chuckus

Agree with this, 3% of something is better than 40% of nothing. I was a technical co-founder was that left a startup early on, and because we didn't have a vesting agreement from the very beginning, I was entitled to my 40%, even when I left the company. While it was to my advantage, I didn't want my co-founder to give up when I left, so I gave most of it up. For my next startup, I'll make sure to have a goals-based vesting agreement from the very beginning i.e. co-founder gets x% on first sale, x% on first raise

I found this particular post from a hedge fund owner quite insightful why the the stock market is unlikely to crash spectacularly if things keep going the way they go with the Fed bank-rolling https://medium.com/@dan_60967/devils-advocate-the-bull-case-.... The ones stating the market is going to crash are also the ones that are either shorting or have closed out their positions, and waiting to swoop in to profit.

I've been using Evernote for 6 years, and still continue to use it for the following reasons:

* Everyday I use https://marxi.co to write my technical work journals in Markdown (with nice extensions like flowcharts) that gets rendered into rich text format within Evernote

* I archive and tag each article I read with the Evernote Web Clipper, because URLs always go stale so you want your own copy.

* Evernote works with https://ifttt.com so it integrates seamlessly with my other applications and workflows

* Evernote is also capable of OCR within PDFs if you use the paid pro version.

* This means that all sorts of note taking is in a single place, making it a breeze to quickly search.

I pay for Evernote to get around the device limit, offline usage etc, as the free version is pretty crippled. I know there are definitely cheaper alternatives in terms of price, but I feel it's worth it for all the features available because I value my precious time, which I don't want to consume more of to maintain the same set of features using FOSS alternatives. Good thing is that Evernote allows export to a human readable archive format which I use to ensure that I have a personal copy of the notes to prevent vendor lock-in.

EDIT: Just formatting

We've already established that the main thing to know what makes your customer tick so I'm surprised this isn't mentioned yet:

Your first MVP is simply a static website describing problem, solution and signup, with Google Adwords and analytics.

* Given that your target market are going to be ideally using Google to search their problem or solution, with Adwords, you can test exactly what they are actually searching for when they are looking for your product.

* Analytics will be powerful to measure the engagement of the user to your desired product. Have buttons or measure scroll for engagement. Do they read your problem and leave? Obviously not relevant. Do they continue onto your solution but leave? Wrong market-product fit. Have options on the website for easy A/B testing to figure out your demographic.

* Static website is super easy to change and make pretty as so many templates out there, and even if you don't use A/B testing tools, you note when you make changes, so you can compare sets of user analytics data.

This approach was popularised by lean startup methodologies, but what I love about it is it takes a couple of hours to setup, and an hour each week to tweak and monitor, and you'll know early on whether it's worth even developing the software from the very beginning. The saved time is worth the adwords cost (you can set a budget per day on their dashboard) and cost of static website hosting.

Totally agree, I've got a solid applied calculus background from my electrical engineering undergrad degree and some DSP in my first job, but avoided learning statistics and probability because I thought it was intuitive. But after doing a MOOC course on Machine Learning, I realise that statistics and probability is more complex than anticipated.

If you don't work on your fundamentals, you end up simply memorising the algorithms and basic applications. Much like the neurons discussed for deep learning, we need to create rich relationships between our own to ensure we retain and can apply the knowledge in the long term, which starts with laying a foundation of fundamentals.

For brushing up on those fundamentals, I recommend Bertsekas & Tsitsiklis : Introduction to Probability. Theory supported with lots of examples, as well as comparing the theory to "intuition" and why it is much more effective to apply the theory.

Good point, that adjective changes everything. In regards to scaling, yes I haven't met performance scaling issues with Python web applications, even when needing long running asynchronous tasks by relying on the ever popular celery and redis, because I've never had somewhat even moderate traffic. In hindsight, I am guilty of over-engineering previous web applications "to deal with potential scaling issues", especially at the infrastructure level, leverage clusters of containers when I could of got away with Heroku.

For Evernote, to write in Markdown, I've been using http://marxi.co and am a big fan of it, though it does cost and runs on only web technologies.

True, I've been using type notations with all my Python 3.5+ projects (and works very well with PyCharm), though noting that this is only a recent addition, available (officially) for very recent Python releases and is not enforced out of the box. And yes, delivering on the project is critical, especially for startups at the very beginning where you're still trying to find product-market fit so sudden production changes need to be swift.

In your case, if you are just planning to de a web API with the majority of the workload being I/O (such as hitting other APIs), then node.js (outperform Python and Ruby out of the box in this case IMO). Otherwise, Python is a more versatile choice. All 3 are relatively easy to start, but given you like Rails, which is big on convention over configuration, the closest you'll get, that has a large community is Django, and a Node.JS counterpart would be sails.js. The biggest difference is in the languages itself, all 3 have some distinct differences in design.

But all 3 suffer from the same issues that dynamic languages have, and weren't designed for enterprise. Node.js is also being added to existing enterprise applications, but normally for anything web facing.

EDIT: Add opinion relating back to main question.

Depends, there are billable hours e.g. time spent with customers and non-billable hours e.g. administrative tasks not specific to any customer such as payroll, transfer of knowledge between work colleagues. So by targeting reduction of non-billable hours, you would have a compelling reason to sell to firms who bill by time.

From my experience, I disagree with the heuristic of money paid within the first month for knowing if you are really talking to users, because it doesn't apply especially for enterprise SaaS, where you likely to have a direct sales model, and as a co-founder with no sales experience at the beginning, as you continue to sell subscriptions, let's say the same functionality within a product, you will improve as a salesperson, closing deals earlier and by that heuristic, you know what your customers want.

Consistent user engagement with the product is a better metric to build such a heuristic, because user engagement is direct correlated to value IMO. That's why I am a fan of even charging $1 per month for a product, because it easier (relative to having given it away for free) to increase pricing based on the value you deliver to your customer, which can be measured through user engagement with the product.

I feel we in New Zealand, despite our small size, we actually have modern POS systems. I have been using contactless Visa regularly for at least 3 years now and have switched to Apple Pay recently. It is so popular here, that relatively small number of vendors who do not have contactless, have stick a physical label on the POS device saying "No Paywave" so when the customer goes to wave, they know do swipe/insert instead.

I've heard that we are a test bed for some technologies, given that the sample size is small relative to the world. An example of this was Pokemon Go, which was AFAIK release first here in NZ (and Australia).