Pros: The company as a whole is doing well, with good revenue numbers. The talent bar is generally pretty high, but it's not as good as it once was, and the company is starting to lose top talent.

Cons: - Toxic management and terrible work-life balance. - Becoming increasingly political, which projects you get to work on, promotions, and performance reviews have been increasingly about who you know. - Within AI, there's constant project churn, changing roadmaps, and a lack of product vision, leading to very few successful products. - Substantially decreased refreshers and compensation recently, especially for those who have been there a long time. - Slow career growth and promotion timelines, and no longer with the increased pay to justify it. - No longer really innovating or doing anything interesting as a company. - Still no 401k.

Pros: - Interesting technical problems. - Co-workers are very smart and very collaborative. Consistent high quality, unlike high variance at FAANG. - Engineering org is still small enough that you can have a lot of impact regardless of your level. - Focus on building great products, cut through BS, company doesn't waste time on distractions. - Well-positioned for lots of future growth.

Cons: Technical debt from organic growth over many years, but this is also an opportunity and the company is prioritizing fixing it. Internal tools could be better, but this is also an opportunity (if you work on a team that works on internal tools) and the company is working on fixing it. WLB is not ideal, but also not as bad as some people say. It seems to be more a function of the kind of people Databricks hires than something imposed by management.

Pros: The company really cares about innovating and executing fast, and customers feel the same way.

Cons: Not enough insights to share.