Thursday, July 16, 2026 · San Francisco
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Moonshot Launches Kimi K3 With 2.8 Trillion Parameters and 1M Context

Moonshot Launches Kimi K3 With 2.8 Trillion Parameters and 1M Context

Moonshot has put Kimi K3 online with 2.8 trillion parameters, native vision and a one-million-token context window, but the model's most important test cannot begin yet. Its benchmark table puts K3 near proprietary rivals even though the comparisons used different agent harnesses, and one early tester reported reasoning runs longer than 1,000 seconds. With full weights promised for July 27, the launch turns on what outsiders can verify once the files arrive.

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Meta Admits Its 8,000-Layoff Reorg Hasn't Delivered, Even as Its Next Model 'Catches' GPT-5.5
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Meta Admits Its 8,000-Layoff Reorg Hasn't Delivered, Even as Its Next Model 'Catches' GPT-5.5

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Repo Radar: 5 GitHub Projects Worth Your Week
Tools & Workflows

Repo Radar: 5 GitHub Projects Worth Your Week

Repo Radar No. 13: graphify turns any folder of code, papers and screenshots into a queryable knowledge graph. Tencent's CubeSandbox boots a hardware-isolated agent sandbox in under 60ms. Together AI's hallmark stops coding agents shipping the same gradient hero. Microsoft's Flint compiles agent chart specs into Vega-Lite, ECharts or Chart.js. PentAGI runs autonomous security tests inside Docker. Five projects that narrow what an agent may see, run, render or spend.

11 min read ·
Repo Radar: 5 GitHub Projects Worth Your Week
Tools & Workflows

Repo Radar: 5 GitHub Projects Worth Your Week

This week's Repo Radar tracks five GitHub projects where AI agents move from chat into real production work: OpenMontage turns a coding assistant into a video studio, Google Labs' design.md gives agents a design-system spec, Strix runs autonomous penetration tests, Alibaba's page-agent drives live web interfaces in natural language, and MinerU converts messy PDFs into LLM-ready markdown. Difficulty scores, licenses, and push dates for each, plus why OpenMontage is Repo of the Week.

11 min read ·
Repo Radar: 5 GitHub Projects Worth Your Week
Tools & Workflows

Repo Radar: 5 GitHub Projects Worth Your Week

Repo Radar's eleventh issue tracks five GitHub projects builders attach to AI agents once a demo becomes a workload: Agent-Reach, a CLI giving agents live access to Twitter, Reddit, and YouTube; Flue, the Astro team's sandbox agent harness; cognee, a graph-based memory layer; hunk, a review-first diff viewer for agent-written code; and mistral.rs, a Rust engine for local inference. Each scored on stars, language, license, push date, and setup difficulty.

11 min read ·

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When Claude Fable 5 Is Worth Double, and When to Use Opus 4.8

Anthropic reports Claude Fable 5 falls back to Opus 4.8 on a fifth of Terminal-Bench trials, and after the July relaunch one tester measured three of four debugging tasks rerouted. The launch drew a researcher revolt over hidden limits; Andon Labs found an alignment slip. Double the price.

Every Tuesday Morning

Give Your AI a Memory Layer That Survives Sessions

Coding agents, support bots, and assistants all restart cold. A bigger context window does not fix it; a memory layer does. A build-along with Mem0 and Qdrant, the contradiction test most demos skip, and the real token math, costs, and controls a production memory store actually needs.

Thinking Machines’ Inkling Takes U.S. Open-Model Lead With 41 Score
Analysis 17 min read

Thinking Machines’ Inkling Takes U.S. Open-Model Lead With 41 Score

Thinking Machines’ Inkling leads U.S. open-weight releases with a 41 index score. Independent tests also found high pricing and a 63% hallucination rate, while the full checkpoint needs two terabytes of GPU memory. The open weights leave companies with a harder deployment decision.

Thinking Machines Lab’s first production model has taken the U.S. open-weight lead with a score of 41 on Artificial Analysis’s Intelligence Index. Inkling uses fewer output tokens than several Chinese rivals, yet testing found high prices and a 63% hallucination rate on one knowledge benchmark. Its weights are free, but the full checkpoint needs at least two terabytes of GPU memory. The test begins after the download: which companies can afford to turn open access into a working system?

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