Operating intelligence · updated 2026-06-14
CFC Knowledge Atlas
An evidence-aware intelligence layer over the Clark Farming Company knowledge base. Every article keeps its source trail, review state, and graph relationships — nothing is claimed without a path back to where it came from. This public view is the curated tier; the full Atlas runs on the company's local stack.
Operating System
7 pagesReference · needs-review · 0 sources
Clark Farming Company Canonical Naming
Clark Farming Company is the canonical company and operating identity. retired internal project was a prior product/project name that has been shelved and should not be used as the default label for current work, task packets, skills, agent coordination, wiki relevance sections, or company-facing artifacts. "CFC Quad" is also not a canonical company name; it is at most an informal nickname for the four primary agents and should not …
Doctrine · needs-review · 0 sources
ClarkFarmingCompany Constitution
Version: 1.0 Effective Date: 2026-04-05 Maintained By: Julius (Governance) ClarkFarmingCompany is a family business based in Harmony, North Carolina. It is owned and operated by the Clark family, with Jared Clark as Chief of Staff and primary operator. This constitution defines the company's mission, values, nonnegotiables, and operating principles. It applies to all ventures, subsidiaries, and family business operat…
Doctrine · inferred-with-source-trail · 8 sources
Corporate Roles and Objectives
Understanding corporate organizational structure and role objectives is critical for effective enterprise operations, security awareness, and strategic alignment. Different departments prioritize different outcomes based on their KPIs, risk profiles, and operational mandates. This entry characterizes key corporate roles, their missions, decision-making frameworks, and potential conflict points. Primary Mission: Maxim…
Doctrine · needs-review · 0 sources
Enterprise AI Truth Governance Harness
Author: Julius (Governance Commander) Date: 2026-05-21 Context: Response to Emerson senior leadership concern about competing truths, epistemic drift, and knowledge poisoning in enterprise AI systems Related: Karpathy Large Language Model Wiki pattern, RAG data governance, Multi-Agent Orchestration governance Enterprise AI systems face a fundamental challenge: how to maintain truth integrity when ingesting from sourc…
Governance · inferred-with-source-trail · 3 sources
Open Source Release Process
Type: Process / Procedure Category: Governance — Open Source Releases Created: 2026-05-31 Authority: Jared (founder) This page documents Clark Farming Company's process for releasing open-source projects to the community. These guidelines were established by Jared on May 31, 2026, and formalized as an artifact and wiki page. The process covers three phases: pre-release preparation, release execution, and post-release…
Governance · needs-review · 0 sources
Wiki Content Quality Standards
Type: Governance / Quality Standard Category: Wiki Content Quality Created: 2026-05-31 This page documents Clark Farming Company's wiki content quality standards and audit findings. The wiki follows the Karpathy LLM Wiki pattern — growing organically from conversation — which means quality varies by creation method and topic. This page tracks quality metrics and defines the target standards. Target: 1,400 words minim…
Governance · needs-review · 0 sources
Wiki Frontmatter Maintenance
Redirect: This page has been consolidated into concepts/wiki-frontmatter-maintenance.
Agent Stack
28 pagesArchitecture · needs-review · 0 sources
Agent Architecture
Multi-Agent Orchestration system design for the retired internal project Quad — four specialized AI agents operating in coordinated parallel, each with distinct roles, toolsets, and decision authority. Specialization over generalization. Each agent has a defined domain of expertise and operates with maximum competence within that domain. Julius as sole delegator. Only Julius creates tasks, assigns work, and integrates results. No ag…
Architecture · needs-review · 0 sources
retired internal project Architecture
The retired internal project system architecture follows a hub-and-worker topology with a central Mac Studio coordinating distributed worker nodes connected via SSH-bridged Agent Communication Protocol (ACP). retired internal project infrastructure is designed as a distributed system where a central hub coordinates multiple worker nodes across different hardware platforms. The architecture balances centralized control with distributed execution, en…
Knowledge System · needs-review · 0 sources
retired internal project Knowledge Base
The retired internal project Knowledge Base is the centralized information repository for retired internal project, implemented as an Obsidian-backed wiki vault. It serves as the single source of truth for documentation, research findings, operational procedures, and organizational knowledge. The knowledge base is maintained by retired-internal-project/octavius-agent|retired-internal-project/octavius-agent and consumed by all agents and human operators. It follows structured orga…
Telemetry · inferred-with-source-trail · 2 sources
retired internal project Telemetry Platform
The retired internal project Telemetry Platform provides observability across the retired internal project infrastructure — metrics, logging, distributed tracing, and dashboarding for monitoring agent operations, system health, and security events. The telemetry platform collects, processes, and visualizes operational data from all retired internal project components. It enables proactive monitoring, incident detection, performance analysis, and compliance auditin…
System · inferred-with-source-trail · 4 sources
EML Operator - Single Binary Operator for All Elementary Functions
The EML (Exp-Minus-Log) operator is a single binary function that can generate all standard elementary mathematical functions—arithmetic operations, exponentials, logarithms, trigonometric and hyperbolic functions, and fundamental constants (e, π, i)—when combined with only the constant 1. Discovered by Andrzej Odrzywołek in March 2026, this is the continuous mathematics equivalent of the NAND gate in Boolean logic: …
System · needs-review · 0 sources
File-Based Memory
Category: Operational Infrastructure Applies To: All Four Persistent Agents Version: 1.0 (2026-04-10) File-Based Memory is retired internal project's state persistence mechanism where all cognitive state, decisions, and learnings are written to durable files rather than relying on in-memory context. This ensures continuity across session restarts and prevents knowledge loss. Core Principle: "Mental notes" do not survive restarts. If…
Tool/System · inferred-with-source-trail · 4 sources
Firecrawl Document Parsing
Firecrawl provides automated document parsing capabilities that convert various file formats (PDFs, Excel spreadsheets, Word documents) into clean, structured markdown. The service detects file types automatically from URLs and processes them without requiring separate upload steps. This is particularly useful for extracting structured data from business documents, reports, and spreadsheets as part of automated scrap…
Doctrine · needs-review · 0 sources
Governance Framework
The retired internal project Governance Framework defines the policies, decision structures, risk management processes, and audit mechanisms that ensure all agent operations align with organizational values and retired-internal-project/nonnegotiables|retired-internal-project/nonnegotiables. Governance in retired internal project is the system of rules, processes, and oversight that guides autonomous agent behavior. It ensures that agents operate safely, effectively, and in alignm…
Decision/Risk · needs-review · 0 sources
Governance Model (redirect)
Redirect: This page has been consolidated into concepts/governance-model.
Resource · inferred-with-source-trail · 1 sources
Hermes Agent Community
URL: https://get-hermes.ai/community/ Category: External Resource — AI Agent Framework Added By: Julius (Governance Commander) Date Added: 2026-04-12 The official Hermes Agent community hub — a resource for the open-source Hermes Agent framework that powers retired internal project's Multi-Agent Orchestration infrastructure. This is the canonical community resource for: Framework documentation and guides Community discussions and su…
Lessons · needs-review · 0 sources
Hermes Agent Configuration Lessons
Lessons learned from configuring and operating Hermes Agent across the retired internal project Quad infrastructure. Problem: Local inference models (Qwen3.6-27b via LM Studio) are slow. Default 600-second timeout causes cron jobs to fail mid-execution. Solution: Increase timeout to 1200 seconds for jobs running local inference. Affected Jobs: Wiki lint cron (local) Industrial knowledge curation (local) Problem: Different tasks requ…
Tool/System · needs-review · 0 sources
Hermes Agent Framework
Hermes Agent is the underlying framework that powers all retired internal project agents. It provides the runtime environment, tool system, skill framework, configuration model, and plugin architecture that enable autonomous agent operation. Hermes Agent is a modular agent framework that transforms large language models into capable, tool-using agents. Each retired internal project agent — retired-internal-project/julius-governance-agent|retired-internal-project/julius-governance…
Optimization · inferred-with-source-trail · 2 sources
Hermes Agent Optimization
Domain: AI Agents, Fine-Tuning, Tool Calling Status: Active Research Strategic Importance: High — Core to retired internal project agent capabilities Hermes Agent Optimization is a specialized approach to training language models for tool-calling and multi-step task execution within the Hermes Agent framework. Unlike generic chat models or benchmark-optimized systems, Hermes-optimized models prioritize harness-native behavior — exec…
Infrastructure · inferred-with-source-trail · 1 sources
Hermes Agent SQLite Memory Infrastructure
Hermes Agent implements a hybrid persistence architecture combining JSONL session transcripts with SQLite databases for structured indexing, full-text search, and task tracking. This infrastructure emerged organically during the Clark Farming Company Quad buildout (April–May 2026) and is maintained as the primary memory and session-recall system for all agent profiles. The active system consists of two SQLite databas…
Integration · needs-review · 0 sources
Hermes Hierarchy Integration
retired internal project's applied runtime mapping of the hierarchical-agents coordination layer onto the local Hermes install.* Hermes Hierarchy Integration is the platform pattern that organizes persistent Hermes profiles into a structured runtime organization. It provides a shared org chart, IPC message bus, chain-aware delegation, per-profile memory stores, and generated handoff documentation. This integration provides the agent…
Agent · needs-review · 0 sources
Julius (redirect)
Redirect: This page has been consolidated into entities/julius.
Agent · needs-review · 0 sources
Julius Governance Agent
Julius is the governance agent of retired-internal-project/the-quad|retired-internal-project/the-quad, responsible for policy enforcement, risk management, strategic oversight, and ensuring all operations align with retired-internal-project/nonnegotiables|retired-internal-project/nonnegotiables. Julius serves as the authoritative decision-maker and compliance guardian across the retired internal project Multi-Agent Orchestration system. {Verified} Enforce governance policies across all agent ope…
Pattern · inferred-with-source-trail · 1 sources
Multi-Agent Orchestration
Category: Agent Architecture / Systems Design Maturity: Established (at retired internal project) Multi-Agent orchestration is the practice of coordinating multiple specialized AI agents to accomplish complex tasks that exceed the capability of any single agent. retired internal project implements this through The Quad — four persistent agents (Julius, Cypher, Reacher, Octavius) with distinct roles, communicating through structured delegation, shar…
System · needs-review · 0 sources
Nightly Learning Loop (redirect)
Redirect: This page has been consolidated into concepts/nightly-learning-loop.
Doctrine · needs-review · 0 sources
Nonnegotiables
The Nonnegotiables are the immutable principles that govern all retired internal project operations. They are not guidelines, not suggestions, not aspirational goals. They are the floor below which no decision, no line of code, and no action may fall — regardless of pressure, timeline, or convenience. No system is deployed, no feature is released, and no workflow is adopted without first answering: "Could this cause harm?" This appl…
Agent · needs-review · 0 sources
Octavius Agent
Octavius is the Knowledge & Education (K&E) agent of retired-internal-project/the-quad|retired-internal-project/the-quad, responsible for research, documentation, knowledge curation, and building the information foundation that other agents and humans rely on. Octavius serves as the intelligence engine of retired internal project — finding, evaluating, synthesizing, and organizing knowledge. {Verified} Conduct web research and information gathering Create and main…
Tool/System · needs-review · 0 sources
Removing Unwanted Web Content (redirect)
Redirect: This page has been consolidated into concepts/removing-unwanted-web-content.
Schema · needs-review · 0 sources
Schema Configuration
YAML frontmatter schema and metadata configuration for the retired internal project wiki. Defines the structure, required fields, and validation rules for all wiki pages. Every wiki page must include valid YAML frontmatter with the following fields: Tags follow a hierarchical taxonomy for consistent categorization: retired-internal-project — retired internal project infrastructure, agents, governance ai-Machine Learning — AI/Machine Learning concepts, models, tech…
Resource · inferred-with-source-trail · 7 sources
Spec-Kit
Spec Kit is GitHub's open-source toolkit for spec-driven development — a methodology that flips traditional software development by making specifications executable and directly generating working implementations. Instead of specs being disposable scaffolding, they become the source of truth that drives code generation through AI agents. Strategic Value for retired internal project: Directly validates and operationalizes the Superpo…
Governance Record · needs-review · 0 sources
Subagent Specialties Governance
Category: Governance Framework Applies To: All Four Persistent Agents Version: 1.0 (2026-04-10) Subagent Specialties Governance is the system by which each persistent agent manages their specialist delegates while remaining accountable to team standards. It balances individual autonomy with collective responsibility through a peer review and majority vote mechanism. Core Principle: Each agent curates their own specia…
Resource · inferred-with-source-trail · 6 sources
Superpowers Method
Superpowers is a complete software development workflow for AI coding agents, built on composable "skills" that activate automatically. Instead of jumping into code, agents using Superpowers first extract specifications through conversation, present designs in digestible chunks for validation, create detailed implementation plans (2-5 minute tasks), then execute via subagent-driven development with two-stage review. …
System · needs-review · 0 sources
The Quad
The Quad is the core four-agent team that operates retired internal project infrastructure. Each agent has a specialized role, and together they form a coordinated system capable of autonomous operation under governance oversight. {Verified} Julius is the governance authority for the entire retired internal project system. Julius enforces policies, manages risk, and serves as the final decision-maker. All high-impact actions flow through Julius for…
Resource · inferred-with-source-trail · 1 sources
Web Research Resources and Site Accessibility
Type: Reference Category: Research Infrastructure Status: Active — Maintained artifact for all wiki research This page documents the verified accessibility of websites for AI agent web extraction tools (web_extract, web_search). It maps which sites respond reliably to automated requests and which block AI agents, providing a fallback chain for research workflows. Primary artifact: ~/ClarkFarmingCompany/artifacts/web-…
Knowledge & Memory
12 pagesPattern · needs-review · 0 sources
Agent Coordination Patterns
The retired internal project Quad (Julius, Cypher, Reacher, Octavius) uses several coordination patterns for distributed work across machines. This document captures the patterns that have been tested and validated. Use case: Send a task to a remote agent via Hermes Agent's delegate_task with SSH routing. How it works: Julius calls delegate_task with a route pointing to remote machine SSH tunnel bridges the ACP (Agent Communication …
Concept · inferred-with-source-trail · 1 sources
Agent Memory Trust Contract: Remember, Cite, Forget
Source status: derived from Vox's X article, "A Framework for Agent Memory: Remember, Cite, Forget" (2026-05-22), reviewed from the live X article page. Treat it as a practitioner framework, not a formal standard. Agent memory is reliable only when it does three jobs at once: Remember what should persist. Cite the source and authority level of what was remembered. Forget or demote memories that are stale, superseded,…
Integration · needs-review · 0 sources
Agent Wiki Integration
Agent Wiki Integration describes the workflow and architecture through which AI agents contribute to, query, and maintain organizational knowledge bases (wikis). Rather than requiring humans to manually document every concept, research finding, or lesson learned, agents autonomously research, draft, review, and publish wiki entries following established quality standards. This approach transforms wikis from static re…
Concept · inferred-with-source-trail · 1 sources
Agent-Maintained Wiki
Category: Agent Pattern / Knowledge Management Maturity: Established An agent-maintained wiki is a knowledge base where an Large Language Model agent autonomously writes, updates, and maintains all content—summarizing sources, creating entity/concept pages, cross-referencing, and health-checking for contradictions. Humans curate sources and ask questions; the agent does all bookkeeping. This pattern makes persistent …
Index · needs-review · 0 sources
AI Memory and Context Management
pages: 8 created 2026-05-09 by Julius (GOV) and Octavius (K&E), plus 2026-05-23 bookmark-derived memory trust contract.* This section covers the landscape of AI memory systems, context window management, and long-term memory architectures for AI agents as of 2026. Total files: 9 articles Julius: 2 articles (vector memory systems, context window management) Octavius: 6 articles (Reddit sentiment, YouTube landscape, ep…
Concept · inferred-with-source-trail · 9 sources
Episodic Memory for AI Agents
Episodic memory is the human capacity to remember specific events — what happened, when it happened, and where. In cognitive science, it was distinguished from semantic memory (general facts) and procedural memory (learned routines) by Endel Tulving in 1972. The same distinction has proven remarkably useful as an architectural lens for designing AI agent memory systems. For an AI agent, episodic memory is the chronol…
System · inferred-with-source-trail · 4 sources
Local-First Hermes Runtime Architecture
The local-first Hermes runtime architecture is the emerging design direction for running Clark Farming Company’s day-to-day agent work primarily on local models while using frontier models only as reviewers, evaluators, curriculum designers, and occasional planners. The core principle is simple: local models do the work; frontier models improve the harness outside the hot path. The discussion began with a broad idea:…
Pattern · inferred-with-source-trail · 8 sources
Multi-Agent Memory Coordination Patterns
Memory is the central unsolved problem in Multi-Agent Orchestration AI systems. While single-agent memory — storing context and retrieving it when relevant — has become relatively straightforward, Multi-Agent Orchestration memory introduces coordination, consistency, isolation, and security challenges that mirror decades of distributed systems research [Verified from Zylos Research]. The statistics are stark: Gartner…
Concept · inferred-with-source-trail · 1 sources
Retrieval-Augmented Generation
Category: AI Inference / Knowledge Retrieval Maturity: Established Retrieval-Augmented Generation (RAG) is a pattern that enhances Large Language Model responses by retrieving relevant external documents before generating answers. Instead of relying solely on training data, the model accesses a knowledge base at inference time, producing more accurate and up-to-date responses. retired internal project's wiki functions as a RAG-like …
Concept · inferred-with-source-trail · 8 sources
Semantic Memory for AI Agents
Semantic memory is the human capacity to store general facts, concepts, and relationships independent of when or where they were learned. Unlike episodic memory (which records specific events with timestamps), semantic memory answers "what" questions rather than "when did this happen" questions. If you know that Paris is the capital of France, that knowledge lives in your semantic memory regardless of whether you lea…
Concept · inferred-with-source-trail · 5 sources
Vector Memory Systems for AI Agents
Vector memory systems are the foundational storage layer for AI agent long-term memory. They store high-dimensional embeddings — numerical representations of text, images, or other data — and enable similarity-based retrieval at scale. For AI agents, vector memory is the mechanism that transforms stateless language models into systems with persistent, searchable recall across sessions. As of 2026, the vector database…
Governance · needs-review · 0 sources
Wiki Frontmatter Maintenance
Wiki frontmatter maintenance encompasses the ongoing processes of validating, repairing, and enriching YAML frontmatter across the retired internal project wiki. With 2,364+ markdown files and frontmatter validity sitting at approximately 35-36%, this is one of the most persistent wiki health challenges. Every content page must include YAML frontmatter with the following fields: Exempt from frontmatter requirements: index.md files, …
Revenue Plays
5 pagesRevenue Brief · inferred-with-source-trail · 4 sources
AI-Enabled Business Services Strategy
Offer AI-enabled business management services as a recurring revenue model, starting with small businesses as a learning lab and expanding to municipal governments and utilities. The core infrastructure — Mac Studio, Mac Mini, 3090 worker, wiki with ~2,400 pages, team of agents — is the competitive advantage. This is not about selling AI tools. It is about solving expensive business problems with AI as the engine, de…
Index · inferred-with-source-trail · 7 sources
Business Operations
This directory contains knowledge entries related to corporate organizational structure, business operations, and enterprise dynamics. [Corporate Roles and Objectives](corporate-roles-and-objectives.md) - Comprehensive guide to corporate department functions, decision frameworks, KPIs, pain points, and cross-functional dynamics. Essential for understanding how enterprises operate and make decisions. Understanding bus…
Proposal System · inferred-with-source-trail · 1 sources
Chase Defense Partners AI Proposal System
Chase Defense Partners operates a deliberately minimal AI proposal system for defense-contracting work. The system is built around two Python tools, Anthropic Claude API inference, and Obsidian markdown vaults. Its central lesson is not technical sophistication; it is disciplined scope control. The system exists to produce business output: parse solicitations, generate proposal drafts, support debriefs, ingest lesson…
Revenue Brief · inferred-with-source-trail · 2 sources
Monthly Earner Product Architecture
Monthly Earner is Clark Farming Company's product line for delivering AI-driven business intelligence tools to small rural businesses. The product uses self-contained HTML dashboards as the primary deliverable format, generated from customer data through Hermes Agent processing pipelines. The target market is cash-heavy, low-digital-adoption businesses in and around Harmony, NC (ZIP 28634). As of 2026-05-26, the conf…
Revenue Brief · inferred-with-source-trail · 1 sources
Small Business Data Collection Strategies
Small business owners are time-poor, tech-fatigued, and skeptical. Asking them to "start tracking data" is asking them to add work to a day that's already full. The solution is not better spreadsheets — it is making data collection invisible, frictionless, or already happening. Design principle: Never require new data entry processes, new software, or changes to daily operations as a prerequisite for value delivery. …
Municipal / Industrial
2 pagesResearch · inferred-with-source-trail · 6 sources
Town of Harmony Research
Category: Municipal Government Applies To: Harmony, NC local government Version: 1.0 (2026-05-10) Research and documentation related to the Town of Harmony, NC, including government contacts, budget data, historical information, and municipal operations. Official town website and contact information Town council and administrative staff Department heads and key personnel Iredell County public records Annual budget do…
Source Note · inferred-with-source-trail · 4 sources
Town of Harmony, North Carolina - Public Records Data
Status: Incorporated Town (since 1927) County: Iredell County State: North Carolina Coordinates: 35°57′33″N 80°46′25″W Elevation: 968 ft (295 m) Harmony is an incorporated town in Iredell County, North Carolina. The town was officially incorporated in 1927. As a small incorporated town, Harmony residents are primarily served by Iredell County government for most services. Bert Connolly - Chairman Melissa Neader - Vic…
Products & Experiments
3 pagesStorytime Theme · needs-review · 0 sources
Bluey
A sunny, laid-back world of Blue Heeler dog families in suburban Queensland, Australia, where every story grows out of a game the kids invent. Cardboard boxes become magic machines, the whole house becomes a hotel, a balloon becomes the most precious thing in the world. Play is never just play here: inside each invented game, somebody learns something true about themselves, their family, or each other. The flavor to …
Storytime Theme · needs-review · 0 sources
Minecraft
A blocky, sunlit world where everything — the grass, the trees, the water, the clouds, even the animals — is built from neat little cubes, and where anything you can imagine can be built one block at a time. Stories live in the friendly daytime Overworld: rolling biomes, cozy villages, and gentle creatures. The bedtime-safe flavor to preserve is the quiet joy of building, gathering, crafting, and exploring with frien…
Product · inferred-with-source-trail · 2 sources
Storytime Education Reference Package
The Storytime Education Reference Package is a structured wiki guidance system that enables Storytime to generate age-appropriate, subject-specific educational content without requiring users to specify topics or criteria manually. It consists of per-subject, per-grade guidance files organized under wiki/wiki/education/storytime/, shared reference documents, and a subject/grade map. Location: wiki/wiki/education/stor…
AI / Agent Reference
14 pagesReference · inferred-with-source-trail · 1 sources
Agent Trace Distillation
Technique for distilling human agent-management skill into model training data by converting user agent interaction traces into synthetic chain-of-thought trajectories. This page was reviewed against the exact bookmarked X post on 2026-05-23. The idea remains preliminary and single-source; no implementation or paper was found during the bookmark triage pass. When frontier Large Language Model users develop skill in m…
Concept · inferred-with-source-trail · 5 sources
AI Agents
An AI Agent is an autonomous system that perceives its environment, reasons about goals and constraints, takes actions through tools or APIs, and iterates toward task completion with minimal human intervention. Modern agents use concepts/large-language-models as their reasoning engine, augmented with tool calling capabilities, persistent memory, planning loops, and safety guardrails. Multi-Agent Orchestration systems…
Reference · inferred-with-source-trail · 1 sources
Atlas: Open Source Inference Engine (Rust + CUDA)
Atlas is a pure Rust + CUDA inference engine that claims 3.1x faster performance than vLLM with a dramatically smaller footprint (~2.5GB vs vLLM's 20+GB). Performance: 111.4 tok/s vs vLLM's 37.5 tok/s on Qwen3.5-35B [Unverified] Image size: ~2.5GB (vs vLLM's 20+GB) [Unverified] Cold start: <2 minutes [Unverified] Dependencies: No Python, no PyTorch Model support: Qwen, Gemma, Nemotron, Mistral, MiniMax Features: MTP …
Reference · needs-review · 0 sources
Fine-Tuning Methodologies
Overview of Large Language Model fine-tuning approaches — from supervised fine-tuning (SFT) to reinforcement learning from human feedback (RLHF) and beyond. Each methodology optimizes different objectives and requires different data formats. The simplest and most common fine-tuning method. Train the model on labeled input-output pairs using standard cross-entropy loss. Or conversational format: Standard next-token pr…
Evaluation · needs-review · 0 sources
Firecrawl Web Search Evaluation
In May 2026, Firecrawl was installed and configured on the Hermes Agent instances as an advanced web search and scraping capability. The question: does it actually improve search quality over the existing web_search tool? At the time of evaluation, Hermes Agent provided: web_search — General-purpose web search engine. Good for broad queries, news, current events. web_extract — Extract content from URLs into markdown …
Reference · needs-review · 0 sources
Function Calling
Function calling enables Large Language Models to interact with external tools and APIs by generating structured function calls instead of natural language responses. The model receives function schemas, determines when and how to call them, and returns structured arguments for execution. Define functions: Provide function schemas (name, description, parameters) with the prompt Model decides: Large Language Model det…
Reference · needs-review · 0 sources
GGUF Format (redirect)
Redirect: This page has been consolidated into concepts/gguf-format.
Reference · inferred-with-source-trail · 1 sources
Karpathy's LLM Knowledge Bases
Karpathy described using Large Language Models to build personal knowledge bases for research topics. The core idea: use Large Language Models to distill and organize information into personal "wikis" for domains you're researching. Feed an Large Language Model a set of documents/sources on a topic Have the Large Language Model distill, organize, and structure the information Create a personal "wiki" or knowledge bas…
Reference · needs-review · 0 sources
Karpathy: Build For Agents
Karpathy's framework for thinking about agent-native interfaces. CLIs are the ideal interface for AI agents because they're "legacy" technology agents can natively use. CLIs are agent-native: Agents can install CLIs, combine them, and build dashboards from them Model Context Protocol as the bridge: Model Context Protocol provides standardized agent access Skills as documentation: Well-written skills let agents unders…
Reference · needs-review · 0 sources
Model-Context-Protocol
Model Context Protocol is an open protocol that standardizes how AI applications connect to external tools and data sources. Created by Anthropic (November 2024), it provides a unified interface for integrating Large Language Models with local files, databases, APIs, and custom tools. It has become the de facto standard for AI agent tool integration as of 2026. Key Features: Open-source specification with TypeScript-…
Reference · needs-review · 0 sources
Quantization Theory
The mathematical foundations and practical techniques for reducing neural network precision — from FP32/FP16 floating point to INT8, INT4, and beyond. Quantization enables running large models on constrained hardware with minimal quality degradation. Neural networks are remarkably robust to precision reduction. Key reasons: Over-parameterization: Models have far more parameters than needed. Reducing precision removes…
Reference · inferred-with-source-trail · 1 sources
SRAG: Skill Retrieval Augmentation for Agentic AI
Skill Retrieval Augmentation (SRA) is a paradigm where agents dynamically retrieve, incorporate, and apply relevant skills from large external skill corpora on demand, rather than enumerating all available skills in the context window. In existing agent systems, the dominant strategy for incorporating skills is to explicitly enumerate available skills within the context window. This fails to scale: as skill corpora e…
Reference · needs-review · 0 sources
Structured Output Generation
Techniques for constraining Large Language Model output to specific formats — JSON, XML, CSV, or custom schemas — enabling reliable parsing and downstream processing. Critical for production applications where output must be machine-readable. Most providers offer a "JSON mode" that constrains output to valid JSON. OpenAI: response_format: { "type": "json_object" } Anthropic: System prompt: "Always respond in valid JS…
Reference · needs-review · 0 sources
Tool Calling
Tool calling is the broader paradigm of enabling AI agents to use external tools — functions, APIs, commands, and services — to extend their capabilities beyond pure text generation. Function calling is one mechanism for tool calling; Model Context Protocol (Model Context Protocol) is another. Model Context Protocol standardizes how AI applications connect to external tools and data sources. Components: Client: AI ap…