SOFT ENTRE 432 midterm

software entrepreneurship

process of identifying and capitalizing on business opportunities through the creation and delivery of innovative software products/services.

combines technical expertise with business strategy, focusing on solving market problems, building scalable solutions, and generating value.

tribal knowledge

refers to the unwritten or poorly documented, informal knowledge and expertise accumulated by individuals within an organization/group, often passed through experience or word of mouth.

can be critical to operations but is typically not accessible to everyone.

venture capital

raise funds from investors to accelerate business growth.

enable rapid hiring and tech investment.

greater focus on scaling quickly.

provides mentorship and strategic support.

product market fit process

ideation →

fundraising →

go to market →

repeat.

ideation elements (4)

problem identification.

product conceptualization.

customer discovery.

market analysis.

fumdraising elements (2)

story development.

investor pitching.

go to market elements (4)

focus.

channel analysis.

message experimentation.

pricing.

start simple →

← iterate

important entrepreneur traits

deep customer empathy.

strong product orientation.

sales and selling- all the founders and most of the early employees must always be selling to customers, investors, employees, and each other.

cliche entrepreneur traits

grit.

hustle.

passion/perseverance.

tenacity.

creativity.

hunger.

thick skinned.

flexibility- bendable/open to uncomfortable change.

optimism- unbridled.

why be an entrepreneur?

strong passion to solve a problem, esp for a particular constituency.

want a high amount of agency over how time and efforts are spent.

emotionally/intellectually aligned with a mission.

want to solve a problem people said can’t/shouldn’t be done.

passionate about the work, want time and effort to matter.

want a seat at the table- control, a voice/vote.

want to solve bigger pieces of the puzzle.

don’t trust authority to do the right thing.

don’t want to be pigeon holed- want to contribute to multiple areas of the business, wear multiple hats, be a generalist.

why not be an entrepreneur?

limited resources and time.

have other higher priority responsibilities.

low risk tolerance.

thin skinned.

need for/prefer structure.

need predictability- knowing what the long term plan to be more mentally/emotionally/technically prepared.

need to know where the bar is and need it set.

don’t like wearing multiple hats- like to specialize in one very narrow domain.

want to maximize income predictably- make a ton of money and buy a yacht.

extrinsic vs intrisic motivation

autonomy.

mastery.

purpose.

difference between startups and other challenging endeavors (college)

startups:

loaded with uncertainty and open ended.

are emotional with lots of ups and downs/highs and lows.

have no predetermined time frame.

offer no predetermined next steps after it’s over.

pays poorly, unless there is a successful exit.

talent or effort in grit?

talent * effort = skill.
skill * effort = achievement.

ways to develop grit

discover your interests.

practice.

develop and define a sense of purpose.

nurturing hope → perseverance → grit.

being a student of startups characteristics

need to be humble students of all things startups.

know it alls fail.

comparables- given the complexity and quickly evolving nature of early stage startups, pattern matching against many past and current examples is critical.

true not only for own space or vertical, but also for VC backed startups.

deep knowledge of the VC backed startup ecosystem will be critical for appearing credible and raising money.

likely want to tune vision and strategy to align with the market.

networking.

these are muscles and habits that need to be developed and many first time entrepreneurs struggle with the overwhelming/anxiety provoking aspect.

embrace that many can be thinking about similar, timely ideas as yours- can be validating.

being a student of startups networking

build and work network any way you can- meet ups, industry professionals/events, friends, former co workers…

be a sponge for difference perepectives, knowledge, and advice.

being a student of startups questions to ask (4)

what and who is getting funded? how much is being raised? what are valuations?

what kinds of products/sectors/verticals are getting funded? what isn’t/anymore? what’s hot and not?

what disruptice tech are investors salivating over?

what novel revenue/pricing models/GTM strategies… are considered SOTA and exciting?

being a student of startups comparables (5)

given the complexity and quickly evolving nature of early stage startups, pattern matching against many past and current examples is critical.

tesla- the apple of cars.

shopify- the intel inside of commerce.

robinhood- the spotify of investing.

bloomberg- the operating system for finance.

duolingo- the tiktok of education.

how i built this with Guy Raz format (6)

opportunity.

the journey.

why now?

funding.

co founders.

friction.

where do ideas come from?

i see a problem.

i have an idea for a product.

i’ve got a new technology i’m excited about.

what’s a good idea? big questions/pitfalls to ponder

what problem are you solving for the customer? problem → solution.

what’s the value/benefit of your idea/product in relation to the problem? is there an actual problem or are you offering a better way of doing something? EX: horses vs cars.

is the problem and solution obvious to the customer or will you need to explain/educate them on why they need it?

is the value truly compelling, game changing, or nice to have? vitamin or painkiller?

is the value ephemeral or is it sticky and addicting? if ephermeral, what will make the user engage with it habitually?

more likely disruptive or incremental? company, product, and features.

displacing homegrown/ad hoc solutions?

homegrown/ad hoc solutions good vs bad

good: problem is established and already being solved in an improvised way.

bad: people get attatched to thier own solutins and processes.

startup cliche

is your idea’s value truly a vitamin (compelling, game changing, nice to have) or a painkiller?

the challenge of change

humans don’t like change, we’re creatures of habit.

changing customer behavior is hard, even if the advantages of new solutions are clear.

defensibility

how imitable is your idea/product/tech?

VC: “so why wouldn’t ___ just do this?

VC: “i think your solution is imitable.”

patents- generally not a good strategy for startups.

trouble with AI/ML tech- especially gen AI- a rising tide lifts all boats.

the best defense

happy customers.

high switching costs.

data.

the virtuous cycle of customer data

better data →

faster, more focused product innovation →

better products →

better customer engagement →

more willingness to share data →

repeat.

data powers

machine learning models, recommender engines.

analytics to iteratively improve the product experience.

EX: stitchfix.

innovators dilemma

explains why successful companies often fail to adapt to disruptive innovations despite their market leadership.

concept popularized by harvard professor Clayton Christensen in his book of the same name.

innovators dilemma definition

the challenge established companies face in balancing their focus on sustaining existing markets while being vulnerable to disruptive technologies.

innovators dilemma sustaining innovations

improvements to existing products that cater to current customer needs, often pursued by leading firms.

innovators dilemma disruptive innovations

new tech or business models that initially underperform on mainstream metrics but eventually capture emerging or overlooked markets.

innovators dilemma key insights (2)

conflict between short term and long term goals.

organizational inertia.

innovators dilemma with conflict between short term and long term goals

established firms focus on incremental improvements/sustaining innovations because that’s what their best customers demand.

often ignore disruptive innovations, as these initially serve smaller/less profitable markets.

innovators dilemma with organizational inertia

large companies have structures and processes optimized for their existing business, making it hard to pivot.

innovators dilemma examples (3)

kodak- focused on film despite pioneering digital photography.

blockbuster- failed to adapt to netflix’s disruptive streaming model.

nokia- lost dominace in mobile phones due to the rise of smartphones

innovators dilemma strategic takeways (4)

companies should create separate units to experiment with and scale disruptive innovations.

leaders must embrace uncertainty and invest in potential future markets, even when current returns are unclear.

orgnaizations should develop customer foresight to anticipate shifts in market demand.

acquisitions.

why is TID the startups friend?

startups can have a shot against the big guys.

acquisitions.

packaged software (off the shelf)

this is the classic model: one product, many customers, mostly identical bits.

you buy/license it and run it yourself.

historically this came on disks, now it’s usually a download.

key trait is that you manage the environment it runs in.

EX: desktop productivity tools, design software, and developer tools.

software as a service (SaaS)

similar to packaged software: one product, many customers- but the vendor runs it for you.

you access it through a browser, thin client, or mobile, usually via subscription.

updates happen continuously and invisibly.

this model dominates business software because it collapses distribution, upgrades, and support into one loop.

enterprise software

built for organizations rather than individuals.

it often overlaps with SaaS or packaged software, but it’s distinguished by scale, compliance, integrations, and procurement rituals.

think ERP systems, CRM platforms, identity management, and large analytics suites.

the software itself matters, but contracts, support SLAs, and integration surfaces matter just as much.

embedded software (commercial)

sold inside something else: medical devices, cars, industrial machines, networking gear.

users don’t usually buy it separately, but it’s still commercial software with licenses, updates, and long maintenance tails.

this category quietly runs much of the physical world.

platform software

instead of selling an end-user experience, this software sells a foundation.

value is leverage as other software is built on top of it.

successful ones create ecosystems, not just customers.

EX: operating systems, cloud platforms, databases, and developer frameworks live here.

vertical software

designed for a specific industry rather than a general audience.

these products win not by being generic and flexible, but by knowing one domain obsessively well.

EX: legal practice management, hospital record systems, construction estimating tools, airline scheduling.

custom commercial software

built for a specific customer, paid for by that customer, but still commercial because money changes hands and IP is negotiated.

the software may never be resold, but it’s still part of the commercial software economy.

EX: consulting firms and system integrators.

most of modern software world is a remix of what 3 axes?

who runs it? customer or vendor.

who’s it for? individuals, orgs, or industries.

how’s it monetized? license, subscription, or contract.

tech enabled services

simple idea: supercharge human driven services business with powerful AI technologies and tools.

build a services business from the ground up with technical leadership DNA.

like a regular tech startup: domain expert (FMF) + AI-savvy CTO.

EX: stitchfix.

tech enabled services huge opportunity

tax accounting:

there is a huge shortage of accountants in the US today.

the current workforce of accountants is reaching retirement age.

overall enrollment in accounting programs has decreased significantly.

accounting regulation changes have led to an increased need for CPAs.

many firms are family/legacy businesses.

Jay’s experience – getting fired by my tax accountant.

tech enabled accounting service upsides (7)

built from the ground up with SOTA tech and mindset.

nothing is relearned/retrofitted, existing workforce is not reduced.

5x (?) human efficiency.

why now? gen AI.

be in a unique position to identify when there is a standalone product opportunity.

you’re constantly talking to customers and helping them with their business challenges.

because it is paid services, you get to cash-flow-positive quickly.

tech enabled accounting service downsides (2)

bootstrapping.

less VC friendly.

MVP note

development for this typically comes after hypothesis forming, validation, and market research phases.

minimum viable product MVP

essentially, an early version of a product.

has just enough features to demonstrate to early customers and gather feedback for future development.

not just a thing, but also a process.

MVP goal (2)

test the core value proposition with minimal resources.

gather validated learning before committing to full-scale development.

MVP motivation

don’t build some big, complicated, fancy, expensive software until you are confident that someone wants it/will pay for it.

MVP history

originates from Lean Startup methodology, developed by Eric Ries.

Lean Startup movement took off in 2008-2011:

Ries formally introduced the term as a way for startups to test ideas quickly and avoid wasted effort.

Ries emphasized the Build-Measure-Learn cycle, where companies release a simplified version of a product, gather feedback, and iterate based on real user data.

many inexperienced entrepreneurs believe?

if i build it, they will come.

—> but really, if you build it, they almost certainly won’t come.

MVP entrepreneur struggles (4)

they always wanted to be at the helm of product development – this is their chance!

they believe (perhaps unconsciously) their vision for the product is the right one, regardless of feedback they get from real customers.

they feel very uncomfortable/vulnerable showing products that lack polish or what they believe is a complete feature set (this might come from their BigCo pedigree).

learn from the customer! Let them tell you what they need, even if it is at odds with your vision (and your ego).

highest paid persons opinion HiPPO

in a startup or corporate context.

used to describe a decision-making process where, instead of relying on data, user research, or evidence, the company defers to the opinion of the most senior or highest-paid person in the room.

HiPPO how to manage

to mitigate this effect, teams are encouraged to "let the best idea win" rather than the loudest voice, or for the leader to speak last.

HiPPO concern in startups

can stifle innovation, promote conformity bias (where employees are afraid to disagree), and lead to poor decision-making.

startups are supposed to be agile and data-driven (e.g., Lean Startup methodology).

the HiPPO effect

occurs when the CEO, founder, or senior stakeholder makes a decision based on gut feeling or personal experience, which then overrides data-driven insights.

HiPPO

the "Highest Paid Person's Opinion" (or sometimes "Highest Paid Person in the Office").

traditional enterprise software sale

build enterprise accounting software with CEO w/FMF + CTO “We’ll increase your productivity!”

—> sell to different accounting firms (A,B,C).

*hard to do w tech enabled services because of the Challenge of Change.

go to market GTM

not just marketing, it’s the bridge between the product you build and the revenue you generate.

distribution must be built into the product.

GTM requirement

distribution cannot be built in later- must be built into the product.

it’s an engineering constraint that must be a feature of the product itself.

GTM core tension

the user vs. buyer problem.

in B2B, the person using the software is often not the person signing the check.

the product must solve for both.

why do most startups fail?

because the math doesn’t work, not due to the product.

*channel fatigue phenomenon:

customer acquisition costs > lifetime value.

channel fatigue

if you use Facebook ads like everyone else, you’re bidding against the entire world.

this drives ROI to 0.

*reason for startups to fail

startup strategy stages (3)

seed stage: doing things that don’t scale, channel = your (founders) phone

first 10 customers: co creation phase, design partners (not just customers), thier testimonials are your most valuable asset.

product market fit: the tipping point, when the product is pulling itself out of the building.

seed stage

startup strategy stage 1.

doing things that don’t scale.

channel = your (founders) phone.

first 10 customers

startup strategy stage 2.

co creation phase.

design partners (not just customers).

their testimonials are your most valuable asset.

product market fit

startup strategy stage 3.

the tipping point.

when the product is pulling itself out of the building.

the hiring pivot

build the playbook before you run it.

rule: don’t hire a VP of sales until the founder has closed 5-10 deals personally.

logic: you cannot outsource the discovery of the sales motion. sales leaders scale what works, founders discover what works.

*founders = building the playbook.

*VP sales = run the playbook.

the rule for building the playbook

don’t hire a VP of sales until the founder has closed 5-10 deals personally.

*founders = building the playbook.

*VP sales = run the playbook.

build the playbook before you run it → the hiring pivot.

the logic for building the playbook

you cannot outsource the discovery of the sales motion.

sales leaders scale what works, founders discover what works.

*founders = building the playbook.

*VP sales = run the playbook.

build the playbook before you run it- the hiring pivot.

the bullseye framework

outer ring: all possibilities- brainstorming.

middle ring: promising options- testing.

inner ring: magic- doubling down.

*prioritize quick and inexpensive tests.

*double down on high ROI.

the bullseye framework core philosophy (3)

all possibilities → promising options → magic.

prioritize quick and inexpensive tests.

double down on high ROI.

the bullseye framework outer ring channels to consider (19)

1. targeting blogs.

2. public relations.

3. unconventional PR.

4. search engine marketing.

5. social & display ads.

6. offline ads.

7. SEO.

8. content marketing.

9. community building.

10. speaking engagements.

11. email marketing.

12. viral marketing.

13. engineering as marketing.

14. business development.

15. sales/outbound.

16. affiliate programs.

17. existing platforms.

18. trade shows.

19. events.

moving from possibility to traction

brainstorm (19 potential channels) →

test (pick top 3 promising options, run cheap experiments) →

focus (find the inner ring channel, ignore the rest, double down).

the early days of shopify case study

didn’t start as a giant.

it required clever, specific distribution hacks to bridge the gap from niche store to platform.

skateboard store → lifestyle business → venture scale business.

winning experiments:

1. partner referral program

2. build a buisness contest

3. pricing model pivot

4. paid split tests

the early days of shopify case study winning experiments (4)

winning experiments:

1. partner referral program- turned web designers into a decentralized salesforce by offering revenue share.

2. build a buisness contest- a “bet the company” viral stunt w $100k prize, generated $3M revenue.

3. pricing model pivot- switched from transaction fees to subscription, removed friction for high volume merchants.

4. paid split tests- small scale data driven experiments to prove predictable growth by tuning the dial on spend.

changes for GTM in the times of gen AI (4)

accelerated bullseye: experimentation is faster and cheaper, test messaging in hours, not weeks.

content & SEO saturation: rapid Al generation creates noise, the quality bar rises.

engineering as marketing: Al lowers the barrier to build free tools and calculators for lead generation.

adversarial marketing: channel fatigue sets in faster, distinctiveness is the only defence.

constants for GTM in the times of gen AI (4)

user vs. buyer problem: Al cannot fix the organisational mismatch.

unit economics: $CAC < LTV is still the law, Al efficiency cannot fix a broken model.

founder's role: you must still build the playbook, Al cannot automate empathy.

product-market fit: Al cannot pull a product out of the building if it solves no real problem.

types of customer research conversations (2)

forming.

validating.

forming customer research conversation

stage: hypothesis building.

goal: gather enough data & info to derive unique insights.

features: volume, 3+ dozen, semi structured, 2nd & 3rd order q’s, patterns & variations, identify constraints.

macro pivot (or abandon).

validaing customer research conversation

stage: hypothesis testing.

goal: confirm uniqueness of insight & validate proposed solution.

features: tell you customers smth they don’t know, give them smth to react to without leading them, test to value not the idea, maintain objectivity throughout.

micro pivot.

customer discorvery & research is challenging due to (2)

noise.

confirmation bias,

noise

sampling error.

not talking to the right people about the right things.

confirmation bias

tendency for people to seek out, interpret, and remember information in a way that proves their existing beliefs, while ignoring or downplaying contradictory evidence.

can significantly impact interviews, decision-making, research & ultimately the success of your entrepreneurial journey.

one of the most common cognitive tendencies.

how confirmation bias affects interviews (4)

leading questions

selective attention.

cherry picking data.

self fullfilling prophecy.

leading questions

reason why confirmation bias affects interviews.

if you expect a certain answer, you may unintentionally frame your questions in a way that steers the interviewee toward confirming your assumptions.

EX: instead of “what do you think about remote work?” asking “don’t you think remote work makes employees less productive?” nudges the interviewee toward a particular answer.

EX: “I had this problem with XYZ so I built this tool to solve it…do you have this problem too?”

selective attention

reason why confirmation bias affects interviews.

you may unconsciously focus more on responses that align with your preconceptions and ignore contradictory statements.

cherry picking data

reason why confirmation bias affects interviews.

when reviewing interviews, there’s a tendency to emphasize information that confirms what you already believed and overlook opposing viewpoints.

self fullfilling prophecy

reason why confirmation bias affects interviews.

if an interviewer expects a candidate or respondent to behave a certain way, their own behavior (tone, body language…) might subtly influence the interviewee to conform to that expectation.

how to reduce confirmation bias in interviews (5)

use open ended questions: allow the interviewee to express their perspective without leading them.

be brave, seek contradictory evidence: deliberately explore viewpoints that challenge your assumptions, this takes guts and grit! (personal cost)

be introspective: reflect on your own biases, acknowledge your expectations before conducting the interview.

blind analysis: if possible, analyze transcripts without knowing who said what to prevent personal biases from influencing interpretation.

have a structured interview format: standardized questions reduce the chance of bias-driven deviations.

the mom test

hoe to talk to customers and learn if your business is a good idea when everyone is lying to you.

by Rob Fitzpatrick.

mom test fundamentals

•Talk about their life, not your idea.

•The purpose of these conversations is to falsify weak assumptions early.

•The moment you pitch, you contaminate the data. Stay focused on their world (ask about the past, not the future).

•“Tell me about the last time…” beats “Would you ever…?” every time. Past behavior is evidence. Future intent is fiction.

•Dig into specifics: Time spent. Money spent. Frequency. Workarounds. Specifics are signal; vagueness is politeness.

•Avoid leading questions: If your question telegraphs the “right” answer, humans will deliver it (don’t seek validation, seek truth).

•Compliments feel good but are informationally empty.

•Look for commitment signals: Real interest costs something: time, money, data, introductions. Words are cheap (follow the pain).

•If the problem hurts, there will be artifacts: hacks, spreadsheets, duct-tape processes, budget allocations (let uncomfortable answers surface).

•Silence is better than rescuing the conversation with enthusiasm (separate problem discovery from solution pitching).

•First understand the terrain. Only later discuss your proposed map (change direction when evidence demands it).

tidbit of tribal knowledge

B2B companies topline vs bottom line.

which is your solution?

it depends how much the bottom line matters.

revenue (topline) - expenses = profit (bottomline).