Akshay (@akshay_pachaar)

Claude Code에서 백엔드 컨텍스트 엔지니어링 레이어로 InsForge Skills와 CLI를 적용해 토큰 사용량을 10.4M에서 3.7M으로 줄이고 오류를 10개에서 0개로 낮췄다고 소개한다. 오픈소스이며 로컬에서도 동작하는 방식으로 비용 절감과 안정성 개선 효과가 크다.

https://x.com/akshay_pachaar/status/2051589749689962949

#claude #contextengineering #opensource #developertools #llm

Akshay 🚀 (@akshay_pachaar) on X

Claude Code used 3x fewer tokens with one change: - Before: 10.4M tokens · 10 errors · $9.21 - After: 3.7M tokens · 0 errors · $2.81 I used Insforge Skills + CLI as the backend context engineering layer for Claude Code (open-source and local). Repo: https://t.co/01v2PYDPpY

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AI Engineer (@aiDotEngineer)

컨텍스트는 단순 입력이 아니라 개선 루프를 만드는 ‘flywheel’이라는 주장입니다. 더 나은 컨텍스트가 더 나은 에이전트 출력을 만들고, 그 결과가 더 좋은 관측과 재생성된 컨텍스트로 이어져 팀의 속도와 품질, 재사용성을 높인다는 메시지입니다.

https://x.com/aiDotEngineer/status/2051065977123881204

#agents #contextengineering #llmops #aicoding #workflow

AI Engineer (@aiDotEngineer) on X

Patrick also makes the bigger point: context is not just input, it is a flywheel. Better context -> better agent output -> better observations -> better regenerated context. Teams that learn to engineer that loop will ship faster, review less garbage, and build a real moat

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AI Engineer (@aiDotEngineer)

AI 코딩에서 프롬프트·규칙·메모리만큼이나 ‘컨텍스트’를 핵심 엔지니어링 계층으로 다뤄야 한다는 키노트 내용입니다. 컨텍스트를 코드처럼 생성·평가·배포·관찰하는 생명주기로 관리하고, 일회성 프롬프트 대신 재사용 가능한 컨텍스트 컴포넌트로 전환하자는 제안이 핵심입니다.

https://x.com/aiDotEngineer/status/2051065645610017222

#aicoding #contextengineering #agents #promptengineering #llm

AI Engineer (@aiDotEngineer) on X

Context may be the most under-engineered layer in AI coding today. In this keynote, @patrickdebois, argues that if agents are driven by prompts, rules, and memory, then context deserves the same rigor we already give code. https://t.co/YOOgssva84

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AI Engineer (@aiDotEngineer)

AI 코딩에서 유용한 방법론으로 컨텍스트를 ‘비정형 프롬프트’가 아닌 엔지니어링 자산으로 취급하고, Generate-Evaluate-Distribute-Observe라는 운영 사이클을 만들자는 제안입니다. 일회성 프롬프트를 재사용 가능한 컨텍스트 컴포넌트로 바꾸고, 생성 코드의 품질을 체계적으로 테스트하자는 내용입니다.

https://x.com/aiDotEngineer/status/2051065840364126678

#aicode #contextengineering #llmops #agents #softwareengineering

AI Engineer (@aiDotEngineer) on X

Some of the most useful ideas from this talk: - Treat context as an engineering artifact, not ad hoc prompt text - Build a lifecycle around it: Generate, Evaluate, Distribute, Observe - Move from one off prompting to reusable context components - Test whether generated code

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Effective Context Engineering for AI Agents: A Developer's Guide

Learn how context engineering improves AI agents by delivering the right information at the right time for better, more reliable outputs.

MachineLearningMastery.com

AI agents do not fail only because the model is weak. A lot of the time they are drawing from a blank page.

I wrote about the back-to-back drawing experiment, grounding, the curse of knowledge, and why specifications are context transfer, not paperwork.

https://www.the-main-thread.com/p/context-transfer-ai-agents

#AIAgents #ContextEngineering #SoftwareEngineering

"I think much of the surviving employment will sit in strong-bundle, AI-augmented work and in the political-organizational core of firms. The future includes more therapists, tailors, personal trainers, and craft brewers, but also more managers whose value lies in handling ambiguity, integrating context, reconciling conflicting interests, and bearing the consequences of decisions."

#LLM #vibecoding #contextengineering #AI #jobs

https://www.siliconcontinent.com/p/why-desk-jobs-survive-and-amodei

The task is not the job

A supply-side answer to Amodei and Imas

Silicon Continent

As model capabilities expand, building support harnesses around models loses value. Harnesses may still have value right now, but their useful lifespan keeps getting shorter.

"The job isn't to stop building harnesses. It's to build them cheap enough to throw away."

#softwaredevelopment #LLM #vibecoding #contextengineering #programming

https://tanay.co.in/blog/todays-harness-is-tomorrows-prompt

Today's harness is Tomorrow's Prompt

In 2023, I spent two weeks wiring up a RAG pipeline so a sales team could ask questions about a folder of PDFs. Chunking, embeddings, a vector store, a reranker…

lucas (@lucas_flatwhite)

Anthropic의 컨텍스트 엔지니어링 가이드가 공유됐다. 프롬프트 엔지니어링에서 컨텍스트 엔지니어링으로의 전환을 강조하며, 모델의 원하는 동작을 가장 잘 이끌어내는 컨텍스트 구성과 2026년에도 유효한 기본 레시피를 다룬다.

https://x.com/lucas_flatwhite/status/2048777532913422450

#anthropic #contextengineering #promptengineering #llm #ai

lucas (@lucas_flatwhite) on X

📑 Anthropic 컨텍스트 엔지니어링 가이드 > 2026년에도 유효한 것들.. 프롬프트 엔지니어링에서 컨텍스트 엔지니어링으로.. 질문은 이거 단 하나예요. "어떤 컨텍스트 구성이 모델의 원하는 동작을 가장 잘 이끌어낼까요?" 기본 레시피는 여전히 유효해요. 여기에 2026년에 추가된 레이어들을

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Please do not implicitly trust anything generated by an LLM. Confident framing often appears indistinguishable from verified claim.

LLMs are game changers for learning, researching, and experimenting. They will boost your productivity. But approach your work in small iterations, and rely on primary (or well-regarded secondary) sources.

In the world of software, instrumentation is a primary source. Observability can help shed light on reality.

#AI #Observability #ContextEngineering