Claude Code, set up to ship safely
Agentic coding changes the unit of work from lines of code to whole features. We set up Claude Code properly: modular architecture, automated tests, enforced security, a safe deploy pipeline and the AI development environment itself, so the change lasts. It works for engineering teams and for non-engineering teams who have built their own app with AI and need it to hold up in production. We build with Claude Code every day, so the setup comes from practice, not theory.
Agentic coding changed the unit of work. Most teams have not changed how they work.
The first wave of AI coding tools helped at the line level but did not change how teams ship. The next wave, Claude Code and agentic coding, changes the unit of work to features and tasks. Two things follow.
Engineering teams get the most from Claude Code only when their codebase is set up for it. And non-engineering teams are now building real, working apps with AI, then hitting a wall the moment those apps reach production, because there is no structure, no tests and no enforced security underneath. Both need the same thing: agentic coding, set up properly.
What Claude Code does for engineering and product
Claude Code in production
Agentic coding for feature development, refactoring, debugging, and Git workflows. Engineers describe what they need; Claude reads the codebase and ships it.
Code review and quality
Claude reviews PRs against your code standards, catches likely bugs, and suggests improvements before human review. Reviewers focus on architecture and intent.
Technical documentation that stays current
READMEs, API docs, architecture diagrams generated from the code itself. Updated automatically as the code changes.
System design and architecture review
Claude as a thinking partner for design decisions. Compare options, surface trade-offs, document the rationale.
On-call support and incident response
Claude triages alerts, suggests root causes from logs, drafts incident summaries, and writes the post-mortem.
What “set up properly” actually means
Buying licences is not a setup. Whether your engineers are adopting Claude Code or your team has already built an app with AI, the foundation is the same. This is what we put in place so every future AI-assisted change is faster, cheaper and safe.
Modular code
One monolith becomes self-contained modules. The AI reads a few hundred focused lines instead of tens of thousands, so output quality goes up and cost comes down.
Automated tests
Tests on the critical business flows, so a change cannot silently reach production unverified.
Staging + CI/CD
A staging environment and an automated pipeline: every change is checked and previewed before it ships, with a tested rollback.
Enforced security
Roles and validation enforced at the data layer, not just hidden in the UI. The security model matches how the business actually works.
Error monitoring
Unified error handling with alerts, so you see failures as they happen rather than when a user reports them.
AI dev setup
The configured AI development environment, project Skills and coding standards, handed over with training so your own team keeps building with AI safely.
Not an engineering team? That is exactly who this is for. If your people built the app with AI, we make it production-grade and give them the setup to keep going, without a full engineering hire.
From an AI-built app to a system the team can keep building
A UK fresh-produce business built a full operational app with Claude: procurement, stock control and traceability, the workflows their business runs on. The logic was sound and the team had built something real. The foundation underneath was the risk.
Our review found sensitive files (passport scans, compliance photographs, supplier documents) readable and deletable by any signed-in user, role permissions enforced only in the interface, a single codebase of around 58,000 lines with no modules, no tests and no monitoring, and a structure that actually worked against the AI they were building with: every change meant the tool loading the whole codebase.
We are rebuilding it onto a modular, tested and secure foundation, on the same platform, with the same screens and workflows, and zero-downtime data migration. The security exposure was closed on the live app in the first week. Just as important, the full AI development setup, the configured environment, the project Skills and the coding standards, is handed over with training, so their own team keeps building with AI, faster and safely, long after we step back.
The point is not that AI built something flawed. The point is the opposite: the team built something genuinely useful with AI, and the right foundation is what lets them keep doing it in production.
How we set this up for your team
Engineering Project setup
Architecture docs, coding standards, and key codebases loaded so Claude reasons with your system, not a generic one.
Connectors and integrations
GitHub or GitLab, Linear or Jira, Slack, and your monitoring stack. Claude Code deployed with scoped Git permissions.
Custom Skills and training
Agentic-coding workshops for your team. Skills for PR review, documentation sync, and incident response. The AI dev setup handed over.
What changes for the team
Without Claude Code
- Line-level autocomplete with Copilot or Cursor
- Code review queues back up for half a day or more
- Documentation written on Fridays, out of date by Monday
- On-call engineers dig through logs manually
- AI-built apps with no tests, no structure, growing risk
With Claude Code in production
- Feature-level work: describe intent, Claude ships a PR
- PRs pre-reviewed for standards and likely bugs
- Docs generated from code and kept in sync automatically
- Incident triage accelerated with log analysis in seconds
- AI-built apps on a modular, tested, secure foundation
Where Claude Enterprise is not the right tool for engineering
If the codebase is a single file or a weekend prototype with no real users, Claude Enterprise is overkill. If the team is not ready to review AI output, the value will not land. If your constraint is hiring (you need more senior engineers) rather than velocity (you need more output from the team you have), that is a different problem.
If your app was built with AI and has no standards or tests yet, that is not a disqualifier, it is the starting point: we build the foundation first.
Claude Enterprise for Engineering and Product: at a glance
- Deploying partner
- Softblues (softblues.io)
- Partner status
- Registered Anthropic Partner Network member
- Team
- 30+ AI specialists
- Cloud partner
- Google Cloud Partner
- Headquarters
- London, United Kingdom
- Programme phases
- Strategy and Roadmap, Deployment and Activation, Continuous Partnership
- Core use cases
- Claude Code, code review, technical documentation, system design, on-call support and incident response
- Typical deployment
- 4 to 10 weeks from kickoff to daily use
- Connectors
- GitHub or GitLab, Linear or Jira, Slack, monitoring (via MCP)
Common questions about Claude Code and agentic coding
Yes, with scoped permissions. Claude Code operates inside the Git boundaries you grant it, opens PRs for review, and never merges unilaterally. Every change goes through your standard review and CI.
Copilot and Cursor help at the line and file level. Claude Code operates at the feature and task level: it reads the whole repo, plans the change, writes the tests, and opens the PR. The unit of work is larger.
Good engineers adopt tools that make them faster without compromising quality. The deployment includes workshops on agentic patterns so the team sees the uplift first-hand, which usually flips scepticism quickly.
Anthropic does not train on enterprise customer data by default. Code stays in your Claude Enterprise workspace. Audit logs and data retention policies are available at the standard required by engineering IP protection.
Yes. This is one of the most common things we do. We review the AI-built system, close any security exposure first, then rebuild it onto a modular, tested, secure foundation, on the same platform, and hand over the AI development setup so your team keeps building. The app the team built keeps paying off instead of getting riskier with every change.
No. We set up agentic coding for non-engineering teams too. If your people built something with AI, we make it production-grade and give them the environment, Skills and standards to keep going, with training, without needing a full engineering hire.
Three ways to start
Book a code-audit call
A no-pitch conversation about your codebase, your team, and where Claude Code or a foundation rebuild would fit.
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A 10-question quiz that scores your company's readiness for Claude Enterprise across people, process, technology, and culture.
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A 16-slide reference covering platform choice, governance, costs, rollout timing, and the questions to ask any vendor.
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