Context Engineering at the Frontier | Thrive Capital
[2026 - DAY 1 - AGENT INFRASTRUCTURE] As models become more capable and reliable, it’s more important than ever to design tools and context thoughtfully. When models had short context windows and low agency, basic document retrieval into the model’s context window made a dramatic difference; but as frontier models boast millions of tokens of context and run for minutes and hours through tool calls and cycles of compaction, there is an ever growing list of concerns all vying for our models’ scarce attention. Extending context windows is an expensive and incomplete workaround. In this talk, we will share some of the principles and techniques we found useful in navigating these problems ourselves as we worked on the goal of improving our assistant, Puck, from a simple retrieval-based chatbot to a deeply knowledgeable general assistant. In particular, we will touch on two prevailing challenges. First, we’ll share how we’ve sought to raise the signal-to-noise ratio in Puck’s context by thinking of context engineering itself as a search problem, involving every step of the pipeline from indexing to subagents. Second, we’ll share how Puck approaches blending faithful, up-to-date structured data queries with the richness, breadth, incompleteness, and frequent conflicts latent in unstructured data in production. We’ll walk through a few concrete tactics in detail within both of these pillars, demonstrating that creative and useful approaches often come when we stop thinking of databases, search indexes, tools, and subagents as separate components, but as different solutions to the same underlying, age-old problem: searching for signal in a confusing and noisy world. SPEAKER: Linus Lee - Head of AI, Thrive Capital 👉 Sign up for our "No BS" Newsletter to get the latest technical data & AI content: https://aicouncil.com/newsletter ABOUT AI COUNCIL: AI Council brings together the brightest minds in data to share industry knowledge, technical architectures and best practices in building cutting edge data & AI systems and tools. FIND US: Website: https://aicouncil.com/ LinkedIn: https://www.linkedin.com/company/aicouncilconf/ X: https://x.com/aicouncilconf
Read Video · 文字稿與深度分析
一鍵獲取文字稿與 AI 深度分析 — 免費體驗
免費註冊 · 無需信用卡 · 註冊即獲 150 積分,足夠解鎖本集
- 📄 完整文字稿含時間戳
- ✨ AI 摘要、關鍵詞與心智圖
- 💡 核心要點與精彩引言
Podcast 與影片,已可閱讀
音訊 Podcast

Grit: The power of passion and perseverance | Angela Lee Duckworth
TED Talks Daily
2026年9月6日10:23EN
PA Replay: GOING ALL IN....What You Need To Know
The Pure Athlete Podcast
2026年7月14日52:14EN
Diogo Almeida - Deep Learning: Modular in Theory, Inflexible in Practice - TWiML Talk #8
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
2016年10月23日46:11EN
EP678 | 🎮
Gooaye 股癌
2026年7月11日52:46ZH-Hant
Радио-Т 1026
Радио-Т
2026年8月15日RU
#51 Jesus - Dürer - Superstar
Wer wir sind und warum das nicht klappte ...
2026年4月1日56:35DE
影片

DHH: Future of Programming, AI, Agentic Engineering, Vibe Coding & Linux | Lex Fridman Podcast #501
Lex Fridman
2026年8月26日5:15:51EN
Navigating a world in transition: Dario Amodei in conversation with Zanny Minton Beddoes
Economist Enterprise – Events
2025年1月27日45:03EN
The $15B Physical AI Company: Simulation, Autonomy OS, Neural Sim, & 1K Engineers—Applied Intuition
Latent Space
2026年4月27日1:14:07EN
2026/08/24(一) 輝達伺服器傳漲價15%:AI成本暴增,成本誰吸收?
財女珍妮
2026年8月24日30:06ZH-Hant
#27 Die Nibelungen - Wer war Siegfried?
99 mal Geschichte
2025年10月8日1:01:13DE