Blog
This portfolio is the canonical home for long-form writing. LinkedIn, Medium, and Substack are distribution channels, while the repo keeps every article structured, searchable, and easy to maintain at a high publishing cadence.
Build Logs
Short notes when platforms ship or eval gates wire into CI — the implementation trail behind the portfolio.
SOP corpus RAG, Bitext ChatML SFT, S0–S2 eval compare, TRL training CLI, and live UI.
Decision/signal/limitation on every platform card, 5-minute panel checklist, hire audience toggle.
Enterprise RAG and AegisLoop now fail CI on regression — not just validate fixtures.
Access-aware hybrid RAG with side-by-side strategy comparison on the live platform.
Website deploy tools forced through approval_required policy — runtime intercept before side effects.
16 routed intents, 7 RAG strategies, AegisAI gateway on notify channels.
Repo fix loop never pushes to main; ODAEU harness tunes RAG on eval failure.
Bounded missions, Langfuse spans, mission_gate suite in golden-eval-registry.
Research → drafts → HITL → AegisAI gateway blocks publish until policy allows.
Nine allowlisted sources → snapshot diff → eval gate → gateway email.
5-tab interactive simulator + KV budget calculator — no GPU required.
Dual-judge LLM grading with bring-your-own-key — 139/140 live cases passed.
VAP, RAG, LoopForge, Sentinel, and AegisLoop — production-style auth on live APIs.
Featured Post
Why enterprise agent evaluation must verify the execution path—not only the completed task
Substack
The next enterprise-agent challenge is not discovering agents. It is proving they are qualified, authorized, productive—and still needed.
Substack
From Agent Creation to Trusted Production
Substack
A system that works but cannot explain why it failed is not production-ready
Substack
Agent intelligence is becoming commoditized. Agent reliability is not.
Substack
The next AI advantage may not come from a smarter model. It may come from better enterprise context.
Substack
Supervised autonomy—not autopilot—is the production architecture enterprises need
Substack
Why keeping enterprise data local does not guarantee trustworthy retrieval
Substack
Why enterprise agents need more than traces, dashboards, and token metrics
Substack
A malicious MCP tool can influence an agent even when the tool is never called
Substack
Building AI applications is no longer the hardest problem. Operating AI at enterprise scale is.
Substack
A real AI agent needs more than a prompt. It needs a runtime: identity, memory, state, tools, policies, observability, evals, and human approval. That is how agents become enterprise-ready.
Substack
The agent race is on. The governance layer is not ready.
Substack
A practical framework for scaling enterprise AI across platform teams, product teams, security, compliance, data engineering, MLOps, architecture governance, and business ownership.
Substack
One LLM is a dependency. A model router is an architecture strategy. In this article, I explain how production AI systems can route tasks across OpenAI, Claude, Gemini, Llama, Mistral, and local model
Substack
Memory is not enough for enterprise agents. They need durable state.
Medium
Most AI agents fail not because they cannot reason. They fail because their loops are not bounded, observable, and governed. The current excitement around AI agents is understandable. Agents can plan, use tools, call API
Substack
Most AI agents fail not because they cannot reason. They fail because their loops are not bounded, observable, and governed.
Substack
AI cost is not a finance problem. It is an architecture problem.
Substack
Most AI architecture diagrams look impressive. But production-readiness is hidden in what’s missing.
Substack
Most teams compare RAG and AI Agents as if they are competing patterns.
Medium
Enterprise AI chat is not just a chat window. It is a distributed, event-driven system. That distinction is important. Many teams look at service chat as a simple communication feature. A customer sends a message. A serv
Medium
Salesforce + Agentic AI Reference Architecture: Building an Event-Driven Intelligence Layer for the Enterprise Salesforce AI should not be just a chatbot inside CRM. It should be an event-driven intelligence layer across
Medium
Most AI teams evaluate models. Production AI teams evaluate systems. That distinction is important. In enterprise AI, the final response is rarely produced by a model alone. It is produced by a chain of components workin
Portfolio
Why LangChain is excellent for linear workflows, but LangGraph becomes the better mental model once enterprise AI systems need shared state, branching, and coordinated execution.
Portfolio
A practical architecture for orchestrating specialized AI agents with LangGraph, FastAPI, Next.js, RAG, and observability while keeping the starting cost near zero.
Follow the Writing
Each article should create more than a pageview: it should move readers into the newsletter, the implementation trail, or a hiring/advisory conversation.