Your product ends up with a backend that survives growth: services with clear boundaries, documented APIs and a data model built for the queries that actually run.

• REST and GraphQL APIs with versioned, documented contracts and contract tests.
• Services in Python (Django, FastAPI), Node (NestJS, Express), Deno or Ruby on Rails, depending on what your team already runs.
• PostgreSQL data model: schema, indexes, migrations and queries that do not degrade as the table grows.

When a product grows, the problem stops being a feature and becomes how the services talk to each other. That is where service boundaries, event delivery and flows that cannot be lost along the way come in.

• Microservice design: where to cut, who owns which data and what contract sits between them.
• Event-driven architecture on Kafka: topics, partitions, schemas and backward compatibility.
• Durable workflows with Temporal for multi-step processes that must survive a restart.

Infrastructure ends up described as code and deployment automated, so shipping to production is routine and anyone on the team can do it.

• Infrastructure as code with Terraform or Pulumi, reviewable in a pull request.
• CI/CD pipelines (GitHub Actions, Jenkins, Bitbucket) that build, test and deploy with no manual steps.
• Containers and orchestration on Kubernetes, with resource limits, health checks and autoscaling.

Models and agents go into the product you already have with the same discipline as any other service: a contract of your own, cost limits and a log of what they did.

• Model API integration (Claude, GPT, Gemini) behind a contract of your own, so you can swap provider without touching the product.
• MCP servers and clients to give a model controlled access to tools and data.
• Agents that run multi-step tasks, orchestrated with Temporal when they need to be reliable.