emeerson's comments

Orchard | Software & Infra Engineers, all levels | NYC, Austin, DC, Atlanta, Remote | Full-Time

At Orchard we're building software for life's biggest financial decision: buying and selling a home. Our products solve problems along the entire lifecycle of the home-buying transaction: from finding your perfect home to coordinating with multiple parties along the way so that the entire experience is seamless.

We're looking for software engineers at all levels and especially Senior and Staff engineers to work on scaling our consumer-facing web services, developer tooling & workflows for scaling business ops. We work with Python 3, TypeScript & Angular, Docker deployed on AWS.

Details: https://orchard.com/careers/engineering

Agree.

Further corollary: more workers will be concentrated around 2nd-tier hubs where their wages will be lower than 1st-tier, but higher that median wages. 2nd-tier median wages will then drive up housing prices which will rinse & repeat COL increase trends seen in the Bay Area.

Hopefully these other hubs will have better development zoning & housing policies than San Francisco / Bay Area.

Orchard | ONSITE (WFH for now) | Full-time | https://orchard.com | NYC - New York City, NY

Orchard is building software for life’s biggest financial decision: buying and selling a home. Our products solve problems along the entire lifecycle of the home-buying transaction: from finding your perfect home to coordinating with multiple parties along the way so that the entire experience is seamless.

We are hiring software engineers, leads and managers in all 3 of our product areas: consumer, operations platform & data.

We're a 3-year old series B company tackling a massive $1.5 trillion market in residential real estate. Our business is growing fast and we have an exciting technology and product roadmap ahead of us.

Our tech stack consists of Python3 with type-hinting on the back-end and TypeScript & Angular on the front-end, with PostgreSQL as our DB. We leverage RedShift for analytics pipelines, Python, SQL & Airflow to orchestrate ETL pipelines, and Static Site Compilation + Material Design components for low latency user experiences. Our services are developed, built, tested and deployed via Docker containers on Kubernetes.

Software Engineer: https://boards.greenhouse.io/perch1/jobs/4487204002

Engineering Manager: https://boards.greenhouse.io/perch1/jobs/4487207002

Interview Process: 2 coding (pragmatic engineering leaning), system design + product collaboration, & behavioral engineering career learnings.

You can also send an email to elijah+aug20 [at] orchard [dot] com to learn more.

Super helpful - thank you! IIS / containerized .NET apps that may be optimized in Azure is compelling.

Exciting is also a confusing property for me.

AWS has offered a superset of services beyond what I or colleagues have ever been able to apply.

Makes sense that business incentives inform decision making, but how do you explain the difference in Twitter's content policy? They also, presumably, measure their business via MAU & DAU.

Sometimes I think its as simple as humans making decisions. And Zuckerberg is making a spineless decision (by way of inertia).

Initially I thought of those numbers (36m in the US) as totally unrealistic. But then comparing to seasonal influenza case counts, they seem to be within that order of magnitude (39m-56m cases): https://www.cdc.gov/flu/about/burden/preliminary-in-season-e...

would that be implausible? am I misunderstanding or comparing the wrong metrics?

I'm actually curious to see the time interval of when the first true COVID-19 case appeared plotted over first true 2019-2020 influenza cases. If along the same timeline, you'd figure that social distancing would have affected the R0 of both.

Assuming that SARS-CoV-2 is truly more (or comparably) contagious, 36M could be plausible.

To be clear: I am not equivalating COVID-19 fatality rate w/ the flu, or suggesting it is "innocuous" as the flu is.

Re. Money in a bank account not contributing to scarcity: I think that logic checks out when you observe money as a resource in isolation.

If you think of Money as a proxy for "captured value," then one way to look at it is how much "captured value" is "captured opportunity for wealth creation," which has a certain distribution % chance across the entire population.

In that sense, total aggregate money at any point in time can be viewed as zero-sum.

Interesting to present it as a binary tradeoff.

I want to win, but I want to make sure that the thesis has some modeling diligence =)

Strongly agree with this. Dates serve a critical goalpost in technical planning, yet they should be viewed as flexible (having a reasonable margin of error) and informed by tight & trust-driven feedback loops. I subscribe to Gantt charts as a planning tool, not a bible. Use it to empower development teams to plan and track execution, but don't use it for 0-margin accounting.

One anti-pattern in engineering management is shielding engineers entirely from timeline estimates. A CEO with limited runway, reporting to the Board, doesn't have such a luxury of infinitely elastic time.

Edit:

Note: dates should never be prioritized over value. If you're hitting dates and not delivering value then it won't do good for anyone. Product value should always be the function to optimize for, but rarely is it entirely independent of time.

not an argument, an attempt to synthesize this event into a parable. Failed attempt at that ;)

To clarify my thinking: defunding Govt' pandemic preparedness became a forcing function for the individually wealthy to deploy private capital with much higher $$$ cost.

Point taken that its a stretch of the imagination.

What's remarkable is how this is a clear case study of the amount of wealth destroyed _by gutting government_

If I were to try to be pithy: Capitalism destroyed by the incompetency of libertarian ideals.

I suspect this is because these are wolves in operator's clothing. If you deploy true operators that are doing labor in their area of expertise, and if they can pre-empt obvious mistakes + generate reproducible playbooks, you could net out ahead.

Won't claim this is the absolute priority, but recently been thinking about the generalizable problem of: "domain disentanglement."

In other words: solve the Data Model Coupling problem programmatically. Applied to an RDBMS, one could imagine a graph with weighted edges representing coupling between database tables and dynamically reverse-engineering joins into DB-isolated API calls.

PG, this is a thoughtful essay. Yet I'll point out a flaw in this thinking below.

Intellectually Honest merits here: - you want to incentivize people to create value for society and optimize globally by raising the quality of life of (most) humans. - Wealth creation itself is not by default at the cost of others.

Intellectually Dishonest: - That startups and wealth creation converge on a quality of life optimization function for humanity.

In other words: startups and wealth creation operate within the randomness of free market. And most software technology in the last 30 years has not unlocked some kind of massive step function value in global problems.

If we could align more Venture Capital funding and R&D output to solve fundamental problems (in other words: can we solve access to affordable nutritious food, reduction of common disease, reducing cost of housing ahead of 5-minute media formats or SaaS Invoicing Applications?)

Housing has continued to become less affordable and poverty still prevalent in the US.

- That there is a binary debate: "should there be wealth or not?"

Social Programs, funded by government, funded by taxes on higher earners and large capital gains, are one lever to address this.

The reason the inequality gap matters is less that its a metric of the _delta in absolute wealth_ but more that opportunity and livability of average Americans has a worse outlook in the last 20 years, not a better one.

You don't have to imagine. You can do a real cultural economic comparison to other countries: Italy, Greece, Russia, Spain (and others) are countries that index more on your proposed value system: socialization, family, quality of life over hard work.

China, Japan and the US index very highly on the productivity side of the spectrum, China probably significantly more than the US.

Some of those QOL-indexing countries also have high unemployment rates and relatively lower GDP per capita.

Unemployment + GDP are probably the wrong things to optimize for. Personally I believe Unemployment is overloaded as our optimization function for economic health, where median wage increase is more representative of livability.

One question I have (and genuinely can't guess at): if you are unemployed in Greece, on average, what exactly is your quality of life?

All that said, there are countries that strike a healthier balance with strong economies: Germany, Canada, UK.

Zooming way out, my take on productivity generally is: human pressure to push our productivity is inevitable because we still need to solve some very hard, expensive problems: (1) Our history of industrialization has led to unsustainable environmental impact. This may require 10-100x the engineering focus & coordination we've ever had before. (2) Disease still has significant impact. (3) We still need human labor to harvest and transform resources (agriculture, metals) (4) We still need human labor to generate more "life necessities" supply: electricity, housing, water / plumbing.

One could argue that for (3) & (4) we can be more like Germany and we'll still do great. Also one could argue that if we increased taxes / shifted government spend to subsidize housing development (vs. home ownership) we might also be fine.

Edits: grammar

Is this even addressing the root cause of 2016 misinformation campaigning? I was assuming most misinformation was distributed as user-generated content, not ads.

How much was Spotify exploited as a media platform for campaign misinformation? Its cute that Spotify is doing this, but I think Facebook + Twitter were the big distribution channels (and probably Reddit is closest to the “astroturf core”).

Edit: grammar

eerily poignant

This is very wise advice, and I can especially appreciate the layer of empathy: empower engineers to add to their toolchain (mgmt or technical).

To complement this thinking, however, I also expect a leader to align engineers to business priorities. There is a fine line to walk in balancing the growth of engineers with the needs of a business. I expect engineers with certain years of experience to understand that as professionals we are hired to address these needs.

Of course there is also the flip side of this alignment: aligning the business to the real (vs. imagined) capabilities or investment needed.