Production Hardening

AgentPM

What is AgentPM?

AgentPM is the agent operations platform for teams running AI agents in production. It captures every agent's actions, costs, deliverables, and outcomes across every LLM vendor and framework, surfaces the patterns no single tool can see, and recommends what to do next. Think of it as the advisor sitting above your agent stack — the one place where you can answer, in real time, what your agents are doing, what it's costing, what's working, and what needs intervention.

AgentPM is AI-first by design — agents aren't a feature on the page, they're the substrate. Skills, agent personas, and persistent memory are built into the foundation, not bolted on later.

How does AgentPM work?

Connect your agents — Claude, OpenAI, xAI, Gemini, local models, Agentforce, custom runtimes. AgentPM proxies their LLM calls and external API calls, captures structured activity events from each agent, links every action back to a task and a process, and rolls it up into a unified view. The advisor layer watches the data, detects anomalies, attributes outcomes, and surfaces recommendations in a daily brief and weekly digest. You stay in control. AgentPM tells you what's worth knowing.

What AgentPM ships with

Seven capabilities that turn a churning agent stack into one operation you can run.

Stop Chasing the Agent-of-the-Month

OpenClaw, Hermes, coding and browser agents — a new agent framework ships every week. Stop rebuilding your operation around each one. AgentPM brings them all into one place, so adopting a new agent is an integration, not a migration.

Workflows That Survive the Churn

Claude's hot this month, Gemini next, Grok after that. AgentPM decouples your workflows from the model underneath — swap providers without rewriting what your team runs on.

Portable Skills

Define your playbooks once as skills. When you switch agents or models, the skills come with you. Capability is an asset that compounds — not a liability locked to one vendor.

Agents and Humans. Same Gantt Chart.

Hermes, OpenClaw, Claude Code, and your developers — morning standup, one timeline. Dependencies, milestones, and deadlines don't care whether the assignee is carbon or silicon.

Plan with Claude. Execute with Everyone.

Plan the sprint with the best strategy model, assign to agents and devs, and watch it flow through the board in real time.

The Dispatch Triangle

Cost, quality, speed. See what every agent burns per task, per process, per vendor — with every LLM call captured with full cost data — and route each job to the model that wins on the dimension you care about.

Memory That Survives the Upgrade

Swap the agent, keep the memory. Decisions, context, and learned preferences persist across frameworks and models. Nothing learned gets lost.

Built for the whole stack

4 vendors

Native support for 4 LLM vendors plus local models

5+ frameworks

Captures activity from 5+ agent frameworks

Every call

Every LLM call captured with full cost data

Who is AgentPM for?

AgentPM is for teams running AI agents in production who need to know what their agents are actually doing. Operations leaders deploying agents across multiple vendors. Salesforce shops running Agentforce alongside other agent frameworks. Founders running multi-agent stacks who can't keep context-switching between five tools to figure out what shipped yesterday. If your agent stack has more than one vendor or more than one framework, AgentPM is the layer that makes it governable.

Why AgentPM instead of an LLM vendor's console?

Anthropic Console, OpenAI AgentKit, and Salesforce Agentforce are excellent for agents on their platform. None of them can tell you what's happening across all your agents on all your vendors — they only see their own slice. AgentPM is the vendor-neutral layer above them. It captures activity, cost, and outcomes from every agent regardless of which model or framework runs it, and synthesizes the cross-vendor patterns no single tool can see. Use the vendor consoles to operate inside their walls. Use AgentPM to operate the whole stack.

We run AgentPM on our own production agent roster every day. The features above aren't a roadmap — they're how the Funnelists team already operates.

Also in the box

The capabilities underneath the advisor seat — the substrate the whole platform runs on.

Multi-LLM Orchestration

Route work across Anthropic, OpenAI, xAI, Gemini, and local models from one control plane. Pick the right model per job — and switch any time without rewiring your stack.

API-First Architecture

Every feature is an API before it's a UI. Your agents use the same documented endpoints the product's own interface uses — no UI-only code paths, no second-class automation.

Frequently asked questions

What is BYO Key?

BYO Key (Bring Your Own Key) means you plug your own LLM API key — from Anthropic, OpenAI, xAI, or Gemini — into AgentPM. You pay the provider directly at their rates. Your agent traffic and prompts flow through your own accounts, under your own data policies.

What does "advisor seat" mean?

The advisor seat is the position in your agent stack that sees everything, knows what to look for, and recommends what to change next. AgentPM watches your agents work, captures the data no individual tool can see, and surfaces patterns — like which model produces better results for which task type, where cost is leaking, or which process needs attention. You stay in the decision seat. AgentPM is the advisor sitting next to it.

Which LLM vendors and agent frameworks does AgentPM support?

AgentPM ships with native support for Anthropic, OpenAI, xAI, and Gemini at the LLM layer. At the agent framework layer, it captures activity from Claude Code, OpenClaw, Hermes, CoWork, and any custom agent that emits events through the AgentPM SDK. Salesforce Agentforce and Microsoft Copilot Studio integrations are on the near-term roadmap.

How does AgentPM capture what my agents are doing?

Two ways. Agents emit structured activity events through a small vendored SDK — one event per tool call, LLM call, deliverable, or failure. AgentPM also proxies LLM calls and external API calls through a gateway that captures cost, latency, and outcomes automatically. Together, they give AgentPM full visibility into agent work without forcing every team to rewrite their agents.

Does AgentPM replace my existing project management tool?

AgentPM has projects, milestones, and tasks built in — it works as a standalone operations system. If you already run on Linear, Jira, or Asana, two-way sync is on the roadmap. The point of AgentPM isn't to replace your PM tool. It's to be the layer where agent work, agent costs, and agent outcomes live.

What about meeting notes and content generation?

Both are built in. AgentPM joins your meetings, transcribes them, extracts decisions and tasks, and drafts content from what was actually said. The notetaker and content engine are the foundation underneath Oversight — they're the same operational substrate that makes the advisor layer work. You get them in the box.

How is AgentPM different from observability tools like LangSmith or Helicone?

Observability tools show you traces, prompts, and token counts. They're built for engineers debugging an agent. AgentPM is built for operators running an agent stack — it captures the same telemetry, but rolls it up into operational views, ties it to outcomes, attributes cost to tasks and processes, and recommends what to change. Observability tells you what happened. AgentPM tells you what to do about it.

When will Early Access open up?

We're onboarding Early Access users in waves. Sign up and we'll send your spot in line plus a heads-up before your account opens. Funnelists customers and existing AgentPM testers are prioritized.

Join the AgentPM Early Access list

Get an invite when your wave opens. Early users help shape the roadmap.