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Engineering 2022 in review

Adam Mills

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Jan 20, 2023
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0
min read

Year 5 has been HUGE for our Engineering team @ Hatch. Here are our highlights.

Year 5 for the Hatch Engineering team was focused on supporting our transition to a marketplace open to all talent, not just students, and what a year it was.

Our 2022 Technology & Practices Radar.

Engineering 2022 Highlights

Marketplace

The march towards the marketplace vision saw the consolidation of a number of products/tools we had provided to the market in 2021. This allowed us to simplify our offering as well as the code that delivers it, with a large amount of our legacy 1.0 code being removed. As part of this we released Team content for companies, fit matching, Sign Up with Google (which counter intuitively for me, only accounts for 50% of sign ups!) and a large investment in the generation of role recommendations for candidates.

If you haven't yet, check out all the latest features on Hatch's new website.

Fully serverless!

At Hatch we have an engineering principle of Serverless First. In 2022 we decommissioned our last container running internal analytics and after 5 years we are 100% serverless 🥳. Ironically, it was also the year we first hit serverless scaling issues. With the 2022 focus on GTM growing our user base and role recommendations, our data science workload started to reach the time limits of AWS Lambda. Our infrastructure is geared towards OLTP but we worked around it in a lean fashion by partitioning the workloads. Our data engineering infrastructure will be a focus for 2023.

Yep... that's our Product Engineer, Steve.

Hatch-a-thon

Hackathons were back in 2022! Cross-functional hackathons are quite challenging, trying to ensure everyone has something to do and it’s not just people sitting around watching engineers code. The teams all did an amazing job of shipping a solution to their problems, lots using low/no code solutions. It’s amazing how lean we can be in taking a first step towards solving problems. How we can include this style of iterative problem solving in 2023 is a big question for Hatch.

Self-serve internal tools

A big goal for Hatch’s engineering team is empowering #self-serve to the wider business. Ever since the labour exchange in 2020, we have been making heavy use of low-code tools to facilitate this. We have learnt lots of lessons of walking the line between incurring too much tech debt and the velocity of learning rapidly iterating brings. 2022 was no different, Airtable became the operational control centre for ingesting external roles to Hatch. Our website refresh was done external to engineering via Webflow. Segment (gosh it’s expensive for startups!) continues to empower GTM to setup and use new tools for analytics and email. In 2023 we are aiming at exposing our data swamp to the business with self-serve BI tooling.

So long, and thanks for all the fish

This will be my last update from Hatch, I’m heading to new pastures in 2023. Sean Xiong will be taking the helm and I, like you dear reader undoubtedly are, am looking forward to reading about 2023!

- Adam Mills, Head of Engineering @ Hatch


P.S. Everything has to include something about ChatGPT at the moment. I tried giving it our raw meeting notes of our 2022 retrospective and asked it to write a post. Check out its version below... Is my writing career over?


Blog post written by ChatGPT from raw meeting notes

2022 was a year of transition and growth for Hatch. Our team faced new challenges and achieved significant milestones as we worked to improve our product and better serve our customers.

One of the biggest highlights of the year was the successful integration of a matching feature into our product. This was a critical missing piece that had been a long-time goal for the team. Additionally, we were able to improve the overall user experience and feel of the product, creating a more coherent design language and UX. We also implemented third-party sign-in, making it easier for users to access our platform.

Another major achievement was the move back to a more focused marketplace model, after a short detour into the SaaS space. We also incorporated data science into the product, using machine learning algorithms to improve matching and recommendations for our users. This was a big step forward for us and allowed us to make more data-driven decisions.

We also faced some challenges in 2022. Some of our features felt over-engineered for what they were currently doing, which led to redundant code. We plan to address this in 2023 by simplifying these features and moving towards a well-defined structure with a clear purpose. Additionally, we aim to optimize the application journey to reduce the drop-off rate.

Looking ahead to 2023, we're excited about the potential for our evergreen profiles to create a more social feel to the product and for the opportunity to refine the application process to provide a smoother experience for candidates. We're also working on new team structure, and to design and build more innovative experiences, such as team fit UX.

Overall, we feel that we have made a lot of progress in 2022, and we're excited to see what the next year brings. We'll be focusing on scaling, simplifying complex features and maintaining the focus on evergreen.

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