brianletort.ai
Thought Leadership

Writing

Thoughts on agentic AI, context engineering, data architecture, and the future of intelligent systems. Deep dives from 25+ years at the cutting edge.

Featured Series

Agent Societies

A 4-part series exploring what happens when agents interact at scale—from emergence to institutions. Grounded in real observations from Moltbook.

Featured Series

Results as a Service

A 2-part deep dive into outcome-based business models and the architecture that makes them real—from Result Contracts to Internal RaaS.

Featured Series

The AI-Native Computer

A 3-part series exploring how AI is reshaping enterprise architecture—from LLMs as the new CPU to BDAT playbooks for the AI-native enterprise.

Agent Societies · Part 4 of 4

Looking Ahead: 12 Agent-Native Institutions Nobody's Talking About

Here's what gets built when agents can form institutions. These are the 'StackOverflow 2.0s' that turn messy questions into verified artifacts.

February 22, 20268 min read
AI ArchitectureAgent SocietiesInstitutionsProduct Strategy
Read more
Agent Societies · Part 3 of 4

From Emergence to Competence: PAR Loops, World Models, and Agent Economies

Societies generate priors. World models generate consequences. Verification generates truth. Here's the architecture that turns emergent behavior into emergent competence.

February 15, 20267 min read
AI ArchitectureAgent SocietiesPAR LoopsWorld Models
Read more
Agent Societies · Part 2 of 4

Reinforced Learning Environments: Why Most Agent Networks Will Fail

Emergence isn't enough. Most agent societies will collapse into confident sludge. Here's what separates the ones that compound from the ones that collapse.

February 8, 20266 min read
AI ArchitectureAgent SocietiesEmergenceVerification
Read more
Agent Societies · Part 1 of 4

The Petri Dish: When Agents Build Societies

I've been watching agents build a society. The emergent behaviors appearing when large numbers of agents interact without human orchestration point to something bigger than better chatbots.

February 1, 20266 min read
AI ArchitectureAgent SocietiesEmergenceMulti-Agent Systems
Read more
Building SemanticStudio · Part 1 of 8

SemanticStudio: A Production-Ready Enterprise RAG Agent System

Open-sourcing the multi-agent chat platform I built to test my AI-native architecture ideas. 28 domain agents, 5 configurable modes, 4-tier memory with Context Graph, GraphRAG-lite, and everything enterprises need to build production AI.

January 26, 20268 min read
SemanticStudioMulti-Agent SystemsRAGEnterprise AIOpen Source
Read more
Building SemanticStudio · Part 2 of 8

The Chat Experience: Sessions, Folders, Files, and More

A complete walkthrough of SemanticStudio's user-facing features—from session management to file uploads to power user shortcuts.

January 26, 20266 min read
SemanticStudioChat UXProduct DesignEnterprise AI
Read more
Building SemanticStudio · Part 3 of 8

Domain Agents: Specialization at Scale

Why SemanticStudio uses specialized domain agents instead of one general-purpose assistant, and how to configure and manage them—from 12 to 50+ agents.

January 26, 20267 min read
SemanticStudioMulti-Agent SystemsEnterprise AIAgent Architecture
Read more
Building SemanticStudio · Part 4 of 8

RAG Chain Configuration: Models, Modes, and Fine-Tuning

The power user's guide to configuring SemanticStudio's RAG chain—multi-provider LLM support, mode parameters, and full control over cost vs. quality.

January 26, 20267 min read
SemanticStudioRAGLLM ConfigurationEnterprise AI
Read more
Building SemanticStudio · Part 5 of 8

Memory as Infrastructure: The Complete 4-Tier System

A deep dive into SemanticStudio's 4-tier memory architecture—working context, session memory, long-term memory, and the Context Graph. Progressive compression meets knowledge bridging.

January 26, 20268 min read
SemanticStudioMemory SystemsContext EngineeringRAG
Read more
Building SemanticStudio · Part 6 of 8

GraphRAG-lite: Beyond Vector Similarity

How SemanticStudio's knowledge graph and entity resolution enable relationship discovery that pure vector RAG misses.

January 26, 20268 min read
SemanticStudioGraphRAGKnowledge GraphsRAGEntity Resolution
Read more
Building SemanticStudio · Part 7 of 8

ETL & Agent Creation: Growing Your Multi-Agent System

How SemanticStudio's self-learning ETL pipelines ingest data, build knowledge graphs, and automatically create new domain agents.

January 26, 20267 min read
SemanticStudioETLData EngineeringMulti-Agent SystemsSelf-Learning
Read more
Building SemanticStudio · Part 8 of 8

Production Quality: Evaluation, Observability, and Trust

What separates demos from deployable systems—SemanticStudio's quality evaluation, hallucination detection, and enterprise observability.

January 26, 20267 min read
SemanticStudioQuality EvaluationObservabilityEnterprise AIProduction
Read more
Results as a Service · Part 1 of 2

Results as a Service: Why 2026 Is the Year Outcomes Become the Product

AI agents make outcome delivery feasible. Economic pressure makes it inevitable. Here's what RaaS actually is, where it's already working, and why the shift from 'pay for software' to 'pay for results' changes everything.

January 3, 20267 min read
AI StrategyEnterprise AIBusiness ModelsRaaS
Read more
Results as a Service · Part 2 of 2

RaaS Architecture: The Control Plane That Makes Outcomes Real

RaaS isn't a pricing model—it's the commercialization of an execution loop. Here's what Result Contracts look like, how the Outcome Control Loop works, and what providers and consumers need to make outcome-based models real.

January 3, 202615 min read
AI ArchitectureEnterprise AIAgentsRaaS
Read more

Stochastic Core, Deterministic Shell: The Enterprise Agent Pattern That Holds Up

A lot of agent talk still sounds like old SaaS talk. In production, the pattern that works is simple: the core is stochastic, the shell is deterministic. You don't trust the agent—you bound it.

December 31, 202512 min read
AI ArchitectureEnterprise AIAgentsProduction Systems
Read more
AI-Native Computer · Part 1 of 3

The New Computer Organization: AI Isn't Just an App, It Is the Computer

We're quietly standing up a new computer on top of the old one. In this new computer, LLMs are the CPU, tokens are the bytes, and the context window is the RAM.

December 22, 20257 min read
AI ArchitectureEnterprise AIFuture of Computing
Read more
AI-Native Computer · Part 2 of 3

When AI Is the Front End: The Future of Software and SaaS

If AI is the front end and the LLM is the CPU, what does that do to traditional software? Apps stop being destinations and become capability graphs.

December 22, 20257 min read
AI ArchitectureEnterprise AIFuture of Software
Read more
AI-Native Computer · Part 3 of 3

Architecting the AI-Native Enterprise: A BDAT Playbook

How should a leading organization design for an AI-native future? Using the BDAT lens—Business, Data, Application, Technology—we explore what's next.

December 22, 20259 min read
AI ArchitectureEnterprise AIEnterprise Architecture
Read more

Private AI: The Next Step in Enterprise Intelligence

Why data sovereignty and secure AI architectures are becoming non-negotiable for enterprise AI deployments.

December 10, 20252 min read
AI StrategyEnterpriseSecurity
Read more

Context Engineering: Beyond Window Sizes

How to architect RAG systems that overcome attention dilution and recency bias in large context windows.

December 5, 20253 min read
TechnicalRAGResearch
Read more

Agentic Architecture: Patterns That Scale

Design patterns for multi-agent AI systems that actually work in production environments.

December 1, 20253 min read
TechnicalAI SystemsArchitecture
Read more

Building RAG Systems at Enterprise Scale

Lessons learned from implementing retrieval-augmented generation across hundreds of documents and thousands of users.

November 26, 20252 min read
TechnicalRAGAI Systems
Read more

Data Products: The Foundation AI Needs

Why treating data as a product is essential for AI success, and how to build the data infrastructure that makes AI work.

November 22, 20253 min read
Data StrategyAI StrategyEnterprise
Read more

Superworkers, Not Replacements: The Future of AI at Work

Why the best AI systems amplify human capabilities rather than replace them. A framework for thinking about AI-augmented work.

November 19, 20252 min read
AI PhilosophyFuture of WorkStrategy
Read more

Teaching Machines, Teaching Humans

What 5,000+ students and two decades of AI development have taught me about learning—both artificial and human.

November 16, 20253 min read
TeachingAICareer
Read more

Data Governance in the AI Era

How traditional data governance practices must evolve to support AI initiatives while maintaining trust and compliance.

November 14, 20252 min read
GovernanceData StrategyAI
Read more