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<div style="display: none; max-height: 0px; overflow: hidden;">Moonshot has launched Kimi K3, a 2.8-trillion-parameter multimodal model with a 1-million-token context window and optimizations for faster β β β β β β β β β β β β β β β β β β β β β β β β β β β β β β β β β β β β β β β β β β β β β β β β β β β β </div>
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<h1><strong>TLDR AI <span id="date">2026-07-17</span></strong></h1>
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<strong>Your AI is only as good as the prompt you feed it. (Sponsor)</strong>
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<p>Millions of developers use Flow daily.</p>
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<div style="text-align: center;"><span style="font-size: 36px;"><span style="font-size:36px;">π</span></span></div></div>
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Moonshot has launched Kimi K3, a 2.8-trillion-parameter multimodal model with a 1-million-token context window and optimizations for faster long-context decoding and agentic coding. The model is available through Kimi's products and API, with open weights scheduled for release on July 27.
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Most failure-handling logic is complex, fragile, and hard to test. <a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Ftemporal.io%2Fpages%2Fsaga-patterns-state-machines-whitepaper%3Futm_source=tldr%26utm_medium=sponsorship%26utm_campaign=tldr-ai-secondary-2026-07%26utm_content=whitepaper-saga-state-machines/2/0100019f703e7efa-4d6acfea-aa34-4428-b211-5738994b9637-000000/GbB78HdH_GSlE0pTYnuMixbiOYp81uSnEU8-7FQ5Jgs=452" rel="noopener noreferrer nofollow" target="_blank"><span>This Temporal white paper</span></a> shows you 2 distinct patterns to take component failure in stride without constraining application structure. Learn how to implement these patterns using the same open source tools used at OpenAI, Lovable, and Replit. <a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Ftemporal.io%2Fpages%2Fsaga-patterns-state-machines-whitepaper%3Futm_source=tldr%26utm_medium=sponsorship%26utm_campaign=tldr-ai-secondary-2026-07%26utm_content=whitepaper-saga-state-machines/3/0100019f703e7efa-4d6acfea-aa34-4428-b211-5738994b9637-000000/jq9I9Vjj2pGnrZx8b6K7Y_N0WbApYlXxsgYVB_jdqug=452" rel="noopener noreferrer nofollow" target="_blank"><span>Get your copy</span></a>
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<strong>Schema (2 minute read)</strong>
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<span style="font-family: "Helvetica Neue", Helvetica, Arial, Verdana, sans-serif;">
Schema is a harness that makes frontier models play like physicists. It can help frontier models achieve 99% on ARC-AGI-3 Public. ARCβAGIβ3 gives agents a game environment without an explanation of what it is seeing. Schema makes agents write each game's mechanism as an executable program, test it against reality, and plan inside it. It controls how observations are turned into a working model of a game, how predictions are tested against the interaction history, and how plans are executed and revised.
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<strong>NVIDIA Nemotron 3 Embed (9 minute read)</strong>
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NVIDIA released three open embedding models for RAG, agentic retrieval, code search, and memory, led by an 8B model that ranked first overall on RTEB.
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<strong>Copilot SDK (GitHub Repo)</strong>
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<span style="font-family: "Helvetica Neue", Helvetica, Arial, Verdana, sans-serif;">
Embeds GitHub Copilot agents into custom applications and developer tools.
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<div style="text-align: center;"><strong><h1>Miscellaneous</h1></strong></div>
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<strong>The Best Model Routing is Task Specific (6 minute read)</strong>
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Model routing is a hot topic because nobody wants to pay frontier prices for every token. The best routing is deeply task-specific. The more narrowly you focus on a single workflow, the more alpha there is to exploit in terms of both accuracy and cost. The problem is figuring out which model clears the bar for which task, subject to cost/latency constraints.
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<strong>The Self-Driving Company (10 minute read)</strong>
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Replit engineers have tripled code output without sacrificing quality, thanks to an innovative system of AI agents. These agents handle tasks like reviewing pull requests, investigating incidents, and analyzing data, enabling engineers to focus on strategic initiatives.
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<div style="text-align: center;"><span style="font-size: 36px;">β‘</span></div></div>
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<strong>Nvidia-backed Fireworks hits $17.5 billion valuation as companies pursue cheaper AI models (5 minute read)</strong>
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Nvidia-backed Fireworks secured a $17.5 billion valuation, driven by demand for cheaper AI models as companies explore open-source options.
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<strong>Connected Apps in Google AI Mode (3 minute read)</strong>
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Google added integrations with Instacart, Canva, and YouTube to AI Mode, allowing users to complete tasks across supported apps from its conversational search experience.
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<strong>Ramp targets AI's fastest-growing cost with expanded token spend tracking (4 minute read)</strong>
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Ramp has expanded its AI Token Spend Management product to give finance teams clear insights into AI spending across providers like OpenAI, Anthropic, and Google's Gemini.
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<strong>NotebookLM is now Gemini Notebook (2 minute read)</strong>
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<span style="font-family: "Helvetica Neue", Helvetica, Arial, Verdana, sans-serif;">
Google has rebranded NotebookLM as Gemini Notebook, expanding its integration across the Google ecosystem, including the Gemini app and Google Search.
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