Gergely Orosz
Engineering industry analysis
Author of The Pragmatic Engineer, the most-read engineering newsletter. Covers how AI is reshaping software teams.
Recent activity
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The rapid advancement of AI technology has significantly increased the risk of software security breaches, making it essential to rethink software security measures. AI-powered attackers can now automate and speed up attacks, exploiting critical vulnerabilities before patches are released, and accessing systems externally or remotely. To combat this, automated patching and ongoing monitoring of security breaches will become non-negotiable, and defenders will need to use AI agents to stay ahead of attackers. AI summary
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Git had too many performance problems at 30,000 PRs per day, so Anthropic built its own. I talked with the team, including asking why they didn’t open source its new system, ‘Scion.’
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Ramp and Stripe built platforms for non-engineers to build internal websites and tools with, and both are taking off in those workplaces. I expect more companies to do the same.
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The Firebase iOS SDK crashed after a backend change, crashing all apps which used Firebase analytics for 2-6 hours. Google didn’t update the status page, but did offer a postmortem 4 days later.
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In his Rails World keynote, David Heinemeier Hansson (DHH) declared the end for writing code by hand for professional work – at 37signals at least. Is this change now unstoppable?
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After a GPU shortage and memory shortage driven by AI companies, we’re now experiencing a CPU shortage, thanks to AI agents using a lot more CPU with tool usage.
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Uber, Pinterest, Stripe, Coinbase, Ramp, and AT&T are making large savings on their AI bills by dropping proprietary models and using smart model routing.
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An in-depth report by Reuters details how Meta’s leadership decided to slash team sizes by 60%. Zuckerberg changed his mind, and now the company is stuck with low morale and culture turned mercenary.
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The pace of change in software engineering is only accelerating, especially since January of this year. This is all to do with the industry-wide adoption of LLMs, AI tooling, and AI infrastructure. At The Pragmatic Engineer, we always want to capture as much of what’s going on
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Asana migrated off testing framework Enzyme in two weeks: without AI, this work would surely have been kicked down the road. Airbnb and Uber share similar stories and AI seems excellent at migrations.
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This email is a response to the 50+ podcast pitches that arrived in my inbox just last month, and keep arriving in growing numbers, from PR agencies and marketing teams at various companies. It's also a message to tech founders building stuff for developers: focus on building something
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In what was predictable: Meta’s layoffs and forced reassignments pushed engineers not impacted by either to look for a new job. Meta is now offering large equity retainers, and it doesn’t seem working
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Devs discover that Grok CLI pushed all local files, .env files and git history have been pushed to a GCP bucket, unencrypted. SpaceX’s initial reaction? Blame the devs
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Bending Spoons' acquisition strategy involves acquiring struggling businesses with well-known brands, taking over operations, and operating the product with a fraction of the original staff. This approach often results in significant cost savings and increased efficiency, as seen in the acquisition of Evernote and the subsequent rationalization of the architecture, migration to cloud-native setups, and significant performance improvements. AI summary
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Spotify’s podcast platform has become chronically unreliable since the company’s leadership started boasting about AI adoption. Competitors haven’t had similar issues, so I offboarded from Spotify.
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Top of mind for engineering leaders: what to do about the growing code review load, and how devs are starting to review code less thoroughly than before? Many questions, but few proven solutions.
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To a sceptic, spending $165K to migrate Bun from Zig to Rust sounds very expensive. But to a realist, shortening a 1-2 year migration down to 11 days opens amazing new opportunities for devs. However, a thoroughly-tested project is required to pull it off.
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Power users generate 10x as many lines of code vs the median, most of the AI spend is coming from input tokens not output ones, and almost half of AI changes are accepted without manual review by devs (!!)
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Are there any ‘intelligent’ router solutions out there which select the right model for the right task? I looked into it, and there are a few options.
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In 2022, I wrote about the damning fall of events tech company Pollen. The short of it: Pollen seemed to have pulled off the improbable feat of building a business in the notoriously low margin industry of events, surviving Covid-19, and building a solid software engineering organization. In April
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