Lakebase Search GA; agent skills for Storage, Functions,…

Jun 26, 2026– Agent skills for backend services, Lakebase Search GA, Postgres version updates, and more

Agent skills for Neon Storage, Functions, and AI Gateway

Neon Agent Skills are instruction files that teach AI coding assistants how to work with Neon. The collection now includes skills for Neon Functions, Object Storage, and AI Gateway, the backend services currently in private preview.

If you haven't requested preview access yet, sign up below and we'll send you the private preview guide to get started.

Get early access to the Neon backend platform

We're expanding Neon into a complete backend platform. Drop your email and we'll reach out soon for early access.

To install all Neon agent skills:

npx skills add neondatabase/agent-skills

For the complete list of skills and other install options, see the Agent Skills documentation.

Lakebase Search is now available to all users

Lakebase Search is now available to all Neon users on Postgres 16+. Two extensions, lakebase_vector and lakebase_text, bring vector, keyword, and hybrid search into Postgres, so you can run semantic RAG, exact-term lookups, and combined rankings without a separate search stack.

First, enable the shared preload libraries and restart your compute. Then install the extensions and query with the same operators you already know from pgvector and full-text search:

CREATE EXTENSION IF NOT EXISTS lakebase_vector CASCADE;
CREATE EXTENSION IF NOT EXISTS lakebase_text CASCADE;

-- Semantic: nearest neighbors by embedding
SELECT title FROM documents ORDER BY embedding <=> $query_vector LIMIT 5;

-- Keyword: BM25 relevance with top-K pushdown
SELECT title FROM documents
ORDER BY body_tsv <@> to_bm25query(to_tsvector('english', 'vector search'), 'documents_bm25')
LIMIT 5;

For production search, combine both with Reciprocal Rank Fusion (RRF): merge top vector and BM25 candidates into one score. The get started guide includes a full hybrid example in TypeScript.

Why Lakebase Search on Neon:

lakebase_ann: drop-in pgvector compatibility; scales to 1B+ vectors; index builds 50-100× faster than HNSW
lakebase_bm25: standard tsvector types; BM25 ranking GIN can't do natively
Scale-to-zero: indexes live in storage, so they're ready immediately after a cold start; branches copy indexes without rebuilds

See the Lakebase Search overview to get started.

Postgres version updates

We updated supported Postgres versions to 14.23, 15.18, 16.14, 17.10, and 18.4, respectively.

When a new minor version is available on Neon, it is applied the next time your compute restarts. For more about how we handle Postgres version upgrades, refer to our Postgres version support policy.

Ephemeral database branches for Vercel Eve agent sessions

In June, Vercel introduced Eve, an open-source, filesystem-first framework for durable agents. Sessions checkpoint as they run, can last for days, and pause for human approval before resuming. Eve includes a sandbox, evals, and built-in channels.

We published a guide that pairs Eve with Neon branching. The integration is a small hook in agent/hooks/provision-branch.ts: create a branch when a session starts, delete it when the session ends. Agent tools read the branch connection URI and work against an isolated copy of your production schema.

export default defineHook({
  events: {
    async "session.started"(_event, ctx) {
      const branch = await createBranch(`eve-${ctx.session.id.slice(0, 12)}`);
      dbBranch.update(() => ({ connectionUri: branch.connectionUri }));
    },
  },
});

Read the guide: Running Vercel Eve agents and evals on disposable Neon branches

Lakebase Search GA; agent skills for Storage, Functions, AI Gateway