Small models got good enough, and devices got powerful enough, that running AI on the user's own hardware — phone, laptop, browser — is now a real option. A trend post on what local-first AI buys you, what it costs, and the hybrid reality where the honest answer is 'some of both'.
Committing your app to a single LLM provider is a risk: a price change, an outage, or a better model elsewhere leaves you stuck. Treating providers as interchangeable behind a routing layer buys resilience and flexibility — but it has real costs. A deep-dive on multi-provider routing, where it pays off, and where it's premature.
Rails 8 is coming with a quietly radical idea: you might not need Redis anymore. Solid Queue and Solid Cache move background jobs and caching into your database, collapsing the standard Rails production stack. A look at what the Solid libraries do, why 'just use Postgres' keeps winning, and when the old answer still applies.
Once your semantic search outgrows a toy dataset, the question arrives: stay with pgvector in Postgres, or move to a dedicated vector database like Pinecone, Qdrant, or Weaviate? A deep-dive on what actually changes at scale, what you give up by leaving Postgres, and how to decide without over-engineering.
Open-weight models like Llama 2 and Mistral mean you can now run a capable LLM on your own infrastructure instead of calling someone's API. A look at why you'd want to — privacy, cost, control — what it actually costs you in ops, and the honest question of whether you should.