By Team Squad on
Hello World from Squad
Why we built Squad, what managing AI agents looks like in practice, and what to expect from our engineering notes on reliable multi-agent execution.
Welcome to the Squad blog.
We are building the platform for managing AI agents: one place to direct multiple coding agents, preserve shared context, and keep full visibility into every decision. Most teams have already adopted AI coding tools, but adoption alone does not create a durable operating model. When each agent runs in a separate window, context fractures, handoffs break, and velocity stalls. Execution gets faster at the micro level while coordination gets slower at the system level.
Why this blog exists
We will use this space to share:
- product updates and release notes
- implementation details from real multi-agent workflows
- lessons learned from building a desktop-first orchestration platform
- practical playbooks for teams moving from solo prompts to coordinated squads
Our thesis is straightforward: software execution is becoming increasingly automated. The durable advantage is no longer manual keystroke output. The advantage is defining outcomes clearly, setting quality constraints, and managing agent execution with trust. Teams that do this well will ship faster, debug less, and make better product decisions because they can see exactly what their agents changed and why.
What shipping looks like
Our default loop is simple:
- define behavioral contracts and constraints
- route work to specialized agents in parallel
- validate changes with receipts, tests, and review
- promote verified changes with clear ownership and traceability
# Inside Squad, a single task fan-outs to multiple agents
squad run "implement auth + add tests + update docs"The goal is not to replace engineers. The goal is to let engineers operate as directors of reliable, auditable AI squads. We believe the engineer role is shifting toward outcome ownership: defining what good looks like, setting boundaries, and coordinating parallel execution that remains reviewable under pressure.
In upcoming posts, we will publish what worked, what failed, and what we changed. That includes interface decisions, workflow architecture, security tradeoffs, and the operating patterns we see across real teams. If your team is already using multiple AI tools and feeling coordination drag, this is the playbook we are writing in public.
See you in the next update.