r/agentdevelopmentkit

Hey folks 👋

We just open sourced TrueForge, our vendor-neutral agent harness for building general-purpose agents.

It handles the runtime pieces that get painful quickly : context management, tool/MCP execution, subagents, sandboxing, approvals, persistent state, and more.

We also benchmarked the harness itself. With the same Opus 4.8 model, TrueForge delivered a similar solve rate at ~30% lower cost than Claude Managed Agents. Switching to an open model pushed that to ~75% lower cost on the same benchmark.

Would love feedback from people building agents.

⭐ Star the repo: https://github.com/truefoundry/trueforge

📖 Read the launch article: https://x.com/truefoundry/status/2090081376330715176

I recently worked on Yaara, an AI agent for an EV charging platform in Sri Lanka.

We built it with Google ADK, Gemini Models, FastAPI, WhatsApp Cloud API, and Vertex AI RAG.

What became interesting wasn't the chatbot part. It was everything around the model.

We ended up with:

• A coordinator and specialist agent architecture
• RAG over company and EV knowledge
• Deterministic tools for calculations and backend actions
• Per user conversation state
• Human handoff through Chatwoot
• WhatsApp specific response formatting
• Tool trajectory evaluations
• GEPA based prompt optimization
• Deduplication, monitoring, and failure handling

One principle became pretty clear while building it:

The model should handle language and decisions. Normal software should handle exact work.

I wrote up the architecture and some of the things we learned while taking it from an agent idea toward a production system.

https://chamidilshan.medium.com/building-yaara-a-production-ai-agent-for-ev-charging-on-whatsapp-with-google-agent-development-kit-0c58caada28e

Would also be interested to hear how others using ADK are structuring coordinator/specialist agents as the number of tools grows.