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re:publica 26: OpenClaw and the Architecture of Visible AI Agents

re:publica 26: OpenClaw and the Architecture of Visible AI Agents

AI Agents Do Not Need Better Policies. They Need an Action Inventory.

AI Agents Do Not Need Better Policies. They Need an Action Inventory.

Technical diagram of the Cerebras enterprise knowledge base retrieval pipeline

How Cerebras Built Its Internal Knowledge Base

Technical concept diagram showing Microsoft Ontology Playground as a learning pipeline from domain ontologies to RDF XML export and knowledge graph platform selection

Ontology Playground: Learn the Graph Before You Buy the Graph Database

LangChain open-source software engineering agent factory: local coding, cloud agents, review agents, repo memory, open models, and LangSmith traces.

LangChain’s Open-Source Software Factory

OpenShip self-hosted deployment dashboard, repo screenshot from oblien/openship.

OpenShip: Self-Hosted Deployment for the Agentic Engineering Era

In April 2026, Andrej Karpathy published a GitHub Gist describing a pattern he called the LLM Wiki. In the months since, four different teams have shipped the same idea without coordinating:

The State of Agent Wikis

How @gumclaw, Gumroad's AI operations agent, is set up: Hermes, Fable 5, tools, workflows, shipped work, memory, and guardrails.

How Gumclaw Works

re:publica 26: OpenClaw and the Architecture of Visible AI Agents

re:publica 26: OpenClaw and the Architecture of Visible AI Agents

AI Agents Do Not Need Better Policies. They Need an Action Inventory.

AI Agents Do Not Need Better Policies. They Need an Action Inventory.

Technical diagram of the Cerebras enterprise knowledge base retrieval pipeline

How Cerebras Built Its Internal Knowledge Base

Technical concept diagram showing Microsoft Ontology Playground as a learning pipeline from domain ontologies to RDF XML export and knowledge graph platform selection

Ontology Playground: Learn the Graph Before You Buy the Graph Database

LangChain open-source software engineering agent factory: local coding, cloud agents, review agents, repo memory, open models, and LangSmith traces.

LangChain’s Open-Source Software Factory

OpenShip self-hosted deployment dashboard, repo screenshot from oblien/openship.

OpenShip: Self-Hosted Deployment for the Agentic Engineering Era

In April 2026, Andrej Karpathy published a GitHub Gist describing a pattern he called the LLM Wiki. In the months since, four different teams have shipped the same idea without coordinating:

The State of Agent Wikis

How @gumclaw, Gumroad's AI operations agent, is set up: Hermes, Fable 5, tools, workflows, shipped work, memory, and guardrails.

How Gumclaw Works

The video examines why 95% of AI projects in large companies fail, attributing it to their internal implementation challenges rather than AI's capabilities. It highlights opportunities for startups to fill this gap with agile and value-adding AI solutions.

30. Oktober 2025

GenAI Updates

Good News for Startups: Large Companies Struggle with AI Implementation

Good news for startups: Big companies are tripping over AI, and that opens doors for…

Steve Ruiz discusses tldraw's latest experiments with AI on an infinite canvas. In 2024, tldraw.computer was created as a loose visual programming environment.

30. Oktober 2025

GenAI Updates Published

tldraw.computer – Steve Ruiz, tldraw

tldraw.computer — Steve Ruiz on drawing apps into life I keep thinking about that moment…

This video introduces DSPy, a framework for incorporating Large Language Models (LLMs) into production systems, specifically demonstrating its use in a geospatial conflation pipeline. It addresses the challenges of writing and managing prompts, which can be unruly and vary by model within large AI pipelines. The session explains how DSPy functions and its benefits for pipeline creators and managers in optimizing LLM integration.

30. Oktober 2025

GenAI Updates

Let the LLM Write the Prompts: An Intro to DSPy in Compound AI Pipelines

Let the LLM Write the Prompts: Why DSPy Matters for Real AI Pipelines If you’ve…

Nathan Lambert introduces a taxonomy for next-generation AI reasoning models, identifying four key traits: skills, calibration, strategy, and abstraction. He highlights that current AI models excel in skills and calibration but struggle with strategy and abstraction for long-horizon tasks. The talk emphasizes how developing these two traits is crucial for creating reliable and effective AI agents capable of advanced planning.

30. Oktober 2025

GenAI Updates

A Taxonomy for Next-Gen AI Reasoning: Skills, Calibration, Strategy, and Abstraction

A Taxonomy for Next-Gen AI Reasoning: Skills, Calibration, Strategy, and Abstraction I watched Nathan Lambert's…

This talk explores Agentic GraphRAG, bridging the gap between AI and logical reasoning. It examines how graph databases enhance AI agents, addressing limitations in existing systems, and improving accuracy and reducing AI hallucinations in complex, domain-specific tasks.

30. Oktober 2025

GenAI Updates

Agentic GraphRAG: The Logical Advantage of AI

Agentic GraphRAG: When AI Learns to Think in Networks I watched a talk recently that…

Jon Stewart interviews Geoffrey Hinton, a pioneer in AI, to discuss the rapid advancements in artificial intelligence. They explore the functionality of neural networks, the current capabilities of AI, and Hinton's concerns about the technology's future direction.

30. Oktober 2025

GenAI Updates

AI: What Could Go Wrong? with Geoffrey Hinton | The Weekly Show with Jon Stewart

AI: What Could Go Wrong? A short, human take on Jon Stewart’s chat with Geoffrey…

Jon Stewart hosts Geoffrey Hinton, the 'Godfather of AI,' to discuss the rapid advancements in artificial intelligence. They explore the functionality of neural networks, current AI capabilities, and Hinton's profound concerns about the future direction of AI. The conversation delves into the potential for disruption and the critical need for regulation.

30. Oktober 2025

GenAI Updates

AI: What Could Go Wrong? with Geoffrey Hinton | The Weekly Show with Jon Stewart

AI: What Could Go Wrong? Have you ever watched two people nerd out about something…

Now in its third year, this unique, year-over-year, cross-sectional study shows where the common use cases are, where returns are emerging, and which people- and process-levers could convert mainstream use into durable ROI.…Read More

29. Oktober 2025

GenAI Updates

2025 AI Adoption Report: Gen AI Fast-Tracks Into the Enterprise

2025 AI Adoption Report: Gen AI Fast-Tracks Into the Enterprise If you’re juggling budgets, pilots,…

Surpassing traditional chat-based tools, Flowith streamlines tasks on a multi-thread interface powered by a most advanced agent framework. The intuitive canvas and smart framework boost productivity, helping users stay in the flow.

29. Oktober 2025

GenAI Updates

Flowith – Your AI Creation Workspace, with Knowledge

Flowith — Your AI creation workspace that actually helps you stay in the flow If…

28. Oktober 2025

GenAI Updates

Typeless | AI Voice Dictation That's Actually Intelligent

Typeless | AI Voice Dictation That’s Actually Intelligent You ever start dictating and then realize…