fzwang

IMO, the proposed 5/5 compensation is a bit high. If I understand correctly, he's essentially asking for approx $1.2M total comp package for raising $4M. I'd suggest 2.5% and 2.5%, or some combination of.

There are terms other than valuation which are very important (board rep, liquidity pref, etc). Have you talked about what are the must haves and deal breakers for you and your team?

IME, the bigger issue in the long run with this situation is that you, the founders, do not have a direct relationship with the investors. These investors will most likely be "his" investors, which positions him as a key intermediary. This will be a problem in the future when you need to manage them and must go through a middle man.

The CEO should ideally lead the pitch and an advisor can help with coaching, networking, and strategy (and be well compensated for it). I think any competent VC will want to see that at least one of the founders can do sales.

Sorry to hear that you're going through this. I work with other students/recent grads going through the same thing. A few suggestions:

1) To echo some of the other comments here, getting a regular routine will help you get into better habits. Good sleep, regular exercise, and limited social media etc will help with your mood.

2) The setbacks are situational, not dispositional. It really is a shit job market and you likely don't know how to properly signal yet (ie. sell yourself to others). And to make things even worse, brute force ATS grinding is now even less effective since everyone can now game the systems and generate a plausibly good-looking coherent resume using AI.

3) IMO, one mistake I see often is that students think jobs are the only way to gain experience. This is not true. You really have to be constantly learning new things on your own. Your university education is not enough. This means working on projects specifically for learning purposes. I'd suggest you alternate between learning-mode and applying-mode, where you spend 2-3 months just working on shipping a complete project, then focusing on applying to jobs for another 2-3 months, get feedback and rinse and repeat. You can use the learn-mode time to adapt to feedback. I think this will yield better results than applying over and over again hoping for different results.

Anyways, feel free to reach out. As others have said, you're beating yourself up too much. You'll figure it out and find a way through these setbacks. The important thing atm is not to spiral into a vicious cycle. I applaud you even airing this on HN, as it's much much better than sulking alone.

I used to work in VC and have dealth with university commercialization/IP offices.

1) If it's serious, you need to lawyer up. It might not be now but if you can get some investors involved they could help with getting legal resources. If it's medical devices, you'll need investors anyways. One issue is this gives investors a lot of leverage to negotiate their interests against you.

2) The university office absolutely does not care about how "little" they gave you. Their perspective will be they've given you plenty, as office/lab space and anything else were not part of the deal (unless you have it in writing), and they've subsidized your funding. It's not "fair" but it is what it is.

3) This scenario is quite common, and one of reasons I tell grad students to negotiate this stuff first and pick your school wisely. Some schools are way better than others in allowing their academic staff commercial freedom.

4) You can make it a PR issue for them, to push the narrative of "university stifles innovation via obscure bureaucracy" but it's a risky strategy.

There are usually always room to negotiate/maneuvre, but you need the right contacts and political support within the university to pull it off.

Good luck!

Location: Toronto, Canada

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I'm building out a new comp sci education program based on an advisory model. It is intended to complement instructor-lead models (like traditional schools/universities), with more emphasis on self-direction and real-world exposure. Part of the motivation is to address talent development problems in startups when I worked in VC and in hiring for projects for my own company. These issues are exacerbated nowadays with AI.

I'm the lead advisor and currently looking to recruit students to work with personally, ideally those who are in HS or university but is bored and/or feel like they are not learning useful/interesting things. Bonus if they have an interest in exploring entrepreneurship. I have a background in data engineering, VC, and ML R&D.

From my experience and talking to other founders/engineers ...

1) It's good to analyze what's the source of the burn-out. In many instances, it's not exactly exhaustion per se, but lack of meaning in what they are doing beyond the money. There are acute stressors, like coming out of an intense sprint, and chronic stressors, like not knowing why you're even doing this. If you had fuck-you money, what would you be doing long-term instead? beyond take a vacation, buy a house, etc.

2) Learning to say no to things. Let go of "hero" mode. Good enough for now is good enough for now. Cut down on complexity to reduce cognitive load. Really assess which things you do are real and which are performative.

3) Better understand how work fits in your long term goals. Having worked in VC, a lot of advice for founders are very investor-centric. The core of the thinking is that some sort of exit will solve all your problems, and is worth grinding for. I see many founders become entrepreneurs to "work for themselves" and not be a corp wage-slave, just to become a VC grind-slave. Their health falters, their personal life implodes (divorce/breakups), and they've no genuine friendships (just business acquaintances). When they do get to a good financial exit, they're still miserable. Do try to make the company/product building process enjoyable too. Sometimes it means slowing down, smell the roses, think things through to avoid problems.

Overall, the right advice is very situational. The most important part may be talking out loud to someone you trust about it. Sometimes just verbalizing it helps.

I work with students and junior engs.

Personally, I'd avoid using AI tools for learning atm.

1) As a learning path planning tool, I find LLM tools are very good at creating learning plans and next steps for popular concepts. However, the convenience of the tool also skips over a lot of accidental discovery/exposure, which IMO is useful in the long run in building out broader contextual awareness. The students following an AI plan only knows about the things in immediate vincitiy. Whereas more traditional methods, like a web search (use someting like Kagi, not Google) reveals more advanced stuff which they don't know yet, but plants a seed in their brains.

With the right prompting system, you can probably mitigate some of these issues, but atm I find the general trend is people want short fast answers.

2) For actual coding I'd discourage it. For people to learn quickly they have to build stuff from scratch so they develop the right mental models. Writing code manually is a good check on their understanding. When the work becomes boring/tedious they can offload it to AI tools.

Overall, my experience has been that the AI tools are useful in the short term, but too much reliance amputates a lot of the valuable, but hard to measure, learning experiences. If the goal is to form the right mental model of concepts in the human who is learning, then bypassing some of the "work" and frustration by letting AI do most of the planning and "thinking" actually harms the learning process.

It seems like the cashflow situation will rule out some options, at least for the moment, like boostrapping etc. Contracting could be a temporary option, esp for US companies that need in-person support with good language skills. This would blunt some of the competition from abroad.

Regarding learning "out of the tar-pit", it's hard to give out specifics without knowing more details about your experiences. But it might be worthwhile to reach out to other senior engineers in your network, not to ask for a job, but to ask for advice about switching from entrepreneur/founder to employee. It could be a good way to build rapport and identify what you should be learning next.

Your health obviously takes priorty over everything else. Medical problems can really push you into despair if left unaddressed. Money you can always make back later.

From your comments, it seems like there's a lot of internal and external issues you're dealing with. Internally, your sense of self worth is very much tied to your compensation/wealth. The recent rejections have triggered anxiety / negative self-reflection. The lack of a job/income is really straining your confidence.

Externally ...

1) It's actually a shit job market.

2) Your startup experiences don't really help signal your skillset as an employee. There's a sorta "founder tax" you're paying.

3) COVID, remote work, and new supplies of CS grads have changed the labour dynamics to depress wages. The top 20% may be doing ok, but the bottom 80% are getting diluted.

If I were you I'd consider a few things:

- Really think about what's a good/meaningful life to you. Volunteer/do something useful for other people (ex. a non-profit) to build up confidence again.

- Recognize your technical skillset may not be as "senior" as you think, since you had to expend valuable time learning other skills as an entrepreneur. It might mean more learning, building, leetcode grinding, interview prep, etc, before you can land the role. Concurrently, you can think about how to better communicate all the other useful things you've learned at a startup.

- If you enjoyed the startup experience, but concerned about the grind, then you don't have to build high growth businesses that require the 996 mentality. Boostrapping and organically growing a niche product may be more aligned with your skillset/goals.

Often solo-founders build very niche apps/SaaS which they already have a personal network for or can target smaller platforms and business networks for marketing/distribution. You can stay small and do very well.

The larger platforms are usually too saturated to be effective. In my experience, generally not a good return on $/time.

Generally, less classrooms/traditional schooling, and more exposure to the real world. Taking more time to meet people and expand the social horizons.

I feel like I just didn't know what I didn't know. And I was making decisions on very little experience/information. The "adults"/"experts" didn't know what they were talking about or at least were not aware of their own biases/limitations.

Looking back, almost all the useful/important things I learned were self-directed.

It's an interesting conundrum, where everyone knows the system is bs but no one wants to take the first step. Hypothetically, some possible scenarios:

1) An external event, like a war, that stress test the credentials and to force selection based on outcomes. 2) Some sort of monetary benefit for employers, like extended internships for high schoolers. Assuming it's cheaper/more effective for an employer to train their workforce from scratch than pay the full salary of a recent grad. 3) A new field, where credentials haven't been established yet.

There are obv caveats to all of these. And they don't address the question of what a formal education is supposed to accomplish. At some point, it was supposed to be to train "better citizens". And that shouldn't be dictated by employers, imo. But nowadays it seems like the purpose is to get a job and survive.

I think this is the lack of accountability that I find frustrating in the education system. If the student gets a bad experience, they are always blamed first and the role of the teacher/professor/university is never questioned.

This is an interesting question. I work with students (older teens/young adults) and they are dealing with similar issues. It seems like the world's expectations shifted very quickly under their feet.

I don't think anyone knows the answer. As a hiring manager, I definitely put less weight on generic CRUD apps etc nowadays. You can argue that people can actually just copy and paste from SO before, and that's true, but even with that you had to have some knowledge so integrate what you've copied. With AI assist, the process is orders of magnitude easier, as you can just re-try prompts etc.

What I look for instead is more information on the process of creation, which usually means examining their writing. How did they get the idea? how did they think about what features to build? But even this is not immune to AI contamination.

Overall, I think we're likely to move towards more reliance on verifiable longitudinal data rather than "spot checks". It's much more difficult/challenging to re-create for "portfolio cheaters", and easier for authentic applicants. I get my students to write a dev journal which I verify, and use that as part of a private portfolio that we can share with potential employers.

Overall, I'd say the vetting process is much more onerous on both sides and portfolios will now need proof-of-authenticity.