grounding — Tying a model's answers to checkable sources — retrieved documents, live data, tool results — instead of letting it answer from memory alone.
Why it matters
Peter Steinberger's no-hype, practitioner's guide to actually working with coding agents — real workflows and honest tool comparisons. One of the more groundingTying a model's answers to checkable sources — retrieved documents, live data, tool results — instead of letting it answer from memory alone.Full definition → reads on agentic engineering, from someone shipping with it daily.
Key quotes
“Agentic engineering has become so good that it now writes pretty much 100% of my code.”
Peter Steinberger
“I run between 3-8 in parallel in a 3x3 terminal grid, most of them in the same folder , some experiments go in separate folders.”
Peter Steinberger
“I currently have 4 OpenAI subs and 1 Anthropic sub, so my overall costs are around 1k/month for basically unlimited tokens. If I’d use API calls, that’d cost my around 10x more.”
Peter Steinberger
“IMO most are something for the marketing department to make a checkbox and be proud. Almost all MCPs really should be clis.”
Peter Steinberger
“Don’t waste your time on stuff like RAG, subagents, Agents 2.0 or other things that are mostly just charade. Just talk to it. Play with it. Develop intuition. The more you work with agents, the better your results will be.”
