Hands‑On Kimi K2.6 + Hermes: A Karpathy‑Style Step‑by‑Step Guide

The new Kimi K2.6 release adds noticeable coding and agent capabilities; the author, an early internal tester, shares a complete workflow built around Kimi K2.6 + Hermes + Obsidian.

Quick‑start tutorial : Hermes can be deployed in about 15 minutes, the knowledge base initialized in 5 minutes, and the first video processed in roughly 10 minutes. The tutorial overview (see image) guides users step‑by‑step.

Finding 1 – True video understanding : By feeding a B‑site video link to Hermes, the system downloads the video, transcribes it, and generates a structured note that combines spoken content with visual cues. The 1‑trillion‑parameter multi‑modal model processes both vision and audio at about 100 tokens/s, producing richer notes than audio‑only transcription.

Finding 2 – Reusable Skill : After the first run, Hermes abstracts the whole pipeline into a Skill. Subsequent videos can be processed with a single command, e.g., “use this Skill on the new video,” allowing the workflow to evolve automatically.

Finding 3 – Self‑evolving LLM Wiki : As more material is added, the SCHEMA.md rules let K2.6 automatically associate concepts, merge duplicate information, and record conflicting viewpoints. The knowledge base therefore grows into a coherent, traceable asset rather than a disorganized collection of notes.

Beyond knowledge bases – 300 parallel agents : Official examples include a semiconductor‑targeting quantitative‑strategy project that expands from 100 to 300 sub‑agents and 4 000 steps, and an astrophysics paper transformed into a 40‑page research report with a 20 k‑entry dataset and 14 high‑resolution figures. K2.6 automatically decomposes tasks, creates role‑specific agents, runs them in parallel, and aggregates the results.

Current limitations : Output sometimes mixes Chinese and English, requiring manual polishing for Chinese‑only knowledge bases. The context window is 256 k tokens, which is smaller than some newer models (e.g., GPT‑5.4’s 1 M tokens), so long‑chain tasks may need frequent memory compression, occasionally losing early details.

Getting started : Kimi K2.6 can be tried for free via the Kimi Code portal (https://www.kimi.com/code). The full “nanny‑level” tutorial includes deployment steps for Hermes on Windows/macOS, API‑key configuration, WeChat integration, Obsidian knowledge‑base initialization, first video processing, and Skill reuse.

Hermes deployment on Windows/macOS

Configuring Kimi K2.6 API key

Connecting WeChat for on‑the‑go usage

Initializing an Obsidian knowledge base

Processing the first B‑site video

Persisting a Skill for future reuse

Choose a topic, create the folder structure, drop existing content in, and let Kimi K2.6 handle the rest.