The LLM Tooling Stack I Actually Use in 2026 (After 18 Months of Testing)
18 months of building with LLMs. Here's what survived my actual workflow. The Stack Not the trendy stuff. The tools I reach for every day. Claude Pro — $20/mo Core LLM. I use the API for automation...
Source: DEV Community
18 months of building with LLMs. Here's what survived my actual workflow. The Stack Not the trendy stuff. The tools I reach for every day. Claude Pro — $20/mo Core LLM. I use the API for automation and claude.ai for exploration. The 200K context window is genuinely class-leading. Why it wins: Context. I can give it an entire codebase and say "what does this do?" and get a coherent answer. Cursor — $20/mo VS Code fork with AI baked in at the core. Not a plugin — an IDE designed around AI. Why it wins: Codebase awareness. It indexes your project and actually understands context across files. Pydantic — Free For structured output from LLMs. Define your schema once, get validated output. from pydantic import BaseModel class WeatherResponse(BaseModel): city: str temp_c: float condition: str result = llm.parse_pydantic(user_prompt, WeatherResponse) No more manual JSON parsing and validation. Helicone — Free tier LLM observability. See what's being sent to your models, track costs, spot patte
