Startups

From the first conversation with a customer to the term sheet, through product-market fit, metrics that mean something, pricing, growth, the lead investor and the side business built on nights and weekends, startups and entrepreneurship as told through the free samples of the Leanpub books about them.

Created from the free samples of 19 Leanpub books and the descriptions and tables of contents of 8 more, with every source cited.

A startup is a new company searching for a business model under uncertainty, as distinct from an established company executing one it already has. The distinction is Steve Blank's, and one of the sources sums up his keynote in a line: startups search and pivot, companies execute, and the two call for different skills.[3] The books on this page were mostly written by people who did the searching: the two compilers of Venture Hacks, who spent four years writing up term sheets and investor behaviour for founders,[2] a marketer who took two startups from launch to an IPO filing,[3] the engineer whose blog became the Lean Startup movement,[1] and a finance instructor who reads every clause of a term sheet as the answer to an information problem.[5]

The Leanpub books on the subject fall into two generations. The first is a set of blog archives from 2006 to 2012, the years in which customer development, the Lean Startup and metrics-driven growth marketing were worked out in public, one post at a time.[1][4][3][2] The second is a cluster of books from 2026 about the solo founder and the side business, in which an AI assistant is the leverage that used to require a team and the first sale, not the funding round, is the milestone that matters.[8][9][10] Between the two sit a practitioner's guide to lean product work,[6] a book on reading business metrics,[12] and a 2026 textbook on how early-stage companies are financed.[5]

This article covers finding a problem and a customer, product-market fit and the minimum viable product, the numbers a startup should trust, marketing and growth, raising money and negotiating the round, bootstrapping and the side business, and building the company itself. Its sources are the free samples of nineteen Leanpub books and the public descriptions and tables of contents of eight more, listed at the end; nothing from any book's paid chapters was used. One of the categories the page draws on is Lean, so many books about Kanban, lean manufacturing and agile delivery were read and set aside as being about something else.

Where to start

A reader with no background and an hour to spare can begin with Learn by Doing, which condenses twenty-four talks in Stanford's entrepreneurship lecture series into a page or two of one-line takeaways each, from the Eventbrite founders on co-founder roles to the founder of New Relic on recruiting; it assumes nothing and reads in an evening.[7] The same reader who wants an argument rather than aphorisms should go to Startup Lessons Learned, the collected posts of Eric Ries from 2008 to 2012, which assume a software product but little else and show the Lean Startup method being worked out with his company IMVU as the running case.[1]

A developer with an idea has two natural first books. Best of Andrew Chen's Blog opens with the author's account of the website he and his friends tried to build as teenagers, and the mistakes in it, from an over-designed database schema to building an object-relational mapper before any user interface, are the ones developers still make.[4] The Lean Product Guide, a short guide from two ThoughtWorks coaches, gives the vocabulary of fit: problem-solution fit, product-market fit, and the balance of desirability, feasibility and viability.[6] A developer who wants to build a software-as-a-service product end to end can follow Building SaaS with Laravel, written for bootstrappers and indie makers, though its author flags it as outdated.[13]

Someone about to raise money should read The Venture Hacks Bible first, for the mechanics of a round from the founder's side, and then Entrepreneurial Finance Technical Note Series for the whole financing lifecycle from pre-seed to exit; the latter is written for senior undergraduates and MBA students and assumes a corporate finance course.[5] Someone with a job who wants a business beside it has three 2026 books: The Austrian Side Business for a service business sold before it is built,[10] Vibe to First Sale: Vibecoding a Lean AI Business from $0 to $29 for a first digital product and a first sale,[8] and The One Person Vibe Publishing Side Hustle for a catalogue of small non-fiction books.[9] For marketing, Startup Marketing is the one book here written by someone whose job it was.[3]

History

The ideas on this page have a traceable lineage in the sources. Customer development came first: Steve Blank's method of treating a startup's assumptions as hypotheses to test with customers, which one source quotes for its definition of customer validation as finding customers who react positively by parting with their money.[3] Eric Ries, guest-lecturing in Blank's class, proposed extending agile software development, which works when the problem is known and the solution is not, into the startup's situation where both are unknown, with product development inside the feedback loop with customers; he called it customer development engineering.[1] Soon after he was describing the lean startup as standing on three legs, agile product development, low-cost and fast-to-market platforms, and rapid-iteration customer development.[1]

The other archives record parallel work. Venture Hacks began in 2007 with hacks on term sheets and board composition, kept a cheat sheet of them, and by 2011 was reporting on the authors' AngelList.[2] Andrew Chen's essays run from 2006 to 2012 and are introduced by Ries himself, who calls the 2010 collection an experiment in publishing and the blog one of the best on entrepreneurship.[4] Sean Ellis's posts from 2008 to 2012 gave the movement a measurable definition of product-market fit and a go-to-market method that sequenced marketing after fit, and recorded the 2010 debate between lean and "fat" startups.[3]

The Lean Startup's reach beyond software shows in the other books. A 2013 collection of music-industry essays profiles a radio startup whose founders read the book and began measuring whether features created value instead of assuming it.[11] A management book on process behaviour charts borrows Ries's distinction between vanity and actionable metrics for leaders in healthcare and manufacturing.[12] Lean Publishing applies iterate, get feedback, pivot and build traction to publishing books, and describes Leanpub as the attempt to implement the idea.[19] The 2026 books belong to a new phase: AI assistants that draft code, copy and whole manuscripts, and a founder whose job is to steer, edit and test them against reality.[8][9] One of them gives a chapter to the "vibecoder" whose problem is an addiction to prototypes.[16]

Customers, problems and fit

Every source that teaches founding starts in the same place: with a problem a particular person has, found by talking to that person, rather than with an idea. The sections below follow that order, from finding the problem to knowing when the product fits the market.

Finding the problem

Andrew Chen's first startup is the cautionary case: an apartment-listings site for which he and two friends designed a database for a rental business they did not understand and built an object-relational mapper before any page a user could see, then gave up after months with nothing but back-end infrastructure.[4] His lessons from a second failed idea are the ones repeated across the field: new founders spend their time "acting like a business", on business cards, office space, a big team and financial models, when the risk that matters is market and consumer behaviour rather than whether the software can be built.[4] He also ranks the ways a founder can know the customer, from being the customer, through having a partner or friend who is one, to learning indirectly or not at all, and argues that the risk of intuition failing accelerates down that ladder.[4]

The 2026 books put the same point as a rule for choosing. The first-sale playbook says to pick pain, not ideas: a good first problem is urgent, specific and solvable, held by a small reachable group the founder has proximity to, and a problem that describes everyone reaches no one.[8] The side-business book opens with an operations-minded employee who notices duplicate data entry, stalled approvals and handoffs nobody owns, and argues that side businesses begin with narrow operational pains that are too small for a consulting firm and too specific for enterprise software, yet not small to the people living with them; the people closest to a workflow usually know where the waste is and lack only the time, authority and leverage to fix it.[10] The publishing book says that readers buy non-fiction for a result, a fix or a better decision, and that the market is not cruel but specific, so the more concrete the problem the easier the book is to position and sell.[9]

Talking to customers is the method, but the sources are careful about how. The product guide says customers are good at saying what they want and bad at articulating what they need, that three to five interviews are not statistically significant but point to what quantitative data should then confirm, and that a team should start from a hypothesis about its customer types rather than from whoever is available.[6] Ries warns of the opposite failure, the team that does whatever customers say: LiveJournal, in the account he cites, listened to early adopters who did not want the site to become mainstream and paid for it, which he reads as confusing the tactic, listening, with the strategy, learning.[1]

Product-market fit and the minimum viable product

The product guide lays out the fit journey as a sequence. Problem-solution fit is the early work of validating that the right problem is being tackled; product-market fit is validating that customers will buy a thin slice of the product, commonly called the minimum viable product, and which customer types and market segments it appeals to; only then does the work turn to scaling, and throughout, a solution has to meet the three questions of whether customers will adopt it, whether it can be built, and whether it meets the organisation's goals.[6]

Sean Ellis tried to make the concept measurable. Quoting Marc Andreessen's division of a startup's life into before and after product-market fit, he proposed asking existing users how they would feel if they could no longer use the product, and set the threshold at forty per cent saying they would be very disappointed, after comparing results across nearly fifty startups; those struggling for traction were always under it.[3] Before fit, he argues, a startup should keep its burn low, keep the founders talking to users, and resist hiring vice-presidents of marketing and sales who will add to the burn without solving the problem, which may need significant product revisions or a restart of the vision.[3] Drew Houston's account of Dropbox, as Ellis reports it, modified "launch early, launch often" into "learn early, learn often" because of the data users entrusted to the product, and observed that Dropbox would never win on a feature matrix against every other product.[3]

Ries supplies the test of what counts as progress. At IMVU his team wrote thousands of lines of well-tested code to interoperate with instant messaging networks; the code worked exactly as specified, but positioning the product as an add-on to other networks confused customers and contradicted its value proposition, so all of it was thrown away, which is why a line of working code is not always a unit of progress in a startup.[1] The 2026 first-sale book sets the bar lower still and more concretely: a first sale of twenty-nine dollars is proof of demand rather than revenue, chosen because it is low enough to sell without a call and high enough that the buyer expects something real; likes, sign-ups and compliments are not commitment and money is; and if the first version cannot be built in forty-eight hours of focused work, it is too big to be a first-sale product.[8] Pre-selling, in that book, is honest when it states the outcome, the deliverable, the price, the date and a refund if the promise is not kept.[8] The SaaS tutorial makes a matching engineering choice, taking a fee on each payment rather than running subscriptions so that the minimum product stays small.[13] Lean Publishing applies the vocabulary to books: publish in progress, iterate on reader feedback, pivot until the book is right, then build traction.[19]

Measuring and learning

The startup numbers, in Blank's list as one source records it, are not the balance sheet, income statement and cash flow but cash, the viral coefficient, the cost of acquiring a customer, the burn rate and the average transaction size.[3] Ries's distinction between vanity metrics, which paint the rosiest possible picture, and actionable metrics, whose data must show cause and effect tied to a change in the product or system, has travelled well beyond startups; a book on process behaviour charts adopts it for managers choosing key performance indicators, adding that without it an organisation is just trying improvements at random, and uses the charts to stop leaders reacting to normal fluctuation as if it were signal.[12]

The product guide warns about the timing of measurement. Profit is a lagging indicator, and a new product judged on it will be killed before it has had the chance to show value; the viability of a product in its infancy should be read from leading indicators such as sign-ups and time spent, and funding models have to allow for experiments that disprove a hypothesis, or the business case takes months and the loudest person in the room gets funded.[6] The music-industry collection gives a small example of what changes when a startup starts measuring: Earbits added a search bar so that listeners could start a station by typing an artist, as its rivals offered, and engagement went down, a fact the company would not even have been tracking before it read the book.[11]

Ries also warns against measuring mechanically. Split-testing every release and talking to customers constantly are the two things he most often recommends, yet applied without judgement, in the engineer's habit of "if some is good, more is better", they produce disasters of their own.[1] Andrew Chen's criteria for an "eyeball company", one with many users and no revenue, are of their era but still legible: a hundred thousand or more users as proof they love it, growth that is viral rather than bought, and whether the company does for free what someone else charges for.[4] Ellis's hiring rule follows from all this: his first marketing hire at LogMeIn was a trained actuary, the marketers at the startups he advised were mathematicians, and the casual-games startup his earlier company acquired had been built to cash-flow positive by maths whizzes in their early twenties, who then took over the acquirer's marketing and product teams.[3]

Marketing, pricing and growth

Ellis's starting observation is that most venture-funded startups fail and that a large part of the blame belongs to marketing, specifically to a flawed process at the customer-traction stage; having run marketing at two startups through to their IPO filings, he found that each stage needs different skills, that the earliest stage matters most and is the hardest to get good at because nobody gets enough repetitions, and that option vesting keeps the wrong leader in place for years.[3] His proposal was for a startup to plan from the start on different marketing leaders for traction, for growth to an IPO and for afterwards, which he notes is less radical than it sounds given that a marketing vice-president's average tenure is under two years.[3] The go-to-market method he built on this, the Startup Pyramid, puts product-market fit at the base and treats growth as something to race up to only after the foundation is solid.[3]

Pricing gets its own treatment in the same blog. For a software startup, Ellis argues, optimal pricing mostly means maximising revenue rather than covering a unit cost, because the revenue funds customer acquisition or a free tier that drives adoption; the factors are price sensitivity, marginal cost and growth strategy, and since most startups simply guess, getting the price right is a competitive advantage.[3] Andrew Chen's essays supply the consumer side: a visit to a museum of 1920s to 1950s arcade machines, with their love calculators, fortune tellers and "what do your friends call you behind your back" taglines, leads him to the conclusion that technology changes while the human motives a product can appeal to, narcissism, curiosity and competition, do not, and that Facebook's quiz applications were the same machines.[4]

Tactics for the developer who markets their own product are in Marketing <for> Programmers, whose seven parts, known here only from its contents, cover search engine optimisation, copywriting, analytics, conversion optimisation, statistical significance, email and paid advertising, with an angle for people who control their own HTML and can, for instance, generate images through their own software for image search.[22] The publishing book treats a catalogue as a marketing engine in itself: each small book drives discoverability and cross-sales, teaches which titles and subtitles convert, and can lead readers to templates, newsletters, courses or consulting.[9] Two Nordic APIs books extend the same thinking to an API as a product: The API Lifecycle runs from market research and monetisation models through marketing to retirement,[27] and The API Economy surveys eleven kinds of business that grew up around APIs, from management and testing to documentation as a service.[26]

Raising money

Two sources cover financing from opposite directions: a textbook on why early-stage finance is structured as it is, and a blog of hacks for the founder on the other side of the table.

How startups are financed

The technical notes begin with what an early-stage company lacks: audited statements, analyst coverage, a market price for its shares and a comparable operating history. The problem, the author argues, is not risk, which can be priced, but uncertainty, which cannot, and the staging of capital into rounds is the market's structural response: investors provide capital in increments sized to reach a verifiable milestone, each milestone retires one category of risk, and each retirement unlocks the next tranche, often from a new class of investor.[5] The lifecycle runs from pre-seed, funded by founders, friends and family to prove the problem exists, through seed from angels and accelerators to prove the product, to a Series A of two to fifteen million dollars to prove customers will pay at scale, and later rounds to prove the team can execute; the "Series A crunch" between seed money and institutional traction is structurally wider in Canada.[5] The diagnostic that follows is that a company struggling to raise has not yet reduced the risk its prospective investors care about most, so a financing problem is almost always an evidence problem.[5]

The second note explains the terms. Information asymmetry, in Akerlof's market for lemons, can stop a market forming at all, and the parallel to early-stage capital is direct: investors who cannot tell good companies from bad will price accordingly, good founders will withdraw, and the pool degrades.[5] Adverse selection, before the deal, is why sophisticated investors compete on reputation and network rather than valuation alone; moral hazard, after it, is the rationale for vesting schedules, milestone tranches, board approvals and salary caps.[5] The author's table maps each standard provision, staged financing, board seats, anti-dilution, vesting, liquidation preference, drag-along, participating preferred and pro-rata rights, to the information problem it solves, and argues that a founder who understands this negotiates better than one who treats the terms as positions.[5] Banks do not lend to such companies because their model needs a predictable distribution of outcomes, and startup outcomes follow a power law in which fewer than a tenth of investments produce most of the returns; a venture fund is designed around exactly that distribution.[5]

The practitioners add the founder's view of how much to raise. Ries's blog opens, in its sample, by recommending Paul Graham's essays as the best primer on raising money, with the warning that fundraising absorbs all of a founder's attention and the advice to accept reasonable terms from a reputable investor when offered.[1] Ellis, reading Ben Horowitz's case for the "fat startup", agreed more than he expected: lean is not the end goal, but the companies Horowitz cites had traction, Facebook raised only half a million dollars in its first year, and in Ellis's own startups the purse strings loosened only after users had validated a must-have product, so lean principles matter most early.[3] The lecture notes put it in two aphorisms: capital is always there when you do not need it and unavailable when you desperately do, and how much you raise matters less than who you work with.[7]

Negotiating the round

Venture Hacks' three most effective hacks of 2007 are a founder's negotiating stance in miniature. Create a market for your shares by pitching and negotiating with every prospective investor at once, since focus compounds scarcity and social proof and yields a quick yes or no; create a board that reflects the ownership of the company rather than one investors control through an "independent" seat; and do not let investors set the size of the option pool, the "option pool shuffle", but justify a small one with a hiring plan and so raise the share price and the effective valuation. The cheat sheet adds a focus on share price rather than valuation, accelerated vesting on termination, and unbundling the money from the value an investor claims to add.[2]

The series on finding a lead investor is the archive's most practical. A lead wants at least half the round and often all of it, believes the stock is worth more than the price and needs no social proof, and a financing happens when a lead is found, a term sheet negotiated and followers told to take it or leave it; investors who say they are waiting for a lead are, in the words of the FeedBurner founder quoted there, saying no without saying no, to keep an option open.[2] A seed round, by contrast, can be mass-syndicated without a lead: generate a term sheet with advisers, get feedback on the terms at the end of each first meeting, circulate the sheet with the list of committed investors once enough have said yes, and set a closing two weeks out.[2] When a lead is needed, the three "microhacks" are to ask followers for introductions and read their effort as the signal, to find seed investors who back people, and to find investors who already know the market.[2]

The archive is sceptical about what investors bring besides money. It cites a study in which nearly all investors believed they added value to their companies while under half of the entrepreneurs agreed, and a figure of eighteen per cent of executive hires coming from investors.[2] Its account of the termination of Cisco's founders draws one lesson: there is no such thing as a bad deal as long as the founders understand its pros, cons and possible outcomes, which by their own account those two did not, and every founder should have their own lawyer.[2]

Bootstrapping and the side business

Three books published in 2026 by the same small press describe a different game from the venture-funded one. The first-sale book states its assumptions plainly: the founder is alone, starts at zero, has limited time and wants learning rather than vanity, and these constraints work as a filter rather than a handicap. A venture-backed startup burns cash to buy time; the solo founder buys time with leverage.[8] Its definition of vibecoding is a workflow, not a vibe: the founder defines the outcome and constraints, an assistant generates drafts of code, copy and structure, the founder selects, cuts, edits and tests against reality, and the three roles the founder keeps are strategist, editor and truth-tester. Tool shopping is named as the most dangerous procrastination, and an idea that needs Kubernetes or a mobile app before it can charge twenty-nine dollars is called avoidance disguised as ambition.[8]

The side-business book is for the employed. Its opening chapter follows a man who is not broke but whose family depends on a single income he does not control, and who wants margin rather than theatre: another source of cash flow, however modest, and the experience of producing value for a customer directly rather than through an employer.[10] Its contents then run through Austrian economic ideas, subjective value, dispersed knowledge, opportunity cost and uncertainty, before the practical chapters: choose the buyer before the solution, sell the service before building anything, price the relief rather than the hours, deliver manually with AI as a quiet multiplier, let profit and loss tell the truth, fight the temptation to overbuild, and grow quietly without startup theatre.[10] The publishing book describes a portfolio rather than a product: around twenty small books published on the side over seven years, half of them with AI assistance, for about two hundred thousand dollars of revenue; its napkin maths starts from a ten-dollar ebook selling a handful of copies a day and asks what five or fifteen such books become, and its central claim is that AI changed the economics of production but not the economics of trust.[9]

Other side-business models in the library are narrower. Amazon KDP for Introverts, known here from its description, pitches self-publishing on Amazon as a low-contact business for introverts, from choosing durable niches and validating ideas to tracking monthly profit toward a sellable catalogue.[20] AI Money Systems opens with the claim that most people have a throughput problem rather than an income problem, and treats freelancing platforms as the fastest on-ramp to a pipeline of AI-assisted work priced by outcome rather than by the hour.[15] The Little Book of Portfolio Management scales lean portfolio management down to a solo founder with too many ideas: make the work visible, tie it to strategy, prioritise by value rather than urgency, and keep a sustainable cadence.[21] Kill The Good Options diagnoses the same founder's problem as saying yes to too many good options, which dilute rather than compound, and gives its founder story a chapter titled after the wedge the founder keeps avoiding.[16] The SaaS tutorial belongs here too, written for solopreneurs and indie makers and building one deployable payment product from wireframes to deployment.[13]

Building and running the company

The lecture notes are at their best on the founding team. The Eventbrite founders say that co-founders should not overlap, should have complementary skills and clearly defined roles in leadership, and that culture is what keeps a team centred; they advise healthy paranoia, since things shift rapidly and complacency is death.[7] Two speakers call founding lonely and say to surround yourself with people who bring out your best; the founder of New Relic adds that recruiting continues after people join, with a check at three months.[7] Andrew Chen's account of his first company shows the failure mode: a large group of smart friends with no clear roles got bored and drifted away until three were left.[4]

Growth brings its own discontinuities. Ries describes what the chasm feels like from inside: a well-run team with a history of steady progress keeps executing, delighting customers and learning, and nothing works any more, because in a phase change the things that made the company successful stop working, so the only preparation is to talk about it before the malaise makes talking hard.[1] He also describes the product manager in a startup still working in a waterfall, writing specifications in large batches, and the acrimony when features come out late and different from the spec.[1] Blank's line, recorded by Ellis, is that product management and customer development are different jobs, and product managers must be deprogrammed before they can do the latter.[3] Product Management, by a product leader at two software companies, argues from the other side that product owner and product manager are one role, and includes a short guide for startups.[18]

The books on scaling are written by people who lived through it. The Ultimate Guide to Remote Work is Zapier's running account of its own remote team as it grew from three people to more than two hundred, covering hiring, culture, evaluating employees, retreats, time zones and burnout.[25] Amazing CTO asks the reader to picture a CTO who made her career in startups and large companies, and its appendix holds a Startup Phases model and rules for scaling a team tenfold.[17] The Mistakes That Make Us opens with an infomercial entrepreneur whose bank held two million dollars after a thirty per cent defect rate nearly sank his company, and draws from it the point that entrepreneurs need a continuous flow of cash to stay alive, before distinguishing planning mistakes from execution mistakes.[14] The music-industry collection shows the economics of a two-sided startup: Earbits sells airtime to bands, and the business only works if a band that buys a promotion recoups its cost in concertgoers and comes back.[11]

Planning tools from adjacent fields round out the set. Impact Mapping links a measurable business goal to the actors who can move it, the impacts wanted from them and the deliverables that might produce those impacts, with an "earn or learn" step for prioritising.[23] The Agile Agency applies Scrum and Kanban to a creative agency and gives one chapter to the Lean Startup, the Business Model Canvas and the Lean Canvas.[24]

Sources

Every source is a Leanpub book. The note after each says which part of it was read; where no sample was available, only the public description and table of contents were used.

1.
Startup Lessons Learned, Eric Ries: All Seasons: Every Post from the Startup Lessons Learned Blog Free sample: the posts from August 2008 onward, among them Paul Graham on fundraising, customer development engineering, not crossing the chasm, the product manager's lament, and when not to listen to users. 2012. Free sample: PDF · EPUB
2.
The Venture Hacks Bible, Babak Nivi, Naval Ravikant Free sample: the posts from January 2008, the top three hacks of 2007, the termination of Cisco's founders, how well investors recruit, and the three-part series on finding a lead investor. 2012. Free sample: PDF · EPUB
3.
Startup Marketing, Sean Ellis: Unlocking Startup Growth Free sample: posts from 2008 and 2009 on optimal pricing, the launch process, hiring a mathematician, the Startup Pyramid and product-market fit, lean versus fat startups, and notes on Steve Blank's and Drew Houston's conference talks. 2012. Free sample: PDF · EPUB
4.
Best of Andrew Chen's Blog, Andrew Chen: 2006 - 2010 Free sample: Eric Ries's introduction and the essays of 2006 and 2007, on monetising video, the author's first website, designing for other people, eyeball companies, and what arcade machines teach about human nature. 2012. Free sample: PDF · EPUB
5.
Entrepreneurial Finance Technical Note Series, Bruce Everitt: Foundations for Angel, Venture, and Private Capital Investment Free sample: front matter and the first technical note, on the financing lifecycle from pre-seed to exit, information asymmetry and the deal terms that answer it, and why banks cannot lend to early-stage companies. 2026. Free sample: PDF
6.
The Lean Product Guide, Linda Luu, Paulo Caroli: A practitioner's guide to building viable products customers love. Free sample: the Determining Fit section, with problem-solution and product-market fit, desirability, feasibility and viability, leading and lagging indicators, and a customer research FAQ. 2017. Free sample: PDF · EPUB
7.
Learn by Doing, PersonalOpz: Notes on Entrepreneurial Thought Leaders Volume 10 (2014-2015) Free sample: the preface and the notes on five of the twenty-four lectures, by the Eventbrite founders, Liz Wiseman, Tina Seelig, Matt Rogers of Nest and Lewis Cirne of New Relic. 2015. Free sample: PDF · EPUB
8.
Vibe to First Sale: Vibecoding a Lean AI Business from $0 to $29, Finxter Free sample: chapter one, the first sale as proof of demand, the solo founder's constraints, the barebones stack, vibecoding as a workflow and the loop from problem to first sale; no table of contents was available. 2026. Free sample: PDF
9.
The One Person Vibe Publishing Side Hustle, Finxter: Build a Portfolio of Small Nonfiction Books With AI, Lean Systems, and Zero Team Free sample: the note to the reader, the table of contents and chapter one on the one-person publishing business, with the napkin maths of a catalogue. 2026. Free sample: PDF
10.
The Austrian Side Business, Finxter: Use Austrian Economics to Build a Profitable, AI-Assisted Business Without Quitting Your Job Free sample: the about page, the full table of contents and the opening of chapter one; the practical chapters are known from their titles. 2026. Free sample: PDF
11.
Divergent Streams, Kyle Bylin: Reflections and Explorations of the Modern Music Industry Free sample: essays including the profile of Earbits and its adoption of The Lean Startup, and pieces on streaming and the marketing funnel. 2013. Free sample: PDF · EPUB
12.
Measures of Success, Mark Graban: React Less, Lead Better, Improve More Free sample: chapter one on the metrics roller coaster, what the right metrics are, vanity versus actionable metrics, and the dangers of arbitrary targets. 2026. Free sample: PDF · EPUB
13.
Building SaaS with Laravel, Max Kostinevich: [PLEASE NOTE: THE BOOK IS OUTDATED] Learn how to build and launch a real-world SaaS application in just a few weeks. Free sample: the introduction, what the PayMe product does, prerequisites and the start of the wireframing and database design chapters; the author flags the book as outdated. 2019. Free sample: PDF
14.
The Mistakes That Make Us, Mark Graban: Cultivating a Culture of Learning and Innovation Free sample: the introduction and chapter one, Think Positively, with the Kevin Harrington story and the definitions of planning and execution mistakes. 2026. Free sample: EPUB
15.
AI Money Systems, Finxter: The Finxter Playbook for AI-Driven Wealth Free sample: the front matter and chapter one on the AI-enhanced freelancer; the other seven earning identities are known from the description. 2026. Free sample: PDF
16.
Kill The Good Options, A. C. Weishaupt: To Make Space For The Great Ones Free sample: the table of contents and chapter one, the story of an over-committed product leader; the founder and investor chapters are known from their titles. 2026. Free sample: PDF
17.
Amazing CTO, Stephan Schmidt: The missing manual for managing Free sample: the foreword, the author's story and the case for soft skills; the Startup Phases model and the rules are titles only in the sample. 2026. Free sample: PDF · EPUB
18.
Product Management, Joaquim Torres (Joca): How to increase the chances of success of your digital product Free sample: the opening on product owner versus product manager and how the roles relate; the startup guide is known from the contents. 2020. Free sample: PDF · EPUB
19.
Lean Publishing, Peter Armstrong No sample: from the description and table of contents. 2026.
20.
Amazon KDP for Introverts, Finxter No sample: the download failed, so from the description only; the book has no public table of contents. 2026. Free sample: PDF
21.
The Little Book of Portfolio Management, Tom.perry@acm.org: A Guide for Entrepreneurs and Small Businesses No sample: from the description and table of contents. 2025.
22.
Marketing <for> Programmers, Jack Kinsella: Primer on SEO, Conversion Rate Optimization, Paid Adverts (Adwords, Facebook Ads), Google Analytics, and Copywriting No sample: from the table of contents only, since the description is a placeholder. 2016.
23.
Impact Mapping, Gojko Adzic: Making a big impact with software products and projects No sample: from the description and table of contents. 2014.
24.
The Agile Agency, Bart Vermijlen: How Lean and Agile Will Transform Your Creative Agency No sample: from the description and table of contents. 2013.
25.
The Ultimate Guide to Remote Work, Zapier: How to Grow, Manage, and Work with Remote Teams No sample: from the description and table of contents. 2019.
26.
The API Economy, Nordic APIs: Disruption and the Business of APIs No sample: from the description and table of contents. 2016.
27.
The API Lifecycle, Nordic APIs: An Agile Process For Managing the Life of an API No sample: from the description and table of contents. 2015.