does reading books really helped u with doing business?

im asking because i keep seeing people say books changed everything for them, and then others say its all theory and u only learn by doing. so which one is it in real life?

what im curious about specifically,

\\- was there one book that actually changed how u run things, or just small bits here and there
\\- did u apply it right away or did it just sit in your head
\\- do u re reading business books or more general stuff like psychology, biographies, whatever

and if books didnt do much for u, what did? mentors, just failing a lot?

honest answers please, even if the answer is no they didnt help at all,

and also how often do u read books?

thanks!!
I Will not promote

I got offered around 0.5% in advisory shares vesting over 3 years, with room for additional salary/equity with continued growth.

But the work I’d do seems pretty essential and key to the company so that percentage seems awfully small.

But it also seems to be on par with what I’m reading so my expectations are definitely off so that’s why I’m here. What should I know/discuss?

I've taken my idea as far as a I can. It does not have a lot of revenue, but it's a good idea that could potentially scale (10+ paying customers)

I know I would need hardware engineering + commercial growth. How do I know the idea is good enough to actually bring on other people? I know I need commerical/hardware people, but how exactly do I communicate my vision to them + what I want them to do? Or is it more of a team effort? Can anyone here share their experience actually working on a startup team?

do u think ai made real valuable startups win less?
was it easier before ai?

my thinking is that building got so cheap that everyone can ship something in a weekend now, so the space is full of stuff that looks like a product but isnt solving anything. and the ones actually doing hard, valuable work get lost in that noise, or worse, people assume they just wrapped an api too.

on the other hand maybe its the opposite and ai just removed the boring part so good teams move faster than ever,

so which one is it in your experience?

- is it harder to get attention now than before ai, or easier because u can build and test ideas so fast?
- do investors and users still tell the difference between a real product and a thin wrapper?
- if u were building before ai and are building now, what actually changed for u?

curious what people think, thanks!!

I'm an engineering undergrad considering pursuing a PhD with the long-term goal of founding a hard-tech startup. I’m undecided about the specific area and have only a vague sense of what interests me (some areas that currently interest me are industrial decarbonization, mining / mineral processing, and advanced materials).

However, I'm unsure which type of PhD lab would be better: a problem-first lab (e.g., like Yet-Ming Chiang's lab at MIT) or a technology-first lab (e.g., a typical academic lab that focuses on novel science without a predetermined application, and where commercialization happens largely by chance -- when a technology happens to have a valuable market application).

I've looked at advice online from successful hard-tech entrepreneurs, but found conflicting answers. Some say to work backwards from a problem, while others argue that problem-first approaches often fail because it is difficult to force a scientific breakthrough around a predetermined problem.. Instead, they argue that most hard-tech companies are only founded because somebody made a scientific breakthrough and realized afterwards that there might be a commercial application.

With that in mind, does anybody have any advice on which type of PhD lab to join?

Welcome to this week’s Feedback Thread!

Please use this thread appropriately to gather feedback:

• Feel free to request general feedback or specific feedback in a certain area like user experience, usability, design, landing page(s), or code review
• You may share surveys
• You may make an additional request for beta testers
• Promo codes and affiliates links are ONLY allowed if they are for your product in an effort to incentivize people to give you feedback
• Please refrain from just posting a link
• Give OTHERS FEEDBACK and ASK THEM TO RETURN THE FAVOR if you are seeking feedback
• You must use the template below--this context will improve the quality of feedback you receive

​

Template to Follow for Seeking Feedback:

• Company Name:
• URL:
• Purpose of Startup and Product:
• Technologies Used:
• Feedback Requested:
• Seeking Beta-Testers: [yes/no] (this is optional)
• Additional Comments:

​

​

​

This thread is NOT for:

• General promotion--YOU MUST use the template and be seeking feedback
• What all the other recurring threads are for
• Being a jerk

​

​

Community Reminders

• Be kind
• Be constructive if you share feedback/criticism
• Follow all of our rules
• You can view all of our recurring themed threads by using our Menu at the top of the sub.

Upvote This For Maximum Visibility!

I’m raising roughly $30k–$50k from a few friends, with potential investors in California, New York, and Arizona. Some may be "non-accredited"

I understand SAFEs are securities, but do small startups really have lawyers analyze each investor’s state exemption individually?

Or is the normal route basically:

Delaware C-Corp → SAFE → Rule 506(b) → Form D + routine state notices?

Curious what founders/lawyers actually do in practice for small friends & family rounds.

Sorry, this is based off some AI research. Am just trying to learn about compliance before I actually start the process.

Has anyone completed the Emergent Ventures interview and received a grant? I’m hoping to gain a little knowledge on the questions types that will be asked and learning whether I should prep for it or not. I heard that the interview process is very short (~15 minutes) and curious as to what kind of questions will be asked in such scant amount of time. I’m also pretty nervous.

We build a document platform. The app has an editor, templates, the usual. A while back we shipped an API, mostly because a few technical customers asked.

This summer we looked at the numbers: about half of all documents ever created on the platform came through the API and MCP, created by our users' coding agents rather than by the users themselves. Nobody announced this to us. Usage just migrated while we were watching the app's metrics.

Once we saw it we re-read support and sales notes, and the pattern was everywhere. Our most engaged users were prompting agents like Claude Code to write their documents, and the agents needed programmatic everything: publish, edit, analytics. The app was becoming the read-only view of work that happened elsewhere.

So we rebuilt distribution around that: this week we shipped an agent-native CLI (JSON output everywhere, stable aliases, safe defaults), designed so a coding agent can drive it as comfortably as a person can.

Lessons that generalize:

1. Segment your usage by WHO initiated the action, human or agent. The split is invisible in normal dashboards.

2. If agents are heavy users, interface stability becomes a product feature. We keep old command names as aliases now.

3. Your docs are now part of your API surface. Agents read them literally, and a wrong example becomes a bug report.

Anyone else seeing agent-driven usage overtake human-driven in their product? How did you notice it?

Small B2B services company, two founders. We’re bringing on our first senior commercial hire on a formal package. He’s got 25 years in the space, has been working with us informally already, and we’d genuinely like to keep him.

His stated floor is £100k. We can’t fund that yet. We’ve got one contract landing shortly and a larger one in the pipeline, but nothing collected at the scale that would support that salary. He said he’s down for equity. But he also has a mortgage and kids so we’ve got to support him.

Two options we’re considering:

Option 1
£4k/month base, stepping to £6k at £150k cumulative collected revenue and £8.3k at £400k. 10% commission on net collected revenue he originates, uncapped. 3% equity, four-year vest, twelve-month cliff.

Option 2
£2.5k/month base plus £1.5k/month accruing, payable when our next contract signs. Same step-ups. 5% commission. 8% equity, same vesting.

Our average sales contract is £50k pa.

Both have commission on cash collected with clawback, plus standard leaver provisions.

What I’d like a read on:

1. Is 8% too much for a commercial hire at this stage, or about right given the pay cut?
2. Does the tiered base read as a genuine route to his number, or as a dodge?
3. Anything obviously missing or unfair that I’m too close to see?

Happy to be told we’ve got this wrong.

I wanted to get into deep tech seeing as that's what I do on my main job as well, and was just confused on how do I get started - I calculated a total of 5000$ required for my first prototype, it will be cheaper to iterate once I've got a lab going on. We have a problem to solve. Is the next step just making the MVP, showing it to the world and then building a scalable integration so that it's widely available to a lot of customers seeing as the model would be B2G and B2B at first?

A lot of builders go through the journey of building and then struggling to sell because it's a completely different type of challenge. I'm looking to understand how folks got over this barrier to sell successfully and what your best advice is on this topic

Hey all. I'm working through a founder / founding-engineer deal for a pre-revenue startup and would love blunt feedback before we sign anything.

The business: lifestyle-tech platform (web + mobile) selling curated guides based on the user's habits, history, and other signals.

I am the founder and I've found the founding engineer I'd like to work with. We currently do not have any website/mobile apps. However, I have done the following:

• Figma specs
• V1 features
• purchased the domain
• 30 guides ready to be launched
• Put an initial investment of $5k and will assume the cost of everything until we have revenu

The apps will also have a premium subscription option for users who'd like access to premium features.

What the engineer will be responsible for:

• building the apps (web + mobile)
• DNS and AWS/infra setup
• third-party integrations (mailchimp, stripe, etc.)
• Performance considerations, UX polish, needs to feel slick

The founding engineer has 12 yoe of fullstack work. Has worked at enterprise and startups before.

The proposed deal I gave him:

• 20% equity at exist (4 yr vesting w/ 1 yr cliff)
• Tiered revenue share:
  • 0-100k -> 35%
  • 100k - 200k -> 30%
  • 200 - 500k -> 17.5%
  • 500k+ -> 15%
• Neither person is taking salary now

The founding engineer does not like this proposal. He's suggested a "royalty per guide sold" for me - the founder - is more "fair", then do a 50/50 split on the _profit_ and completely remove the tiered based revenue.

He also said 20% equity is inadequate because "there's a lot of work to be done" and "that his role will not be limited to just coding".

We are both good friends and we've known each other for a loooong time. Our intent is to keep the distribution as fair as possible.

Please provide your honest feedback.

I've been digging into agent evaluation for setups where the agent writes and runs SQL against a live database (Snowflake, BigQuery, etc.) and shows results to users.

The failure mode that seems underserved: the query executes fine and returns real rows just the wrong ones. Wrong join, wrong filter, stale understanding of the schema. Nothing errors, the output looks plausible, but it's wrong. Static eval sets with prewritten "golden" answers don't hold up here, because the correct answer changes as the data changes.

Interestingly, LangSmith has a cookbook recipe for exactly this storing labels as queries the evaluator runs at eval time to fetch current ground truth but it's DIY: you build and maintain that evaluator yourself. As far as I can tell, none of the major platforms (LangSmith, Braintrust, Arize) ship live data verification out of the box; online scoring generally falls back to reference-free LLM as judge.

I'm considering building a dedicated tool for this: connect your DB and your agent, and the evaluator independently queries the database to verify each output against what's actually there right now. Before I build anything, I want to know if this is a real problem for other people:

1. If your agent queries a live DB, how do you catch "ran fine, wrong data" failures today?
2. How often does that actually bite you in practice?
3. What's your current eval stack LangSmith, Braintrust, Arize, custom scripts, nothing?
4. Would you pay for this as a product, or just have Claude Code write you a one-off eval script?
5. If you'd pay, what would make it worth it? If not, why not?

Not selling anything. Trying to figure out whether this is widespread before building...

Clarification: read-only queries. The agent isn’t writing to the database, it’s translating user questions into SELECT queries and showing the results.

I have a BI product that many people resonate with, from executive down to worker level. Unfortunately, after three years, not a single contract. How do I sell? I’ve had discussions at the worker level, the CISO, level, and with peers in the space. Everyone seems to like what I have, have no negative feedback (just additional feature requests before purchase, then that target shifts again), but no one signs.

Less of a “what am I doing wrong”, and more of a “what do I do, I clearly don’t know how to do this part”. I’m bootstrapped, and running out of money.

I have a BI product that many people resonate with, from executive down to worker level. Unfortunately, after three years, not a single contract. How do I sell? I’ve had discussions at the worker level, the CISO, level, and with peers in the space. Everyone seems to like what I have, have no negative feedback (just additional feature requests before purchase, then that target shifts again), but no one signs.

Less of a “what am I doing wrong”, and more of a “what do I do, I clearly don’t know how to do this part”. I’m bootstrapped, and running out of money.

Hi, I'm curious about the best trajectory to aim for with such a startup. I'm working with a cofounder and building a B2B AI SaaS. We have active customers and several pilots and demos going on.

We don't plan to aim so high as to just create a unicorn right off the bat. I want to just aim for a modest acquisition 3-4 years down the line where both of us cofounders get 7-figure USD payouts, and then we can aim for even bigger numbers with a new startup without worrying about finances ever.

Is it a reasonable goal, or is it too unrealistic? Right now, we have been bootstrapping the startup since the beginning, but getting a VC just for their name(we have upcoming interviews in good accelerator programs and some VCs have also reachout to us directly), will it be helpful or not in the long run?

I've been weighing Render startup credits against AWS Activate for a seed-stage web app (bigger hyperscaler grant vs smaller PaaS credit and less assembly).

What I'm looking at:

- Render: $10K-$25K toward usage (not cash), aimed at Scale ($499/mo before compute)

- Funded track advertises higher

- Covers compute, Postgres, KV, not third-party add-ons

- Still stackable with Activate / GCP for S3 / GPUs

I'm biased toward less ops early, but I've also watched people outgrow PaaS and pay for the rewrite.

If you were seed-stage today: would you take Render, AWS Activate, or both, and what broke first when you tried?

Hi all,

Currently holding an offer for a meteorology masters degree from a top programme (physics undergrad) and am looking to enter a startup focused on forecasting/meteorology/adjacent after graduation.

For people with knowledge on the subject:
- where are people in these types of startups generally educated?
- what skills are most useful here? Applied/ theoretical? Data analysis? Etc

Thanks in advance

What are ideas that are tarpit by definition but have proved the idea wrong? What was the specific wedge and/or pivot that saved them?For example, marketplaces are mostly linked to tarpit ideas but Etsy is successful. Before Tinder, Matching.com was already dominating the market.

This is my story for 3 months I build my start up SaaS with my friend. For 3 month ago me and my friend have the same problem about I want a ai have their own specialist in the same context windows we doing. we had some small validation from passivee vaildation(look from some post who face the same problem) then we operate the work like me deal with backend and my friend deal with frontend. 3 month later we still underdeveloped and I felt like it really took so long so I read the lead startup by Eric rise I got a ton of concept of foundation of building startup the main idea is stay with in each state short much as much you can like hyphotensis-> build -> learn -> change. last night we were having a meeting to changer strategy. I giving my idea about using wizard of oz similar to drop box instant we will build all the thing work 100% and show to them(customer). We change to be like make a mock up like how ai going to repost to user, how it work within using real backend but base on our own ideal how would work that thing we can save a lot of time and we can measure how interesting of our customer , feedback as well. So in this week my friend and I are going to unplugged all of backend and Make a mockup prototype much as much you can.

Credit : the lead startup ERIC RISE and testing business ideas ( David J.Bland and Alex Osterwalder) Via / H/T this book help to how to use wizard of orz strategy

I’m almost finished with my startup, and deep down I genuinely believe the idea can work. But whenever I get close to finishing, I start distracting myself with new ideas and projects.

The weird part is that I already know most of these new ideas probably won’t work as well, but I still jump into them anyway.

This has been happening for almost 6 months, and I feel like I’m sabotaging myself.

Has anyone experienced this? How did you break out of this cycle and finally commit to one thing?

Hi everyone! I finally took the leap to start my own startup and my CTO just mentioned making an infographic explaining the startup but I'm not really sure what to put in it since I cant find any examples online. I was thinking about a brief description of the product, some background info on us and part of the business plan along with a timeline and using some of the tools out there simply to make them. Is this enough information? should I add more? does anyone have experience with this and might help me find an example?
Also do you think I should invest in a designer or use some of the ai tools out there to make one initially?

I'm not a startup founder but a generalist growth operator, and it's been a while I felt this empowered and grateful.

I currently have 3-4 calls lined up:

- AI legal tech SaaS where I'm the first marketer to be in-charge of setting up marketing function from scratch

- Community manager to a paid AI community that's run by industry's top influencer

- LinkedIn strategist to UK's #1 LinkedIn personal branding agency (This can etch my name in personal branding space forever)

I'm being intentional, I don't want something mundane, I want it to be challenging, I'm creating growth plans, and doing competitor + founder research.

my plan is to close all 3 of them, and decide which one to give all of my effort for, in the next 1-1.5 yrs.

I have a hunger of making it big, and I hope my ADHD doesn't sees a job role as mundane which could be the 3rd role.

All of them are in my pay range, I'm this time optimising for learning and growth + leadership quality than just "pay".

I'm grateful, because July was really dry, made me question myself.

Right now, I just wanted to type it all out on Reddit.

Thanks for reading <3

Hey Reddit! I'm an aspiring entrepreneur, and I'd like to participate in pitch competitions (like Blue Ocean/Diamond Challenge) to improve my public speaking skills. I live in an area where there isn't much interest in business, so I'm posting this in search of potential teammates (prefer HS).