Effective context engineering for AI agents
anthropic.com
Effective context engineering for AI agents
1–10 of 36 posts
Re: Effective context engineering for AI agents
#2The article doesn't really give helpful advice here, but please don't vibe this.
Create evals from previous issues and current tests. Use DSPy on prompts. Create hypotheses for the value of different context packs, and run an eval matrix to see what actually works and what doesn't. Instrument your agents with Otel and stratify failure cases to understand where your agents are breaking.
Re: Effective context engineering for AI agents
#3I think any meaningful context engineering strategies will be trade secrets.
Re: Effective context engineering for AI agents
#4I think any meaningful context engineering strategies will be trade secrets.
Imagine where we would be if academia or open source had this train of tougth.
No algorithms, no Linux, no open protocols, maybe not even internet.
Re: Effective context engineering for AI agents
#5The article doesn't really give helpful advice here, but please don't vibe this. Create evals from previous issues and current tests. Use DSPy on prompts. Create hypotheses for the value of different context packs, and run an eval matrix to see what actually works and what doesn't. Instrument your agents with Otel and stratify failure cases to understand where your agents are breaking.
How hard is dspy to setup?
Isn't it a programming language type thing?
Can you even integrate that into an existing codebase easily?
Re: Effective context engineering for AI agents
#6I think any meaningful context engineering strategies will be trade secrets.
Maybe, but we'll be getting to a place where each LLM call gets cheaper, faster and has a larger context, it may not matter long term.
Re: Effective context engineering for AI agents
#7The article doesn't really give helpful advice here, but please don't vibe this. Create evals from previous issues and current tests. Use DSPy on prompts. Create hypotheses for the value of different context packs, and run an eval matrix to see what actually works and what doesn't. Instrument your agents with Otel and stratify failure cases to understand where your agents are breaking.
How hard is dspy to setup? Isn't it a programming language type thing? Can you even integrate that into an existing codebase easily?
It's pretty straightforward, different optimizers have different requirements. Some require example inputs/outputs, others will just optimize on whatever you've got. You can use codex/claude code to set it up in order to bootstrap quickly, they're decent at it.
Re: Effective context engineering for AI agents
#8Re: Effective context engineering for AI agents
#9Earlier quoted context omitted.
How hard is dspy to setup? Isn't it a programming language type thing? Can you even integrate that into an existing codebase easily?
It's pretty straightforward, different optimizers have different requirements. Some require example inputs/outputs, others will just optimize on whatever you've got. You can use codex/claude code to set it up in order to bootstrap quickly, they're decent at it.
Does dspy support structured outputs?
Re: Effective context engineering for AI agents
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