Agentic AI Adoption
Get your team onto Cursor, Claude Code, and Linear with Cloud Agents, the same multi-agent workflows we run in production every day. We bring the configurations, the patterns, and a working setup on day one.
AGENT STATUS
a7f29c
● running cursor·claude code·linear
~/select-interactive · agent-loop● LIVE
$claude code → branch "feature/checkout"
✓ patch applied · 14 files · 412 lines
✓ PR opened · awaiting human review
Capacity Gain
- Capacity: 3× ↑ per engineer
- Ticket-to-Merge: 4× faster
What Gets Installed
A working agentic stack from session one
01 Cursor
Editor + agent integrations
02 Claude Code
Terminal-native agent loops
03 Linear
Tickets, sprints, Cloud Agents
04 GitHub
PR reviews and CI hooks
Capabilities
1. Multi-Agent Workflows
Parallel agent sessions for implementation, testing, and review. We configure the orchestration patterns that let one engineer drive several agents at once without losing track of what each is doing.
2. Cursor Configuration
Project-level rules, indexing, prompts, and shortcuts dialed in for your codebase. We share the .cursorrules patterns we have refined over a year of real production use.
3. Claude Code Setup
Terminal-native agent loops integrated with your shell, your IDE, and your repository. Includes hooks, settings, and the agent definitions we use in our own daily work.
4. Linear + Cloud Agents
Tickets that turn directly into pull requests. We set up the Linear-to-agent pipeline so a properly scoped ticket becomes a draft PR ready for human review.
5. AI-Assisted Code Review
Review checklists, automated review passes, and the human-in-the-loop patterns that catch what raw AI output misses. No AI-written code merges without a senior engineer signing off.
6. Custom Agent Loops
For specialized tasks (data migrations, large refactors, test generation), we design and tune custom agent workflows that fit the work your team actually does.
How It Works
The agentic loop, end to end
A Linear ticket gets assigned to an agent. The agent drafts the implementation, runs the tests, and opens a pull request. A human reviews it, requests changes (which the agent applies), and merges. The same loop runs for tests, for migrations, and for refactors: different agents, same pattern.
The Automated Pipeline
- Issue Created: Linear
- Assigned to: Cursor Linear
- Branch & Code: Cursor + GitHub
- PR Opened: GitHub
- Team Notified: Slack
- Tested & Deployed: GitHub Actions
- Linear Status: Open → In Progress → In Review → Done
Tools We Configure
- Biome / Ultracite
- Claude Code
- Cloud Agents
- Cursor
- GitHub
- Linear
- TypeScript
- Vitest
How We Work
From Assessment to Autonomous Loops
A typical adoption engagement runs two to four weeks. We start by understanding your current workflow, then layer in agentic patterns one at a time so the team can absorb each change before the next one lands.
01 Stack & Workflow Audit
We review your current development workflow: how tickets become code, where reviews happen, what slows you down. We identify the highest-leverage points where agents can help first.
02 Tool Installation & Configuration
We install Cursor, Claude Code, and Linear, configure them for your codebase, and import the rule sets and patterns from our own production setup.
03 First Agent Loop
We pick a real ticket and walk through the full loop: ticket → agent → PR → human review → merge. The team watches it work end to end before driving it themselves.
04 Team Onboarding
Each engineer drives an agent loop on their own work, with us watching and offering live guidance. We answer the practical questions that only come up once you are in the seat.
05 Custom Workflows
For tasks specific to your codebase (data migrations, framework upgrades, large-scale refactors), we design custom multi-agent workflows that match the work.
06 Handoff & Documentation
You walk away with a documented setup, a runbook for adding new patterns, and a configured stack the team owns and operates without us.
In Practice
Agentic adoption in our own work
Agentic AI Adoption
Select Interactive: Internal
We rebuilt our own development workflow around the same agentic patterns we now consult on. Every feature on this site, every test, every refactor moves through the loop we install for clients.
Delivery Capacity
- Parallel agent sessions across implementation, testing, and review
- Roughly half the median time from ticket to merge on scoped feature work
- AI-assisted planning that surfaces edge cases earlier
- Automated test scaffolding on every feature with human sign-off
- Architecture review passes built into the standard workflow
Client Voices
Trusted by teams that ship.
We’ve partnered with Select Interactive for years, and they’ve consistently proven to be a forward-thinking, technology-driven partner. Their team is always building and refining solutions that elevate performance, from website development to strengthening SEO infrastructure. Just as importantly, they continuously bring new ideas to the table that help us improve our services and deliver stronger results for our clients. They truly are building a better web.
Alex Klinedinst President + Owner, Bluebird Creative Co.
FAQ
Do you require a specific IDE or editor?
Cursor is our recommended primary editor because of its agent integrations, but the patterns translate to other IDEs. Claude Code runs in any terminal and works alongside whatever editor your team prefers.
What happens to our existing CI/CD pipeline?
We work with what you have. The agentic loop layers on top of your existing GitHub Actions, GitLab CI, or whatever pipeline you run today. We add hooks where they help and leave the rest alone.
How do you handle code review when agents are writing PRs?
The same way any sound engineering team handles junior contributions: a senior engineer reviews every PR before it merges, and AI-assisted review tools provide a first pass. AI generates drafts; humans make the call.
How long does adoption take to feel natural?
Most engineers are productive on day one, and the patterns feel native within two to three weeks of daily use. The compounding gains (running multiple agents in parallel, designing custom loops) typically take six to eight weeks to settle in.
What if Anthropic, Cursor, or Linear changes pricing or APIs?
The agentic patterns are tool-independent. The specific tools may shift over time, but the workflow design (ticket-to-PR loops, parallel agent sessions, human-in-the-loop review) stays valid as the ecosystem evolves. Our retainer clients get continuous guidance as the landscape changes.
Go Deeper
From Ticket to Deployed: Our Agentic AI Development Workflow
A full technical write-up of the agentic workflow: the four tools, the pipeline, the quality safeguards, and the honest tradeoffs. This is the long-form version of the practice on this page.