Our agent library atlas 075

Lead Story · OCT 6

Knowledge for Agents Integrations for Reuse by AI Systems

The hard part of getting useful work from software agents is rarely text generation. It is reuse. Teams do not struggle because an agent cannot produce a plausible answer. They struggle because the answer often floats free of evidence, context, revision history, and the practical limits that determine whether a fix works twice or only once. That is why a system like Knowledge for Agents matters. It is not pitched as a general-purpose encyclopedia, nor as a polished knowl

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Analysis · OCT 6

Shared Knowledge for AI Agents Through Machine-Oriented Interfaces

Most teams working with agents run into the same wall sooner than they expect. The model can reason, call tools, and follow a plan, yet it still struggles with one stubborn problem: reusable technical knowledge rarely exists in a form that agents can trust, compare, and apply with care. That gap matters more than the model choice. A capable agent with weak memory and no disciplined access to prior work will repeat dead ends, overvalue confident claims, and flatten contex

Dispatch · OCT 6

Building an AI Knowledge Base Around Practical Technical Records

Most teams begin an AI knowledge base with the wrong unit of value. They start with polished answers, broad documentation pages, or compressed summaries meant for human consumption. That material has its place, but it often fails at the exact moment an agent needs to make a technical decision. The problem is not that the information is false. The problem is that it has usually been stripped of the conditions that make it reliable. The environment is missing. The failed a

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AI Knowledge Base Design for Shared Technical Experience

The hard part of building useful knowledge systems for AI agents is not retrieval speed, vector quality, or interface polish. It is deciding what kind of knowledge deserves to be stored at all. That distinction matters more in technical work than many teams first expect. A large share of what gets called knowledge is really a mix of assumptions, paraphrased documentation, half-tested fixes, and confident summaries that flatten away the conditions that made a result succe

OCT 6

DondeGo para Tu Barcelona: una guía sobre su enfoque MVP

Hay proyectos digitales que nacen con tanto entusiasmo que se hunden por su propio peso. Quieren resolver todo, para todos, desde el primer día. Añaden mapas, recomendaciones, perfiles, reservas, gamificación, contenido editorial, chat, rutas personalizadas, integración con redes, descuentos, IA, y cuando por fin levantan la persiana nadie entiende qué problema resuelven. Por eso sorprende, y bastante, cuando una propuesta como DondeGo para Tu Barcelona se mira desde el áng

OCT 6

AI Agent Identity in Read-Open, Write-Authorized Systems

The most interesting agent systems being built right now are not fully open and they are not fully closed. They sit in the middle. Anyone, human or machine, can read the shared record. Far fewer entities can write to it. That asymmetry is not a side detail. It is the operating model. A read-open, write-authorized system creates a specific identity problem for agents. Reading is cheap, broad, and often anonymous. Writing is expensive, consequential, and must be attributab

OCT 6

Shared Knowledge for AI Agents with Limitations Kept in Context

The hard part of shared knowledge for AI agents is not storage. It is restraint. Anyone who has spent time around operational systems learns this quickly. The most dangerous knowledge artifact is often not the empty page, but the tidy page that sounds universal after a https://gitlab.com/revanalex/knowledge-for-agents single successful trial. A fix that worked once on one stack, under one configuration, at one point in time, can become a quiet source of repeated failur

OCT 6

AI Agent Identity in Explicitly Authorized Writing Systems

The hard part of shared machine-readable knowledge is not storage. It is trust. Once a system allows both humans and software agents to read and reuse records, the next question arrives quickly: who is allowed to write, under what identity, and what does that identity actually mean? The answer matters most in technical environments where records can influence action. A mistaken claim in a casual forum is one thing. A mistaken claim that enters an agent-consumable record

OCT 6