Decision guides
Which one should you build?
Each guide compares two options fairly. It shows the use cases where each one wins, the trade-offs, and a checklist to decide.
Agent design
- Agent framework vs Custom harnessA framework gets the first agent running. Your own harness is what keeps it running when the model changes.Read more →
- Model Context Protocol (MCP) vs Direct API callsDirect calls are the fastest route to one integration. A protocol pays off when many tools and many agents need the same connections.Read more →
- Single agent vs Multi-agent systemMost failures in a multi-agent system come from the handoffs between agents, not from any single one.Read more →
Build and buy
Models and data
- LLM as judge vs Human evaluationA model judge can score ten thousand answers overnight. Only people can tell you whether the scoring itself is right.Read more →
- Open-weight model vs Hosted API modelA hosted model is usually more capable today. Open weights win when where the data sits matters more than the last few points of quality.Read more →
- Retrieval-augmented generation (RAG) vs Fine-tuningFine-tuning on your policies makes a model sound sure about policies that have already changed.Read more →
Regulation
Roles and hiring
- In-house team vs PartnerA partner gets the first system live. An in-house team is the only way to run the next twenty without asking anyone.Read more →
- Forward-deployed engagement vs Staff augmentationExtra engineers add capacity. They do not add a finished system, unless someone is accountable for the outcome.Read more →
- Forward-deployed engineer vs AI consultantA consultant can tell you what to build. Only someone inside your systems finds out whether it works.Read more →
- Forward-deployed engineer vs Solutions engineerA demo proves a product can do a task on sample data. It does not prove your system will run next quarter.Read more →