diff --git a/documentation/blog/2026-02-07-context-engineering/blogbanner.png b/documentation/blog/2026-02-07-context-engineering/blogbanner.png new file mode 100644 index 000000000000..e39a03ba041e Binary files /dev/null and b/documentation/blog/2026-02-07-context-engineering/blogbanner.png differ diff --git a/documentation/blog/2026-02-07-context-engineering/index.md b/documentation/blog/2026-02-07-context-engineering/index.md new file mode 100644 index 000000000000..cd0381d3d8d4 --- /dev/null +++ b/documentation/blog/2026-02-07-context-engineering/index.md @@ -0,0 +1,158 @@ +--- +title: "One Shot Prompting is Dead" +description: "Practical steps and mental models for building context engineered workflows instead of clever prompts." +authors: + - ebony +--- + + + +I attended one shot prompting’s funeral. + +There were no tears. Just a room full of developers quietly pretending they weren’t taking shots the night before. Because if we’re being honest, everyone saw this coming and couldn’t be happier it was over. + +Saying “one shot prompting is dead” isn’t revolutionary. It’s just catching up to what builders have been experiencing for months. + + + +--- + +## The blog post that aged faster than oat milk + +Last year, I wrote a post about [how to prompt better](https://block.github.io/goose/blog/2025/03/19/better-ai-prompting). I shared tricks, phrasing tips, and even said to add a few “pleases” and “thank yous” and your AI agent would give you the world. At the time it felt cutting edge, because it was. There were livestreams and conference talks entirely about how to prompt better. + +Less than a year later, it feels… quaint. Not because prompting stopped mattering, but because prompting stopped being the main character. + +The conversation shifted from: + +> “How do I coach the model better?” + +to + +> “What environment am I dropping this model into?” + +That’s a completely different problem, and now it has a name. **[Context engineering](https://block.github.io/goose/docs/guides/context-engineering/)**. + + +--- + +## The abstraction that broke + +One shot prompting worked when agents were party tricks. You crafted a clever prompt, you got a clever answer, and by “clever answer” I mean a fully “working” app, so everyone clapped. But the moment we asked agents to plan, remember, call tools, and operate across multiple steps, the definition of “worked” fell apart. + +A single prompt stopped being a solution and became a bottleneck. What matters now isn’t the sentence you type. It’s the system that surrounds it. Prompts didn’t disappear, but they were demoted to one step inside a larger pipeline designed to hold state, plan ahead, and enforce guardrails. + +As someone put it in a thread I recently came across: + +> “The best model with bad context loses to an average model with great context.” + +That line explains the shift. Context is now the advantage. + +And this isn’t theoretical. You can see it in how serious agent systems are being built. Projects like [OpenClaw](https://openclaw.ai/) and [Ralph Wiggum loop](https://ghuntley.com/loop/) aren’t chasing clever phrasing. They’re designing environments where context persists, decisions accumulate, and agents can operate across time without resetting every session. + +The excitement around these systems isn’t just hype either. It’s relief. Builders have been hungry for real working examples that behave *predictably* over time. + +Which leads to the only question that matters .... + +--- + +## How do I actually do this? + +When I started building our skills marketplace, one shot prompting alone couldn't cut it. My normal workflow involved researching in one place and implementing in another, and every time I switched tools I had to re-explain the same decisions. Context wasn’t living inside the system. It was living in my head. The agent would forget, I would remember, and the entire session became an exercise in rehydration instead of progress. + +Here’s what that loop looked like in practice: + +{/* Video Player */} +