Platform & Operations
Fix MCP OAuth 401 and 403 Errors
Diagnose MCP OAuth failures with a local lab: missing or expired tokens, wrong audiences, insufficient scopes, discovery problems, and issuer mismatches.
Platform & Operations
Platform & Operations
MCP servers, workflows, observability, and the control-plane engineering behind it.
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MCP Security: The Complete Guide to Securing MCP Servers
MCP security and MCP server governance: the MCP threat model, authentication, tool-level authorization, rate limits, logging and a hardening checklist.
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Platform & Operations
Portkey Alternatives: Choosing an AI Gateway
Portkey's managed AI gateway category explained, the evaluation criteria that separate gateway options, and when a governance layer is what you actually need.
Platform & Operations
MCP 2026-07-28: What Changed in the Ratified Spec
The ratified MCP 2026-07-28 spec drops session state for a stateless core, adds MRTR and CIMD, and formalizes Tasks, MCP Apps, and EMA as extensions.
Platform & Operations
OpenTelemetry GenAI Semantic Conventions: What's Stable
As of mid-2026, no gen_ai.* OpenTelemetry attribute is stable — what moved, what that means for teams instrumenting agents now.
Platform & Operations
LLM Observability Tools for Security and Compliance Teams
Langfuse, LangSmith, Arize Phoenix, and Braintrust evaluated for audit-trail and compliance readiness — not eval quality.
Platform & Operations
MCP STDIO RCE Vulnerability Wave (2026) Explained
OX Security's April 2026 disclosure found a design-level flaw in Anthropic's MCP SDKs enabling remote code execution via STDIO transport.
Platform & Operations
LiteLLM Enterprise Alternatives: Beyond Self-Hosting
When LiteLLM's self-hosted model stops scaling and what teams evaluate instead — Portkey, Kong AI Gateway, Cloudflare AI Gateway, and TrueFoundry.
Platform & Operations
Agent Evaluations: Catching Quality Regressions Early
Agents regress silently when prompts, models, tools, or data change. How to build an eval harness: scoring methods, what to measure, where evals belong.
Platform & Operations
LLM Gateway Comparison 2026: Security and Governance
Portkey, LiteLLM, Kong AI Gateway, and Cloudflare AI Gateway compared for routing, spend control, and security — how to shortlist for your team.
Platform & Operations
Agent Topology Maps: Seeing the Dependency Graph
An agent estate is a graph of agents, tools, data sources, and models. What a topology map should show, what it answers that a list cannot, how to keep it true.
Platform & Operations
High Availability for an AI Control Plane
A control plane in the request path is a dependency for every agent call. Which parts must fail closed, which can degrade, and how to plan each failure mode.
Platform & Operations
Post-Incident Forensics for AI Agents
Reconstructing what an AI agent did, why, and what it touched needs evidence most deployments never record. The minimum record set and how to investigate.
Platform & Operations
MCP Server Registries: Publishing, Discovery, and Ratings
An MCP server registry is a supply-chain control point. What a registry entry should carry, how ratings get gamed, and why internal catalogues beat public ones.
Platform & Operations
Detecting Shadow MCP Servers
Developers add MCP servers to agents in minutes, without review. How to detect shadow MCP servers already running and make the governed path the easier one.
Platform & Operations
Publishing Agents to a Marketplace: The Review Gate
A marketplace where publishers approve their own listings has no review at all. The listing lifecycle, why self-certification must be impossible, what to check.
Platform & Operations
MCP OAuth 2.1 and PKCE, Explained Step by Step
The MCP 2026 authorization flow: discover metadata, choose CIMD or registered clients, use PKCE, validate the issuer, and request resource-bound tokens.
Platform & Operations
MCP Server Vetting: Registry Risk and How to Manage It
Third-party MCP servers are supply-chain risk: registry provenance, tool-description audits, version pinning, and an approval workflow that scales.
Platform & Operations
MCP Gateway Comparison 2026: Options and Trade-offs
MCP gateway options compared as of October 2026: open-source gateways, API-gateway extensions and governance control planes, and what to look for.
Platform & Operations
Evaluating AI Agent Observability Tooling
A practical guide to what AI agent observability must cover — cost, behavior, and policy compliance — and the key criteria for choosing the right tooling.
Platform & Operations
Guardrail Nodes: Inline Policy in Agent Workflows
A guardrail node in a workflow graph makes policy visible where it applies. What these nodes should do, the silent no-op to avoid, and connection enforcement.
Platform & Operations
Agent Task Marketplaces and Escrow
When agents post and accept paid work across organizations, payment becomes a security surface. The task lifecycle, where escrow protects each side, the leaks.
Platform & Operations
Building Golden Datasets for Agent Evals
The dataset, not the harness, is the hard part of agent evals. How to source golden set cases, set expectations for non-deterministic agents, and version them.
Platform & Operations
Webhook Security: Signing and Verifying Events
HMAC signatures plus timestamp replay windows are the minimum bar for secure webhooks — here's why unsigned endpoints are dangerous and how to fix them.
Platform & Operations
OTLP Telemetry Ingest for Agent Discovery
You cannot govern agents you do not know about. OTLP telemetry ingest turns existing instrumentation into an agent inventory. What the ingest path has to solve.
Platform & Operations
Versioning and Rollback for AI Agents
Version AI agent workflows like code, diff changes between snapshots, and roll back safely when a new version causes regressions or runaway costs in production.
Platform & Operations
Dead-Letter Queues for Failed Agent Jobs
A dead-letter queue nobody watches is where work gets forgotten. What belongs in a DLQ, how to alert on it, and how to replay safely once the cause is fixed.
Platform & Operations
Threat Model: Over-Broad MCP Tool Scope
Over-broad MCP tool permissions give attackers an amplified attack surface. Learn the failure modes and control classes that shrink the blast radius.
Platform & Operations
Benchmarking Agents: What Public Numbers Can and Can't Show
Public agent benchmarks help narrow a shortlist but mislead as a selection criterion. What they measure, how contamination distorts them, how to test your own.
Platform & Operations
Retries and Idempotency in Agent Workflows
At-least-once delivery plus agents that take real actions means duplicate side effects. Where idempotency keys belong, why retries multiply cost, safe replay.
Platform & Operations
Langfuse Alternatives: Tracing, Evals and Governance
Langfuse's open-source LLM engineering category explained — tracing, evals, and prompt management — and where governance requirements go further.
Platform & Operations
Kong AI Gateway Alternatives for Agent Traffic
Kong AI Gateway's platform-extension model explained, how it handles agent and LLM traffic, and when a dedicated governance layer is the better fit.
Platform & Operations
Helicone Alternatives for LLM Observability
Helicone's open-source LLM observability category explained, what it covers, and how to evaluate alternatives for cost tracking and tracing.
Platform & Operations
How to Rate-Limit AI Agents
Design abuse-resistant rate limits for AI agents: choose the right unit, window shape, and enforcement scope to protect costs and downstream systems.
Platform & Operations
Cloudflare AI Gateway Alternatives
Cloudflare AI Gateway's edge-native model explained, when it fits, and how self-hosted, platform-extension, and governance alternatives compare.
Platform & Operations
Arize Phoenix Alternatives for LLM Evaluation
Arize Phoenix's open-source evaluation and tracing category explained, and how it differs from runtime policy enforcement for production agents.
Platform & Operations
How to Monitor MCP Tool Calls
Gain full visibility into every MCP tool call an AI agent makes — with attribution, policy decisions, and cost data needed for security and compliance.
Platform & Operations
Orchestration Patterns for Multi-Agent Systems
Compare pipeline, hub-and-spoke, and blackboard orchestration patterns for multi-agent AI — with security, cost, and auditability trade-offs for each.
Platform & Operations
Observability for AI Agents: Logs, Metrics, and Traces
How logs, metrics, and distributed traces apply to AI agents—what to instrument, where costs hide, and how to connect all three for fast incident triage.
Platform & Operations
AI API Abuse Prevention: Why Rate Limits Are Not Enough
Request counts alone do not stop abuse of AI APIs. The layered controls that do: per-connection limits, spend caps, tool allow-lists and trust gates.
Platform & Operations
MCP Server Authentication: OAuth 2.1 vs API Keys
OAuth 2.1 vs API keys for MCP servers after the Nov 2025 spec: PKCE, RFC 8707 resource indicators, token lifetimes, revocation, and when each fits.
Platform & Operations
Scoping MCP Tool Permissions: Least Privilege for Tools
Grant AI agents the minimum MCP tool access they need — no more. Learn how allow-lists, per-tool rate limits, and policy gates prevent blast-radius breaches.
Platform & Operations
MCP Server Security Checklist (OWASP-Mapped)
An MCP server security checklist in seven domains, from authentication and tool permissions to tool poisoning and logging, mapped to the OWASP MCP Top 10.
Platform & Operations
What Is the Model Context Protocol (MCP)? A Practical Guide
MCP gives AI agents a standard way to call external tools and retrieve context. Learn what it is, how it works, and the security controls it needs.
Platform & Operations
API-First: The Praesidia API Surface
Every platform action is an API call. Learn how Praesidia's OpenAPI-described surface lets you automate governance, integrate tooling, and extend the platform.
Platform & Operations
Platform Operator Access: What Praesidia Staff Can Do
How Praesidia's platform operators are kept apart from your organization's roles, which changes take two of them, and what they leave in your audit trail.
Platform & Operations
Real-Time Events over WebSocket
A persistent, authenticated WebSocket stream replaces polling for agent tasks, workflow runs, and budget alerts — and what safe multi-tenant fan-out requires.
Platform & Operations
Health Probes and Readiness for AI Infrastructure
How to design liveness and readiness probes for AI services — what to check, how to avoid false positives, and what a production health surface looks like.
Platform & Operations
Webhooks and SIEM Forwarding
Stream AI agent events to your own systems and forward security signals to a SIEM — so agent activity is visible in the tooling your team already uses.
Platform & Operations
What Is Tool Poisoning in MCP?
Tool poisoning hides malicious instructions inside an MCP tool's description or schema, manipulating agent reasoning without touching user-facing traffic.
Platform & Operations
Closing the Loop with a Product Feedback Board
Turn scattered user requests into ranked roadmap signal with a built-in feedback board that supports voting, moderation, and visibility across organizations.
Platform & Operations
Slack and Multi-Channel Alerting
Route AI agent budget alerts, guardrail violations, and task failures to Slack and other channels with a reliable, tenant-isolated dispatcher pattern.
Platform & Operations
How to Measure AI Agent Governance Effectiveness
The leading and lagging indicators that show whether an AI agent governance program is actually working, and how to avoid vanity metrics.
Platform & Operations
How to Build an AI Agent Onboarding Process
A numbered onboarding procedure for AI agents, with an owner and evidence artefact at each step, from request intake to monitoring activation.
Platform & Operations
Unsubscribe, Suppression, and Preference Centers
Build a compliant email opt-out system with enforced suppression lists, per-category preferences, and bounce handling that protects your sender reputation.
Platform & Operations
AI Agent Governance for Platform Engineers
What platform engineers own when AI agents run in production: identity issuance, policy enforcement, guardrail wiring, and the artefacts to prove it works.
Platform & Operations
Transactional Email and Templates
Reliable transactional email for AI platforms: how consistent templates, authenticated sending, and delivery safeguards keep security and billing flows intact.
Platform & Operations
Writing Runbooks for AI Agent On-Call
AI agent on-call runbooks need decision trees for runaway spend, guardrail bypass, and stuck queues, not just restart-the-service steps.
Platform & Operations
Web Push Alerts for AI Operations
Browser push notifications deliver agent failures and budget alerts to operators the moment they happen — no open tab or email check required.
Platform & Operations
Multi-Region Failover for AI Agent Workloads
Multi-region failover for AI agents means deciding what fails over and what must stay pinned — control plane logic differs from tenant data. A practical design.
Platform & Operations
Golden Signals for Agent Services
The four golden signals — latency, traffic, errors, saturation — need a fifth for agent services: task outcome quality, since correct output is a distribution.
Platform & Operations
In-App Notifications That Cut Through
How a purpose-built in-app notification system keeps AI platform operators informed of critical agent events and alerts without noise or alert fatigue.
Platform & Operations
Disaster Recovery for an AI Control Plane
Disaster recovery for an AI control plane means restoring policy, audit chain, and credentials from backup, distinct from live regional failover.
Platform & Operations
Chaos Engineering for Agent Systems
Chaos engineering for agent systems means injecting tool, provider, and guardrail failures deliberately, before an incident does it for you.
Platform & Operations
Auth Monitoring and Login Security
How to capture, aggregate, and act on authentication events in your AI platform so credential attacks surface in minutes, not days.
Platform & Operations
Capacity Planning for AI Agent Fleets
Capacity planning for agent fleets means forecasting token budgets and provider rate-limit headroom, not CPU or memory. A method for doing it right.
Platform & Operations
Visualizing AI Usage and Cost
Charts, dashboards, and cost breakdowns that make AI agent spend legible — from real-time KPIs to anomaly detection and per-team attribution.
Platform & Operations
Canary Releases for Agent Prompts and Instructions
Canary releases for agent prompts route a small share of traffic to a new prompt version and promote on eval score and task success, not just error rate.
Platform & Operations
Blue-Green Deployment for Agent Policies
Blue-green deployment for agent policies means running old and new guardrail and permission bundles side by side, with an instant cutover and instant rollback.
Platform & Operations
Prometheus Metrics and Observability
Praesidia exposes a standard Prometheus metrics endpoint so you can monitor AI agent task throughput, latency, and spend using the tools your team already runs.
Platform & Operations
Beating Alert Fatigue in Agent Monitoring
Alert fatigue in agent monitoring comes from thresholds built for deterministic services. Tune thresholds to your own measured variance instead.
Platform & Operations
Global Search Across Your AI Estate
Search across agents, tasks, connections, workflows, and audit logs from a single entry point — find any resource in your AI estate instantly.
Platform & Operations
Saved Views for Faster Operations
Saved views let AI operations teams restore any dashboard state in one click — cutting investigation setup time and reducing filter errors under pressure.
Platform & Operations
Service Level Objectives for AI Services
Set measurable SLOs for task success rate, latency, and agent availability — then alert before users notice. A practical guide for AI agent deployments.
Platform & Operations
Executive Reports for AI Governance
Turn AI activity into board-ready governance reports covering usage, cost, and risk — with scheduled delivery and export for compliance teams.
Platform & Operations
The Operations Dashboard for Your AI Estate
How an AI operations dashboard correlates agent counts, spend, trust scores, and security events in one view — and what to do when the numbers look wrong.
Platform & Operations
Advanced Analytics for AI Operations
Go beyond basic dashboards: model comparison, cost-per-team allocation, anomaly detection, and compliance analytics for AI operations teams.
Platform & Operations
Analytics and the Event Stream
How a per-interaction event model powers AI agent dashboards, cost attribution, and forensic investigation — without additional collection infrastructure.
Platform & Operations
Per-Org Feature Overrides and Canary Rollouts
Per-org feature overrides let you enable a capability for one tenant, observe real behavior, and expand gradually — without touching your deployment pipeline.
Platform & Operations
Plan Gating and Feature Flags
Plan-based feature flags gate capabilities by subscription tier while per-org overrides enable safe canary rollouts — no deployment pipeline changes required.
Platform & Operations
Real-Time Collaborative Workflow Editing
How real-time collaboration on AI workflow canvases works: CRDTs for conflict-free edits, durable working documents, presence, and per-edit authorization.
Platform & Operations
Bring Your Own Key: Managing LLM Configurations
Register your own LLM provider keys in one encrypted registry, route workloads to the right model, and eliminate key sprawl — without platform lock-in.
Platform & Operations
Reusable Workflow Templates
Workflow templates let teams deploy proven agent pipeline patterns in one click — spreading best practices and simplifying governance across the organization.
Platform & Operations
Chat-to-Build: Generating Workflows with AI
Turn a plain-language description into a reviewable multi-agent workflow draft in seconds. Learn how AI generation works and where human review stays essential.
Platform & Operations
Triggering Workflows: Scheduled, Webhook, and Event
The three ways to start an AI workflow—cron schedules, signed webhooks, and platform events—and which trigger fits each operational pattern.
Platform & Operations
Executing and Monitoring Workflow Runs
How workflow runs execute node-by-node, how per-run spend caps prevent cost overruns, and how to observe, pause, cancel, and retry runs in real time.
Platform & Operations
Designing AI Workflows on a Visual Canvas
A node-and-edge visual canvas lets you compose, version, and audit multi-step AI agent workflows before anything runs — catching gaps that code reviews miss.
Platform & Operations
Managing API Consumers with Applications
Register every API consumer as a named Application with scoped credentials and per-agent access controls — so you can see and revoke what each can do.