Source is at https://github.com/afiodorov/hn-search
When a project has little to no traffic, the on-demand pricing of serverless is unbeatable. A static site on S3 or a backend on Lambda with DynamoDB will cost nothing under the AWS free tier. A dedicated server, even a cheap one, is an immediate and fixed $8-10/month liability.
The cost to run a monolith on a VPS only becomes competitive once you have enough users to burn through the very generous free tiers, which for many side projects is a long way off. The primary driver here is minimizing cost and operational overhead from day one.
Location: Las Palmas, Spain
Remote: Yes
Willing to relocate: No
Technologies: Go, Python, SQL, Kubernetes, Docker, AWS (S3, EMR, RDS, Aurora, Athena), Apache Spark, Apache Airflow, TypeScript, React, gRPC, REST APIs, PostgreSQL, Google BigQuery, LangChain, LangGraph, RAG, faster-whisper
Résumé/CV: https://cv.fiodorov.es
Email: hn@fiodorov.esI treat it more like a homework exercise for a Coursera course but I like the result.
This is exactly right. Our role is shifting from writing implementation details to defining and verifying behavior.
I recently needed to add recursive uploads to a complex S3-to-SFTP Python operator that had a dozen path manipulation flags. My process was:
* Extract the existing behavior into a clear spec (i.e., get the unit tests passing).
* Expand that spec to cover the new recursive functionality.
* Hand the problem and the tests to a coding agent.
I quickly realized I didn't need to understand the old code at all. My entire focus was on whether the new code was faithful to the spec. This is the future: our value will be in demonstrating correctness through verification, while the code itself becomes an implementation detail handled by an agent.
It’s true to say that time writing code is usually a minority of a developer’s work time, and so an AI that makes coding 20% faster may only translate to a modest dev productivity boost. But 5% time spent coding is a sign of serious organizational disfunction.
sign of serious organizational disfunction.
You're not wrong, but it's a "dysfunction" that many successful tech companies have learned to leverage.The reality is, most engineers spend far less than half their time writing new code. This is where the 80/20 principle comes into play. It's common for 80% of a company's revenue to come from 20% of its features. That core, revenue-generating code is often mature and requires more maintenance than new code. Its stability allows the company to afford what you call "dysfunction": having a large portion of engineers work on speculative features and "big bets" that might never see the light of day.
So, while it looks like a bug from a pure "coding hours" perspective, for many businesses, it's a strategic feature!
I tried "Who's Gary Marcus" - HN / your thing was considerably more negative about him than Google.