dpandya

Verse Medical | Full Stack Software Engineer | NYC preferred, remote (US or Canada) also works | Series A startup

It costs nearly $12,000 a night to spend a night at the hospital in the US. We're building software that allows patients to recover at home sooner and with better results. We're backed by top investors in technology & healthcare (e.g. Y Combinator, SignalFire, Paul Graham, etc.)

We have a product & engineering focused culture with minimal bureaucracy. We use Python and Typescript with GraphQL to tie it together. But, we're confident good engineers can learn new technologies so we don't require any particular language/framework background.

We're growing fast, are well-capitalized and growing our engineering team!

Hiring across a range of experience levels (new grad to staff). Email dhaivat AT versemedical.com to apply.

Please correct me if wrong, but these are likely measured via the book value of the investments which reflects the private market valuations of the companies you mentioned.

The target market for Google Hire was probably Lever's (https://www.lever.co) customers, i.e. mostly funded startups and other companies hiring white collar employees. For these businesses, $200-400/month for an Applicant Tracking System is pretty inline with market. Lever's pricing is higher as far as I've seen.

As someone working in this area, this is an interesting article.

The core issue of compliance is somewhat buried in the text, but worth pointing out. Optometrists' chief complaint is that very few offices seem to be prescribing the Hubble contacts brand specifically and yet, Hubble seem to be selling them to customers. This implies to them that either all prescriptions aren't being verified or are somehow being "passively" verified. Within the current rules set in place by the FTC, they believe it's unlikely quite so many prescriptions are passively verified.

The FTC is actually actively working on developing new rules around prescription verification to address some of these concerns. [1]

[1]: https://www.ftc.gov/news-events/press-releases/2019/05/ftc-s...

You could make this same argument to argue that Slack would fail against email.

Something like: there are all kinds of email integrations, user-specific and group-specific setups, etc. at companies. How can Slack ever compete?

The answer was that Slack was so much better for many companies that it made sense to suffer the pain of switching.

The company that beats Slack will likely be 10x better communication software or something very similar but distributed much more effectively (maybe Microsoft Teams in the enterprise).

On the flipside: if you're a person that's convinced Uber should be valued at a fraction of what it is and you're not shorting it, why aren't you?

You might argue the market will remain irrational, but this is unlikely to be the case for 25+ years. This should mean that most people set against the Uber IPO should hold a short position with at least a small portion of their net worth. Doesn't seem like this is the case.

Whether or not a company is a "tech" company is kind of a muddled question, but taking even a brief glance at https://airbnb.io/ (their engineering blog) makes it clear that AirBnB does some pretty serious engineering.

For example, their post about their work in search ranking is quite interesting [1].

[1]: https://medium.com/airbnb-engineering/machine-learning-power...

I meant applying a linear approximation.

Not meant as a critique to this book, but the fact that RL-based approaches rarely work for optimal control problems (in, for example, robotics) came as a surprise to me, given the hype and focus on RL [1]. It turns out that model-based methods for optimal control (e.g. linear quadratic control) invented quite a long time ago dramatically outperform RL-based approaches in most tasks and require multiple orders of magnitude less computational resources. Maybe there's some hope for RL method if they "course correct" for simpler control methods. At the moment, it seems like RL for robotics and control lies to the side of "research" and not "engineering."

[1]: https://www.alexirpan.com/2018/02/14/rl-hard.html

This seems like a questionable comparison.

Apple Music, et al. license content and there are few companies that are able to do this. This creates a barrier to entry that wasn't present for the "content clubs" Gates discusses. In fact, his primary point is that due to the lack of a barrier to entry in the market and no accumulating advantage of any kind, there wouldn't be a single dominant player.

One of the keywords you're looking for is "statistical forecasting."

It's a fairly specialized data science skill since it requires experience with some fairly specific techniques (e.g. dealing with seasonality, autocorrelation, etc. within data has all kinds of interesting solutions).

This is great to hear! We've had a peak sales day thanks to all the HN-directed customers.

These are all great points.

> Where did you guys get that idea that prescription should match so very precisely?

It's often much less about the prescription than the characteristics of the material used for the contact lenses and the measurements of your eye. The base curve and diameter portions of the prescription are used to capture this.

> Why do you need a specially trained person to dispense a box of contact lenses?

There are two reasons. With the wrong set of contact lenses (e.g. off-prescription color contact lenses that people wear on Halloween), you can significantly harm your eyes due to low oxygen permeability in the lenses, lack of fit, etc. Second, the contact lens/glasses prescription renewal process forces people to get an eye checkup done, which can often allow the doctor to identify other problems (e.g. infection, cataract, etc.)

It's subjective whether or not using this as a forcing function is really the "right" thing to do, but it does prevent people from living with undiagnosed issues.

> Also, what's the deal with vision insurance?

As people get older, the likelihood of an eye issue increases dramatically. This depends on your specific policy and what it covers, but there are "insurable" (i.e. low likelihood of occurrence, very high cost) events that can occur with your eyes that your VSP policy may cover. I'm not deeply familiar with this, so I can't comment extensively on it.

Sure, I can talk a bit about it.

Essentially, the problem (like all other ad opt. problems) boils down to estimating the expected value of a particular click. This is a particularly challenging/weird problem in this space because unlike other segments of ecommerce, you can't successfully optimize for correlated metrics such as engagement. So, it's a heavily imbalanced problem (i.e. few positive examples, lots of negative examples). In addition to that, the buying characteristics of specific products are heavily related to one another so sales on one affect how we advertise the other. There are a number of other subtleties discovered over time.

Our software produces good bid estimates despite these characteristics.

+1

We don't claim to be the cheapest on all products yet - there's some bizdev work to do before we can say that.

That sounds interesting, but if you've been prescribed the Acuvue Moist, you can only purchase the Acuvue Moist as per law. So, although this info would certainly be interesting (and maybe reduce some customer confusion), it wouldn't actually be actionable.

We're transitioning to a new website ( which is already live on mobile devices when you go to https://beta.jetlenses.com/ ) . It's probably order of magnitude better and the logo is rendered as an SVG :)

Interesting point. We currently direct a lot of our customers to Opternative (https://www.opternative.com/) to renew their prescription. Medium term, we might look into doing some of this in house.

Yes! Please just email me at dhaivat @ jetlenses.com with the specific lenses you need and we can figure out if we can get them for you.

This is a really important question and @alaskamiller has got the right points other than the selling software to others bit - we're pretty confident the stuff we're building is impactful in our space since we're seeing the results.

In comparison to Hubble: we don't require customers to get a new prescription. Just order from us, save money.

Long term, the process improvement software that we're building as well as the intelligence around actually acquiring customers will be defensible because it is hinged on customer and supplier data. Happy to talk about this more - dhaivat@jetlenses.com.

Basically: scale and supply chain. On some lenses, where we're on an even playing field, we're able to dramatically beat everyone else on price (e.g. Biofinity Toric XR, MyDay Toric, Proclear Toric XR).

As we grow and we can add more suppliers, we'll be able to have the best prices across the board.

It depends on the particular contact lenses - can be anywhere from 1 - 8+.

Hi. If you have out of network benefits in your insurance plan , then we can provide you with the necessary paperwork to make a claim. We can also process HSA/FSA cards at checkout. We aren't an in-network provider for VSP yet, however.

> Looking for a SaaS idea? Ask random people in a target industry what kinds of things they do with Excel.

Strongly disagree with this based on personal experience in "traditional" spaces that rely heavily on spreadsheets. There's a reason most of the financial industry uses Excel spreadsheets and it isn't because they can't afford to pay for specialized software. Excel spreadsheets are incredibly versatile. Your data format can change a little bit over time and you'll still be fine. With a custom software solution, you're kind of stuck within the confines of what the developers/product managers gleaned from your working process.

One of the most concerning aspects of the Theranos investment has been the total lack of due diligence in this process.

Putting aside the technology for a moment (it could be considered difficult to evaluate for most investors), due diligence failed on multiple counts. For example, Holmes told potential investors they had over $100 million in revenue when, in reality, they had close to $100,000 in revenue. That's a bit like trying to tell someone a SMB SaaS business with ~100 customers has the same traction as, say, Algolia. Hard to understand how this passed through the filters.

> It's sad, really. It's one of the really innovative companies, but it's not easy to sell tech ahead of its time.

This glorifies failure quite a bit. One major objective of tech companies is to produce products that customers value and like. Lytro failed to do this. Just because the underlying science is complicated doesn't make the tech "ahead of its time" due to the fact that maybe the tech, as implemented, just isn't what people want, now or in the future!

Having complicated science underlying a product certainly doesn't excuse a company from producing products that people want.

> Starting a startup is great and you totally should.

Wouldn't you ask the same set of questions that you describe for this position as well? Why is the outcome different? Arguably, you're taking so much risk as a founder that your expected financial outcome will almost certainly be worse than working at Facebook/Google/Amazon in the early days.

> It may just be that we don't have the right tools at this point.

The real reason is that the solution to this problem isn't valuable to most people that have the resources to pay for a solution. Most bugs aren't caused by issues in the C compiler.

There are many technically challenging, interesting problems that face a similar predicament. The people who solve them will generally find some way to tie them back to reality.

ZenReach (https://www.zenreach.com/) has done this for quite a bit of time and has grown very fast doing it.

It's unclear how Yelp's offering is differentiated from ZenReach's, but Yelp may capture a significant share of the market simply by virtue of the fact that they have excellent reach into brick and mortar businesses.