Skip to content
agentusehub
Sign in+ Submit
Software & DevOpsAny

Build SQLite with a swarm of parallel coding agents

The author recounts using parallel coding agents to build a SQLite implementation and shares experience from it.

Read the experience
Time saved
Not reported
Setup time
Not reported
Running cost
Not reported
Cost range
Not reported

Use case overview

The author recounts using parallel coding agents to build a SQLite implementation and shares experience from it.

Read the original report ↗

Reported experience

  1. What they did

    One Claude run bootstrapped docs, a crate skeleton and a test harness. Then six workers (two each of Claude, Codex and Gemini) looped in separate workspaces. Each pulled main, claimed a task through a lock file, implemented it and tested against sqlite3 as an oracle, updated shared notes, and pushed. A separate Gemini coalescer was meant to remove duplication.

  2. How it went

    About 19k lines of Rust in 154 commits, with 282 AI-written unit tests passing. It passed only 64 SQLLogicTest queries, since subqueries and CASE are unsupported. It has no concurrency, and the code has some slop.

  3. Worth knowing

    54.5% of commits were lock and claim coordination. The coalescer ran only once, at the end, and Codex used 100% of a Pro weekly quota.

Example prompts

Try with Claude Code
I want to build a small [project, e.g. SQLite-style database engine] in [language] using several parallel agents. First write a spec that splits the work into independent modules ([e.g. parser, storage, query executor]), then run one sub-agent per module in separate worktrees with tests for each. Stop when the modules are merged and a test suite of [number] basic queries passes, and show me what failed along the way.

Related use cases

Software & DevOps

Port a Chrome extension to Safari

The author had ChatGPT take the Session Buddy extension source from Chrome, port it to Safari and install it, taking about 20 minutes.

ChatGPT