Roger Montti writes that Google has released version 0.2 of the Open Knowledge Format, incorporating five trust signals to facilitate data verification for consumers. These updates cover provenance, generation and verification status, freshness via expiration dates, lifecycle stages, and computational attestation to address questions regarding a concept's origin, accuracy, and timeliness. By providing raw metadata rather than subjective credibility scores, Google enables users or agents to dynamically evaluate information based on objective signals such as authorship and usage counts.
- Attested Computation is a new type used to confirm that values are calculated using sanctioned methods instead of improvised logic.
- The "sources" field provides objective data points like author and last modified date rather than an inherent score.
- Verification can be performed by humans or machine agents, allowing users to filter content based on verification level.
- Attested Computation is a new type used to confirm that values are calculated using sanctioned methods instead of improvised logic.
- The "sources" field provides objective data points like author and last modified date rather than an inherent score.
- Verification can be performed by humans or machine agents, allowing users to filter content based on verification level.
Andrej Karpathy, Google, and Garry Tan are all adopting Markdown as the primary format for agent memory and organizational context. While Karpathy focuses on personal knowledge, Google targets enterprise runbooks, and Tan defines agent roles, they all share a reliance on versioned Markdown files. This shift suggests that the strategic advantage is moving from the specific large language model used to the curated knowledge base a team accumulates.
- Karpathy's LLM Wiki for personal knowledge bases
- Google's Open Knowledge Format for enterprise context
- Garry Tan's gstack for defining agent roles
- The migration of the competitive moat from models to portable data files
- Karpathy's LLM Wiki for personal knowledge bases
- Google's Open Knowledge Format for enterprise context
- Garry Tan's gstack for defining agent roles
- The migration of the competitive moat from models to portable data files
Google Cloud introduces the Open Knowledge Format (OKF), a vendor-neutral specification designed to formalize documentation patterns into a portable, interoperable standard for Large Language Models and agents. By using markdown files with YAML frontmatter, OKF provides a way to represent metadata, context, and curated knowledge that is readable by both humans and machine-parseable systems without requiring specialized SDKs or proprietary platforms.
Key points:
* Addresses the fragmentation of internal knowledge across disparate systems like wikis, databases, and code comments.
* Enables "knowledge as a living wiki" where information can be managed alongside code in version control.
* Employs a minimally opinionated design that separates content producers from consumers.
* Provides reference implementations including an enrichment agent and a static HTML visualizer.
Key points:
* Addresses the fragmentation of internal knowledge across disparate systems like wikis, databases, and code comments.
* Enables "knowledge as a living wiki" where information can be managed alongside code in version control.
* Employs a minimally opinionated design that separates content producers from consumers.
* Provides reference implementations including an enrichment agent and a static HTML visualizer.
