An easy tell for how good an engineer is is what % of their time they spend on instrumentation, measurement, profiling, telemetry, analysis (and how well they leverage this expertise during incidents).

For AI to outperform human coders, the context and prompt will need to be enriched with data from the live production system. This will lead to self-improving, self-repairing software.

Few things match the empowerment of the individual that vibe coding begets. The personal computer gave us such a leap.

It’s very easy to dismiss it from the glass house of years of engineering experience, CLIs and IDEs.

But technology’s main purpose is its own democratization

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Increasing convinced observability and monitoring as it exists today will soon cease to exist. Two counter trends: autonomous infrastructure & AI.

Humans staring at plots and charts to derive very obvious patterns like why your API is 500ing is NGMI.

On one hand we have infra that scales automatically and self-heals. A lot of our customers simply don’t set up expensive o11y appliances. Prices will go down to approach the cost of data storage. On the other hand, we have the fact that people don’t want o11y, they want solutions.

They want pull requests with fixes, they want automatic rollbacks, they want automatic fail over of vendors (see: AI Gateway).

Coding will reach full autonomy, which I define as an extremely low rate of disengagement to human experts, in narrower domains first. Much like Waymo has crushed the robotaxi usecase, there’s similar alpha in the optimization of programming languages, frameworks and tasks

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AI makes the web shine brightest. The web browser is unique in that it can enable consumption and creation in the same medium. A fully dynamic app can be streamed from a GPU and built just in time for any user according to their wishes and needs.