Philosophy

We had to go from 30 to 10. AI made sure we didn’t skip a beat.

At Arvore, external circumstances forced us to reduce our engineering team from 30 to 10. That kind of change can break a company.

It didn’t break us. We invested heavily in AI tooling, structured our workflows around it, and discovered something unexpected: a smaller team with the right setup doesn’t just survive — it ships faster. Features that used to take 3 to 6 months now go live in weeks.

This isn’t a story about replacing people with AI. It’s about what becomes possible when you give a talented team the right tools.

We’re hiring. But the role has changed.

We want more engineers. We’re actively growing the team. But the profile we look for today is different from what it was two years ago.

We call them product engineers.

A product engineer knows the product deeply — the business logic, the user flows, the edge cases. They also know the technology — the architecture, the security constraints, the performance implications.

What defines them is not how fast they type code. It’s how well they direct AI, review its output, and make the decisions that matter — security, architecture, product judgment.

AI writes most of the code. Product engineers make sure it’s correct, secure, and solves the right problem. That takes skill, experience, and deep context. It’s harder than writing code, not easier.

We want people who can flow with this

The tools change fast. Editors, models, frameworks — what’s best today might not be best tomorrow. We don’t optimize for a specific tool. We optimize for a way of working:

Structured over ad-hoc — Defined pipelines beat improvised prompting
Context over cleverness — The best prompt in the world fails without the right context
Review over speed — Shipping fast means nothing if you ship broken
Adaptable over specialized — The best engineers learn new tools quickly, not cling to old ones

We want engineers who can thrive in this environment regardless of whether the editor is Cursor, Claude Code, Windsurf, or something that doesn’t exist yet.

If that sounds like you, we wrote a role overview here: Product Engineer (Hiring) →

The investment math

AI tooling is extraordinarily cost-effective, but that’s not why we use it. We use it because it makes our team better.

One Claude Opus 4.6 subscription gives every engineer access to the most capable reasoning model available
One Cursor license per engineer pays for itself in the first week
Repo Hub is free, open source, and ties everything together

The compound effect is what matters. Every skill we write, every agent we refine, every MCP we connect — it benefits the entire team instantly. The setup gets better every week.

We’re not early adopters. We’re operators.

This isn’t a demo or a proof of concept. We run a real company on this stack, shipping real software to real users every week.

Our current setup:

9 repositories managed as a single AI-aware workspace
11 specialized agents collaborating in structured pipelines
19 MCP connections giving AI access to databases, monitoring, secrets, and testing tools
Claude Opus 4.6 as our primary model for complex reasoning and code generation

This is production infrastructure. And we’re open-sourcing it because we believe every team should have access to this approach.

What we believe

AI doesn’t replace engineers. It changes what engineering means. The best engineers will be the ones who know how to direct AI, not the ones who type the fastest.
Context is everything. An AI that can’t see your database schema, your API contracts, and your deploy patterns is flying blind. Repo Hub exists to solve this.
Structure beats improvisation. Ad-hoc prompting produces ad-hoc results. Structured agent pipelines with defined roles, skills, and review steps produce consistent, high-quality output.
The editor is the runtime. We don’t need another platform, another server, another dashboard. The AI editor is where the work happens. It should be where the workflow lives.
Open source wins. We’re open-sourcing Repo Hub because we believe this approach should be accessible to every team, not locked behind a SaaS paywall.

What’s next

We want to standardize the agent configurations, skills, and workflows that power our development — and make them tool-agnostic. Not tied to Cursor, not tied to Claude, not tied to any single vendor.

Repo Hub is the first step. The CLI, the YAML schema, the agent templates, the MCP connections — all of it is designed to be adopted, extended, and contributed to by any team.

Get Started →