This episode is a Q&A session following a keynote at Craft Conference 2024, where Gergely Orosz (The Pragmatic Engineer) answers audience questions about the current state of the software engineering industry. He covers how high interest rates are reshaping tech investment and hiring, why even profitable big tech companies are conducting layoffs, whether crypto is draining capital from the industry, the return of “mini waterfall” development, how Eastern European markets are affected by US company hiring trends, and how to distinguish genuinely transformative technology from overhyped dead ends. Throughout, he draws on his experience as a former Uber engineer and his ongoing analysis of tech industry trends.
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Will tech progress continue in a high interest rate environment?
- Tech has advanced in high interest rate periods before, such as through the 2000s when the internet and smartphones emerged despite rates around 5%.
- AI is seen as similarly promising and will likely continue to drive progress.
- The key difference now is the end of free distribution: in earlier eras, startups could launch and get discovered organically (websites via search engines, apps via app stores), but today new AI startups must pay for ads on Google or Apple platforms to acquire customers.
- This raises the cost of growth and will likely make expansion slower and more capital-intensive, but innovation will continue at a steadier, less speculative pace than the 2020–2021 boom.
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Are Shopify’s two mastery paths (management vs. individual contributor) coming with similar compensation changes?
- Gergely does not work at Shopify but reports that employees have not yet received their first raises under the new mastery-based system.
- There is speculation that current salaries have been adjusted based on mastery scores, with the expectation that higher mastery leads to higher pay.
- In practice across the industry, promotions to the next level typically deliver larger compensation increases than mastery-based raises, though they come with higher expectations and stress.
- Shopify’s approach may offer smaller, more granular raises and bonuses for mastery gains, which also provides career stability for senior engineers who prefer not to move into tech lead roles.
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Why are big, profitable companies laying off?
- Mark Zuckerberg described two types of layoffs: first, correcting over-hiring from the pandemic when growth expectations were too optimistic; second, discovering that productivity didn’t drop after the first round and cutting further.
- Publicly traded companies are under pressure from shareholders to maximize returns, which can mean reducing headcount or compensation even when the company is highly profitable.
- Companies like Google have disproportionately cut experimental “bets” rather than core profit centers.
- Gergely argues this is a short-term financial strategy driven by CFO-minded leadership focused on 1–4 year horizons rather than long-term health, and it severely damages morale, pushing employees toward startups where they feel they matter more.
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Is crypto vacuuming money out of the tech industry and contributing to layoffs?
- Gergely covered crypto extensively around 2021, noting extreme spending (e.g., Coinbase paying $65 million to Datadog for observability during the boom).
- He does not believe crypto is significantly draining capital from the broader tech industry anymore, as VC investment in crypto has dried up.
- Crypto companies have proven surprisingly resilient, and while meme coins and influencer-driven speculation persist, the sector is unlikely to attract the level of investment seen in 2021.
- Investor disappointment with crypto is high, and the space is expected to remain small relative to the rest of tech.
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Are we going back to the Waterfall model?
- Gergely discussed this with Kent Beck, who acknowledged a return to waterfall-like practices.
- Classic waterfall meant 6 months of planning, 18 months of building, and a release two years later. What’s returning is “mini waterfall”: 1–2 weeks of planning for a 2–3 month project, then building and deploying.
- This is how most mid-size companies already operate, and it’s being formalized through RFC (request for comments) documents and upfront planning.
- Agile was originally criticized for devolving into mini waterfall, and Gergely notes this pattern is now explicit and widespread, for better or worse.
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How does all this apply to the Eastern European market?
- Much of Gergely’s analysis focuses on the US and Western Europe because they drive global demand, but US companies are increasingly hiring in Europe.
- US-based companies hiring remotely or opening local hubs in Europe offer better compensation and career mobility, which is reshaping local markets.
- Google, for example, laid off US workers from teams like Flutter and hired in Munich instead.
- A US tax change (Section 174) makes it more expensive for US companies to hire foreign developers, which could reduce offshoring incentives.
- Eastern Europe remains attractive due to cultural similarity with the US, lower miscommunication, and competitive costs: one large company found India cheapest and Hungary second-cheapest for global hiring.
- Companies like Stripe (Romania), Adobe (Romania), and Google (Budapest) have established or expanded offices in the region, and Gergely expects this trend to continue or even accelerate.
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How do you distinguish between technology leading to the future versus overhyped dead ends?
- The honest answer is that people often learn by getting burned by overhyped technologies.
- The best practical approach is to build a prototype to test whether the technology actually works for your use case.
- Gergely gives an example from Uber around 2017, when teams could choose their backend language. His payments team chose Java for its mature libraries and stability, while many newer teams chose Go, which was then still maturing.
- Within a year or two, Go teams faced significant pain due to missing tooling, libraries, and performance optimizations that Java already had. Go later caught up and became competitive.
- The lesson: do thorough research, make the best decision you can with available information, and accept that some risk is unavoidable when choosing between a proven option and a promising but immature one.