted, they would have said a faster horse.” Ford wasn’t wrong; asking for features is the wrong way. Study the job graph and invent a more efficient way to do higher-level jobs. The car gets “travel from A to B” done more reliably, faster, and with comfort. People don’t ask for it—but they are able to see and try it to feel the value and switch.

Different people have different success criteria for their jobs. Cheapest. Fastest. Most comfortable. Most status. Same job, different metrics.

If you group people by “similar set of jobs,” you get the most useful segmentation for product decisions. Within a segment, job graphs are similar.

Segmentation is hard and full of traps. Segment by jobs first—not by demographics, personas, or other weak signals. Some criteria produce “false segments” that don’t guide decisions.

Not all segments are equal. Some are complex or unprofitable; others are attractive by unit economics and strategy. Picking the wrong job–segment combo has killed thousands of businesses.

Some jobs form critical chains across roles. In B2B, to win a deal you must get the jobs of all approvers and the decision-maker done. Critical chains between roles enables marketplaces, B2B2B/C and many more business models.

Product communication—ads, landing pages, UI copy—is simply: “Our product will do these jobs for you. If you have fears, it’s safe to proceed.” That’s the core of marketing.

For any business goal there’s a set of strategies derived from the algorithm and value mechanics: find PMF, scale, grow metrics, create disruptive value.

The Algorithm:

  1. Define the business objective. Find PMF, create value, scale, grow conversion, increase AOV, improve retention, escape direct competition, etc.
  2. List risky assumptions, rank them, go test
    • If an assumption fails → ☠️ kill the idea.
    • If you reach the assumption “we can achieve the objective by creating customer value” → go to Step 3.
  3. Estimate preliminary unit economics for plausible strategies & segments: target conversions, AOV, frequency, CAC.
    • If there are no viable strategies and the unit economics will not work → ☠️ kill the idea.
    • If strategies exist and the economics could work → Step 4.
  4. Hypothesize strategies that could solve the objective on top of your hypothesized job graphs of current and potential segments.
  5. Do market research (qualitative + quantitative) to learn jobs, job graphs, and segment attributes where those strategies may apply.
  6. Apply the strategies to the research outputs—using the Step-4 ideas and the broader 80+ strategy toolbox.
  7. Prioritize hypotheses by potential profit (if you can model unit economics) or by RICE if you can’t.
  8. Test remaining assumptions—technical feasibility, UX clarity, can we hit target conversions—until each hypothesis is either killed or delivering target profit.

I claim that every successful product journey follows this logic—consciously or not. What you’ve just read is a simplified version; the book and course go deep into strategies and edge cases.

Creating Products Is REALLY HARD

You walk in fog. Uncertainty is high. Competitors don’t sleep. Anxiety, doubt, second-guessing. In a company role, you juggle stakeholders and politics just to be allowed to do your job.

For years I was stressed and frustrated. I read the books, watched all the talks, memorized frameworks. Still no system. Nothing causal to lean on.

YC and everyone else kept saying: “Fix customer problems.” I fixed problems—until I noticed most things I buy are not to fix a “pain.” Strolling through a mall, I asked: what “problem” do Nike sneakers, Starbucks coffee, or a Chanel bag fix? Most purchases aren’t about pain.

Case studies say “we grew X%.” My question: “Great. How do I repeat it?” Silence.

Breakthrough products don’t win because they fix problems; they win because they follow a (mostly hidden) algorithm. Few know it, fewer monetize it with market share and ongoing self-disruption.

Everyone ships features by gut. It doesn’t work well

Every year I train thousands and consult dozens of companies. Most teams ship ideas without research. Stakeholders get “brilliant” ideas: copy that feature, build a marketplace, let’s add this, and that.

It “works” with a 10% hit rate. My mantra: 9 of 10 hypotheses fail. If you ship your genius ideas, expect 9 of 10 to miss. That is painfully inefficient.

Lean helps—at least you test fast and cheap.

The problem with gut-driven shipping is the lack of cause-and-effect. You miss the most effective launch and scaling strategies and step on avoidable landmines. Months and hundreds of thousands lost.

Teams using AJTBD lift hit rate to 2–4 wins out of 10. That’s huge. Reaching 4/10 is hard and rare—but moving from 1/10 to 3/10 changes the business.

What Is “Value,” Actually?

We all say “value” to explain why people buy. “This product is insanely valuable.” “This isn’t valuable to me.”

But what does it mean? I spent four years searching for a practical answer—and couldn’t find a step-by-step way to create value.

Textbook definitions talk about perceived benefits minus costs, functional and emotional fit, and so on. Helpful words, zero algorithm.

What counts as benefit? In what units? How do you compare emotional vs. functional? How do you create value in your product tomorrow morning?

I had to build a practical model—and that’s a core part of AJTBD and you will learn it from this book and my online course.

Jobs To Be Done is a beautiful theory—but still theory

In 2019 I searched for a framework to explain why people buy another pair of sneakers or upgrade an iPhone every year. I found JTBD, read everything, loved it—and still couldn’t apply it.

“I’m launching a product—what exactly do I do?”

“I’m advising a corporation losing share—how do I use JTBD to fix it?”

Huge potential. But no interpretation made it practical enough.

Introducing Advanced Jobs To Be Done

In 2019, realizing no framework gave an algorithm for strategic product problems—or a crisp answer to “what is value?”—I went back to first principles. I read psychology, needs, decision-making. I was building a therapy marketplace as a founder and consulting widely, so I had access to experts and a steady stream of real business cases to test ideas.

A year in, I saw I was reinventing JTBD. I reread all interpretations and found one invariant: People want to move from one state to another (from A to B).

I took that as the core. For the next years, I studied how the mind and brain manage that transition. I asked: Why move? How does one notice the need to move? How do we choose which way to move? Where do products fit? What is value?

Practical, Repeatable, Causal

AJTBD’s goal is to give you algorithms to solve product business problems repeatably, grounded in cause-and-effect.

It’s not another dialect of buzzwords about “hiring products for jobs.” It’s not cargo cult. It’s a tool.

With AJTBD you can:

  • Diagnose a product across 40+ zones of growth opportunities and risk.
  • Segment customers by their jobs (and second-order attributes like demographics, roles, company size).
  • Select attractive segments—including by projected unit margins.
  • Create value—including unique, hard-to-copy, and disruptive value.
  • Communicate value in ads, landings, sales scripts, onboarding, and positioning.
  • Set strategy: GTM, scaling paths, escaping direct competition, building moats.
  • Grow funnel conversion, increase AOV, improve retention.

So you can:

  • Rescue a dying or stagnant product.
  • Launch successfully—or quickly see a bad idea and pivot.
  • Grow an existing product fast and efficiently.
  • And, most importantly, operate with clarity, backed by a causal system.

A key part of AJTBD’s effectiveness is the research engine: interview guides, algorithms for processing qualitative data, and survey design/interpretation—so you can choose which jobs (and whose) to focus on, craft value hypotheses, and rank them.

Who Can Benefit From AJTBD

  • Founders searching for PMF, PMs with stagnation or falling sales, and PMMs tasked with funnel conversion will see the fastest, most visible gains.
  • Heads of Product / CPOs get strategy algorithms—results are bigger, but show over a longer horizon.
  • Designers, analysts, project managers and others influencing product gain deep understanding of motivation, segments, and value—but the payoff is smaller unless you aim to shape product decisions and grow your career.