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3 min read GitHub’s incident on 17 August 2026 ran from 13:28 to 21:15 UTC, seven hours and forty-seven minutes. At peak, web and API traffic saw error rates of around 20%, while archive and raw-content downloads reached roughly 50%. SAML and OIDC authentication, SCIM and Team Sync were affected alongside Git operations, Actions, Pages, Issues, Pull Requests

7 min read There are cloud outages, and then there are us-east-1 outages. That distinction matters because failures in AWS’s Northern Virginia region rarely feel like ordinary regional incidents. They tend instead to expose something larger and more uncomfortable: too much of the modern internet still behaves as though one place is an acceptable concentration point for infrastructure,

7 min read Artificial intelligence is making software easier to produce. That much is already obvious. Code that once took hours to scaffold can now be drafted in minutes. Boilerplate, integration logic, tests, refactors and small internal tools can be generated with startling speed. In some cases, even substantial pieces of implementation can be assembled quickly enough to

10 min read Whilst AI has compressed the visible stages of software delivery; requirements, validation, review and release discipline have not disappeared. They have been pushed into automation, runtime and governance. The real risk is not that the lifecycle is dead, but that organisations start acting as if accountability died with it. There is a now-familiar story about

4 min read How AI Is Shifting Software Engineering’s Primary Constraint For most of the history of software engineering, the primary constraint was production. Code was expensive, skilled engineers were scarce, and shipping features required concentrated human effort. Velocity was limited by how fast people could reason, implement, test, and deploy. That constraint shaped everything from team size,

5 min read Autonomous Code, Trust Boundaries, and Why Governance Now Matters More Than Ever In Part 1, we looked at how AI has reduced the cost of building monitoring tools. Then in Part 2, we explored the operational and economic burden of owning them. Now we need to talk about something deeper. Because the real shift isn’t

6 min read The Real Cost of Owning Monitoring Isn’t Code — It’s Everything Else In Part 1, we explored how AI has dramatically reduced the cost of building monitoring tooling. That much is clear. You can scaffold uptime checks quickly, generate alert logic in minutes, and set-up dashboards faster than most teams used to schedule the kickoff

5 min read AI Has Made Building Monitoring Easy. It Hasn’t Made Owning It Any Easier. A few months ago, I spoke to an engineering manager who proudly told me they had rebuilt their monitoring stack over a long weekend. They’d used AI to scaffold synthetic checks. They’d generated alert logic with dynamic thresholds. They’d then wired everything