In March of 2019, Stripe famously wrote that their 5th engineering hub would be remote. Other startups and early-stage investors followed their lead. What was previously seen as taboo — having and backing remote companies — became normal overnight.¹
What happened was such a strong shift, it reminded me of the first time I stepped inside of an Uber. In the transition, we gained a few great things, but lost some of the great aspects of the office.
💁♀️ Team: being part of a team that is collectively working together at the same time in the same place. An all-hands meeting is an example of this. Another example is looking up from your desk and seeing everyone else in the same office at the same time: a type of peripheral vision that’s always on. …
Yesterday, Google announced they are shutting down Google Hire, their Applicant Tracking System (ATS). At Agave, we understand how difficult it can be to deliver great hiring software to the market. This is why we want to fill the need Google Hire’s impending shutdown will create.
Agave Hire was born out of frustrations I experienced as a hiring manager in a hyper-growth tech startup. I was in your shoes, trying to figure out which ATS product to use, given there are hundreds to choose from. …
I really enjoyed an interview with the CEO of Hubspot.¹
Business software is moving towards freemium models. Nobody wants to talk to sales reps, they want to self-evaluate. User experience (particularly on-boarding) is the new key differentiator.
This makes sense. At Agave, we use a lot of B2B tools. There’s Google Suite, Slack, Heroku, Slab, GitHub, Asana, many more. I’ve never spoken to anyone at any of these companies, ever. I just signed up, started using it, and then pulled out a credit card when it made sense. …
At Agave, we redesigned the logo and acquired a new domain a few months ago. And we’re moving to the next phase of the business, which requires new tools, architecture, and designs. This includes moving our codebase to ReactJS since we’re building a much more responsive web app and the jQuery/Coffeescript we were using before wasn’t going to be suitable for where we’re going.
When we decided to started working on this new product, we had a lot of decisions to make. The front-end in particular was going to need to be completely revisited.
I spent a few weeks researching the right combination of libraries and UI toolkits. There’s a Hacker News comment that summarizes a great shortlist here: https://news.ycombinator.com/item?id=17971337. There are many more UI libraries out there, but most of them aren’t worth looking at. …
Most companies are lucky if they can find a 5 letter .com domain that’s memorable and easy to spell. With Agave.com, we liked that it met the criteria for a memorable and simple name, but there’s a story behind it too.
If the first thing you think of is tequila when you hear “agave” that’s because it’s made from the blue agave plant. There’s a few similarities between making tequila and conducting interviews:
The difference between a negative and positive experience comes down to the process. …
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The CEO of Carta shared a new offer letter in 2016. When I saw that offer letter, it told me more about the company than anything else. That offer told me this company values transparency and more importantly they value their employees.
The offer letter hasn’t seen any changes in decades. The problem with offer letters is they were designed by lawyers. That happens to be both a feature and a bug. It’s a feature because the company needs to protect itself with the legal language of the offer. …
I’ve talked to various hiring teams over the past several months and after spending 3 years building out an engineering team myself, I was surprised by some of the things I discovered.
The teams I talked to range from very small (1 or 2 founder teams, obscure startups) to very large (thousands of employees, leading startups). I’ve condensed over 50 hours of conversations and thinking on the topic here. I’ve also talked to a few CEOs of ATS platforms who have spent 10+ years working on these problems.
Here’s what I’ll talk about:
I first learned about Tophatter in May, 2017 during a job search and to be honest, it wasn’t quite love at first sight. When I looked at the app, I found a dated UI with a quirky logo and muted color scheme. That’s when I knew they could use some help.
When I met the team at Tophatter, I realized that the brand and design didn’t accurately represent the qualities of people who worked there: friendly, smart, reliable, open-minded, and full of energy and excitement. I was amazed at how I had totally changed my perception of the company after speaking with the team in person and realized that others were probably making the same incorrect assumptions about Tophatter, purely based on its design and branding. …
By Chris Estreich, Co-founder & CTO at Tophatter. This was originally published internally to our engineering team, but we decided to open it up for others who are interested in learning how machine learning can be applied to classification problems at scale.
A taxonomy plays several important roles on marketplaces like Tophatter.
For shoppers: it aids information retrieval by enabling a browse & drill-down experience. Intuitively, we expect an efficient route to the set of products that a customer cares about to outperform an inefficient one.
For Tophatter: it is a form of business intelligence. More specifically, it’s an effective way to group products in order to identify key outliers (over-performers or under-performers), and spot areas where there exists a supply / demand imbalance. These insights can be used to make impactful changes to the distribution of products that we prioritize. On a typical day Tophatter shoppers make nearly 100,000 purchases, and each purchase represents an instance of our inventory scheduling algorithm choosing a particular product to prioritize from a set of millions of products. In order to make smart choices, this scheduling algorithm needs to have a good understanding of what a product is, and how well it might perform. The taxonomy is a key piece of metadata that enables the scheduling algorithm to make smart decisions. …