Every week, I organize 400 to 700 links into roughly 60 categories as part of my ongoing effort to learn about AI. This is my personal notebook, which I enjoy sharing with friends… a hobby and a labor of love, rather than a commercial publication or product.
If you arrived here through a search or shared link, this page collects the links I found for AI Inn of Court for the week ending August 28, 2026.
As part of my learning process, I like to automate the category covers. It gives me a chance to learn Python and APIs.
This week’s cover prompt was written using Claude Opus 4.7, and the image was generated using Nano Banana 2.1.
Category Cover Image Prompt: A 16:9 mid-1980s murder-mystery comedy movie poster of a wide three-story black-and-white engraved Victorian mansion on pure black, with warm amber windows showing campy costumed barristers in horsehair wigs and black robes brandishing gavels and rolled subpoenas, other windows crowded with teetering scales of justice, stacks of lawsuits tied in red ribbon, and one window with a single powdered wig tumbling mid-air; the center double door stands open with a slim upright silver-haired butler in black tailcoat and white gloves holding a silver tray with a sealed envelope marked by a tiny scales-of-justice symbol, dense crosshatching and stipple linework, fat rounded white title lettering reading 'AI Inn of Court' above the roofline, symmetrical frontal composition, playful spooky camp.
This Week in AI Inn of Court News
Summary by Claude Sonnet 5.5 based on this week’s links:
Harvey was the clearest story this week. MarkTechPost reported that Harvey introduced Harvey Tenet, a model built by post-training the open-source Kimi K3 with Fireworks for long-horizon legal agent work. David Sacks praised it as an example of a specialized model built on an open base and trained on legal data, claiming strong legal benchmark results at a fraction of the cost of frontier models. That cost and performance claim is his characterization, not something the excerpts verify.
Elsewhere, Google Cloud announced Gemini Enterprise for Legal, and Thomson Reuters Institute published a post on how it built Thomson. The excerpts are headline-level, so they show these products exist but little about how they work.
This summary was generated by Claude Sonnet 5.5 to help you explore the links below. Rest assured, I select, organize, and check the links by hand in Google Sheets, and write the introduction and personal commentary in The Main Newsletters myself each week as a labor of love.
This week's links related to AI Inn of Court
Harvey Introduces Harvey Tenet: A Kimi K3 Base Post-Trained with Fireworks for Long-Horizon Legal Agent Work – MarkTechPost
https://www.marktechpost.com/2026/08/23/harvey-tenet-post-trained-kimi-k3-legal-agent-model/
Harvey is a great example of how American companies are building world-class specialized models: they took an open-source base (Kimi K3), post-trained it on legal data, and delivered state-of-the-art performance on legal benchmarks at a fraction of the cost of frontier models.”
https://x.com/DavidSacks/status/2090790063047168473
Introducing Gemini Enterprise for Legal | Google Cloud Blog
https://cloud.google.com/blog/products/ai-machine-learning/introducing-gemini-enterprise-for-legal
How we built Thomson – Thomson Reuters Institute
https://www.thomsonreuters.com/en-us/posts/innovation/how-we-built-thomson/
Cohere Parse | Enterprise Intelligence at Scale
https://cohere.com/blog/parse
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