Context Engineering for AI Agents: Lessons from Building Manus
This post shares the local optima Manus arrived at through our own "SGD". If you're building your own AI agent, we hope these principles help you converge faster.
Context Engineering for AI Agents: Lessons from Building Manus Manus is now part of Meta — bringing AI to businesses worldwide Product · Friday, July 18 Context Engineering for AI Agents: Lessons from Building Manus 2025/7/18 - - Yichao 'Peak' Ji At the very beginning of the Manus project, my team and I faced a key decision: should we train an end-to-end agentic model using open-source foundations, or build an agent on top of the in-context learning abilities of frontier models? Back in my first decade in NLP, we didn't have the luxury of that choice. In the distant days of BERT (yes, it's bee
saved by
related reading
- Effective context engineering for AI agents \ Anthropicanthropic.com
- Arjun Virkarjunvirk.com
- Don’t Build Multi-Agents | Cognitioncognition.ai
- LLM Powered Autonomous Agents | Lil'Loglilianweng.github.io
- Building Effective AI Agents \ Anthropicanthropic.com
- How Long Contexts Faildbreunig.com
- How we built Linear Agentlinear.app
- Continually improving our agent harness · Cursorcursor.com
- Supermemory — Memory and continual learning for agentssupermemory.ai
- Building Effective AI Agents \ Anthropicanthropic.com
- Building reliable AI agents · parth sareenparthsareen.com
- What Makes 5% of AI Agents Actually Work in Production?motivenotes.ai