Blog
Practical guides on AI agent governance, the Agentic Gateway, and building production-ready agent infrastructure.
5-Minute LangChain Observability: Cost, Latency, and Policy Without Rewriting a Line
Your LangChain agent is a black box in production. Here's how to get cost per run, full trace history, and policy enforcement by changing one environment variable: no SDK swap, no code rewrite.
Why CrewAI Agents Need an External Control Plane
CrewAI builds the crew. It does not answer for the fleet. What breaks past the first crew, what connecting actually involves, and when you genuinely do not need this.
Prompt Injection: Where Pattern Matching Fails
Pattern matching catches the scripted attacks and misses the novel ones. What runs before the model, and how to answer the question in a vendor risk pack.
Connect Google ADK Agents to Dobby: MCP, A2A, and Webhook Integration (3 Paths)
Integrate agents built with Google's Agent Development Kit (ADK) via MCP, A2A, or webhooks. Monitoring, approval gates, and per-agent cost tracking: with working code examples.
Per-Agent LLM Cost Attribution: Who Spent What
Aggregate model spend tells you the bill, not the cause. How per-agent, per-team attribution works, and what a reviewer asks about it in a vendor review.
Managing CrewAI, n8n and Custom Agents in One Place
Scheduling, webhook triggers, approval gates and audit trails for agents that already run on CrewAI, n8n, Make or your own Python. No agent code changes.
AI Agent Control Plane: The Layer That Has to Answer for the Fleet
Kubernetes gave containers a control plane. Agents need the equivalent, but the job is answering for what the fleet did, to someone outside the company. What that layer owes, and what to ask when evaluating one.
Cost Control for AI Agents: Three Layers and What Each One Misses
Budgets, provider quotas and model restrictions each stop a different failure, and none of them stops the first overage. What the three layers do, where they end, and what a vendor-risk reviewer asks about them.
Connect Your First AI Agent to Dobby
Create a workspace, pick a region, connect an agent, and see its runs land. What the connection actually involves, and what you get once it does.
AI Agent Governance: The Four Controls a Vendor Review Asks You to Evidence
Policy, a halt, an audit trail and approval gates. What each control is, what record it has to leave behind, and why the record is the part that fails a review.
Per-Tenant Gateway Profiles for Multi-Tenant AI Policy
One gateway, 50 tenants with different policies? Per-tenant gateway profiles give each tenant its own budget, models, and DLP via a 5-layer merge.
Data Handling: What Leaves, Where It Goes, Who Reads It
The data-handling cluster of a vendor questionnaire is answered by configuration a reviewer can check, not by a promise. Two scan layers, three actions, one invariant.
Change Management for AI: Proving What Was Live
A reviewer will ask which version served a decision last quarter. Prompt changes ship outside the release process, which is why that question is hard to answer.
The Halt: Article 14's Hardest Requirement to Build
EU AI Act Article 14 requires the ability to interrupt or stop the system. Three scopes, why the read must fail closed, and what a halt has to record to count.
Non-Human Identity: The Access Review Nobody Runs
Quarterly access reviews enumerate people. An autonomous agent holds delegated permissions and appears on no list: which is the finding, not the footnote.
EU AI Act Article 14: Five Oversight Patterns
Article 14 asks for oversight a person can actually exercise. Five patterns that satisfy it, and what each leaves behind when a reviewer asks for proof.
Manage CrewAI, LangChain, and OpenAI Agents from One Dashboard
Your team uses CrewAI for orchestration, LangChain for RAG, and OpenAI Assistants for customer flows. Unified management, monitoring, and cost tracking: from one dashboard, across the frameworks your team already uses.
MCP Protocol Explained: How AI Agents Call Real Tools and APIs (JSON-RPC)
The Model Context Protocol (MCP) gives AI agents structured access to tools and APIs via JSON-RPC. What it is, how it works, and why Anthropic, Claude, Cursor, and ChatGPT all speak it.
Agentic Gateway Explained: Auth, Cost Tracking, and Policy for Every LLM Call
The agentic gateway is a unified proxy that authenticates, meters, and enforces governance on every LLM and MCP request. Why every AI platform needs one, and how to build it.