the operating layer for an agentic organizationthe agentic operating layer

put your ai agents to work together.

You already have agents: in Salesforce, in Clay, in your support desk, in the models your engineers wired up. Each one is good at its job. None of them can carry a process across teams, systems, and permissions.

macro is the layer between them. Describe how the work should run. macro proposes the agents, the handoffs, the rules, and the approvals, then runs the process reliably, with a record of every step.

A new enterprise lead triggers one macro: Clay researches the account, a pricing agent recommends terms, a person approves any exceptional discount, and an outreach agent sends the campaign. Every handoff is explicit, permissioned, and logged. clay research pricing agent person approves outreach sends research terms if > 10% every handoff: explicit, permissioned, logged trigger · new lead = one macro
fig. 01 · one lead, one process

your agents are capable. the work between them is not.

Nobody is short on agents. The gap is between them.

An agent in your CRM can draft the outreach. An agent in your support desk can diagnose the ticket. An enrichment agent can research the account. Ask any of them to finish the whole job, from the first signal to the closed loop, and it stops at a boundary: a different vendor, a different department, data it is not allowed to see, an action it is not allowed to take.

The usual fix is to hand one agent broad credentials. That is unsafe, and hard to audit. The other fix is to have engineers wire the agents together, which turns a business decision into protocols, schemas, queues, retries, identity, and policy. So most companies end up with scattered pilots that each do a narrow task well, and no process that runs end to end.

where the work stops

at the vendor

The Clay agent cannot see what the Salesforce agent knows.

at the department

Sales, legal, and finance each own a piece. No one owns the loop.

at the data

Customer PII cannot go to an outside model, so the handoff never happens.

at the permission

The research agent may read the account but must never touch the opportunity.

at the approval

Above a threshold a person has to say yes. Nobody built the place to ask.

at the translation

The operator knows the rule. Turning it into code takes a sprint.

Companies want agents to do more on their own. The more systems, teams, money, and customer data an agent touches, the more dangerous ungoverned autonomy becomes. the core tension

a macro is a business process your agents can run.

The first-class object is the macro, not the agent.

A macro says what starts the process, which agents and people take part, what context each one gets, what each is allowed to do, when a human has to approve, what happens when a step fails, and what a good outcome looks like. Underneath, a durable runtime executes it. On top, a plain-language product lets the people who own the process define it and change it.

fig. 02 · the shape of a macro
trigger agent or tool condition context handoff agent approval action outcome

With retries, timeouts, fallbacks, budgets, permissions, and an audit trail attached. Versioned, so you can see what changed and roll it back.

01
square · structure

describe the outcome

“Investigate churn risk and create a retention plan.” “Qualify every enterprise lead before a rep sees it.” Say it the way you would say it to a new hire.

02
triangle · direction

macro proposes the process

macro looks at the agents and systems you have connected and suggests a macro: the trigger, the participants, the handoffs, the approvals, and the expected outcome, explained in plain English. You edit it like a document, not like a pipeline.

03
circle · wholeness

run it, with the rules attached

Start in shadow mode, where macro shows what it would have done. Grant action authority one step at a time. Every run leaves a record: what happened, why, who authorized it, what it cost, and whether the objective was met.

The agents can come from Clay, Salesforce, Sierra, OpenAI, Microsoft, ServiceNow, your own team, or a small worker macro creates to fill a gap. macro does not need to outperform any of them. It makes their work together coherent, safe, and reliable.

every action has an owner, a limit, and a record.

Workflow is necessary. Delegated authority is what lets you turn autonomy up.

Most tools decide whether a step ran. macro decides whether it was allowed to. Before any consequential action, macro checks who is acting, on whose behalf, in what business context, against which policy and which limits. The answer is one of four.

fig. 03 · the authority equation
agent identity sponsor business context requested action policy & limits allowed denied redacted ask a person

The sponsor is the person or team the agent acts for. Authority is delegated, never assumed.

what that looks like, written down

pricingThe pricing agent may approve discounts up to 10%. Between 10 and 20%, ask the CRO. Above 20%, no.
supportThe support agent may issue refunds up to $500 for accounts in good standing.
dataThe Clay agent may enrich public account data. It never receives customer PII.
crmThe research agent may read these CRM fields. It may not edit an opportunity.
legalThe legal agent gets the contract and the deal terms. Not the customer’s other notes.
financeAsk Finance before any credit above $5,000.

Rules are written the way you would say them. macro turns them into policy, and shows security and technical owners exactly what it produced.

describe how the business should run. macro does the plumbing.

Business friendliness is the architecture, not a coat of paint.

what you do
  • describe the objective
  • choose a template
  • set the rules, in plain language
  • approve the exceptions
  • inspect the outcomes
  • make the process better
what you never have to touch
  • MCP and A2A
  • worker queues and retries
  • schemas and data mapping
  • model routing
  • OAuth scopes
  • a distributed runtime of your own

Technical admins connect systems and manage reliability. Security teams define data classes, permissions, and audit requirements. Executives see outcomes, autonomy gained, risk controls, and where the human bottlenecks still are. Everyone looks at the same macro, at the depth their job needs.

built for the company that already has agents.

The best first customer is not “interested in AI.” It has several agents, one painful cross-functional process, and someone accountable for it.

revops and sales leaders

Clay, the CRM, support, content, analytics, and internal agents that do not share process state.

customer experience leaders

A support agent that can diagnose the issue but cannot safely coordinate CRM, billing, risk, and retention.

ai-forward enterprises

Dozens of agents, siloed, inconsistently governed, and hard to measure.

regulated and data-sensitive teams

Autonomy blocked by data boundaries, unclear authority, and audit requirements.

turn isolated agents into a process that runs.

Bring the agents and systems you already have. Leave with one macro running in shadow mode and a plan for turning it on.