


AI in Action - Session #13: How AI Agents Build Our Microservices Autonomously
If you're a backend dev, you can't afford to miss this
Most AI content is hype. This is real, production-grade AI leverage in a global product.
Traditionally, building a microservice meant drafting specs, syncing with architects, setting up boilerplate, writing tests, managing infra, and waiting on reviews—often taking weeks for a single service.
We’ve replaced that entire pipeline with an AI agent system. It now handles ideation, design, TDD, implementation, and deployment—autonomously.
We’re not promising a magic button. We’re showing you a system of AI agents that’s already working.
What you'll take away
🛠️ AI-Powered Dev Loop
Agents follow a structured pipeline:Prompted Ideation → System Design → Barebone Scaffolding → TDD → Iterative Codegen → Infra Hooks
⚙️ Live Production Use Cases:
Airspace Threat Processor — reduced latency by 90%, improved throughput 10x
Notification Service — real-time bridge across MQTT & Kafka
DAA Processor — ingesting & resolving sensor streams
🧱 Architecture Patterns We Now Use by Default
Minimal core + AI-guided extension
Template-based doc generation at every step
Full CI/CD-ready outputs
📊 We Show, Not Tell
Agent-generated architecture diagrams & dep graphs
Live dashboards hitting 1000+ msg/sec
TDD coverage reports, linting, benchmarks—generated & enforced by AI
Before/After: code diffs, perf benchmarks, latency graphs
AI is already eating parts of your job—and you can either wait to be replaced, or build the system that does the replacing.
AI-native builders and explorers, let's spark high-signal conversations!
Bring your team for maximum impact.
🌐 Join our WhatsApp community for latest AI news, tools, and mental models: https://chat.whatsapp.com/CSg6OChjPmCHt2lASGJKgA
