Partner programs that produce revenue, not just partner counts.

I'm Tony Gilharry. I build the partner operating system that turns signed partners into revenue, at Fortune 100, midsize, and startup scale. Yours will be custom, so what follows is how I'd build it, not a highlight reel.

Talk to Tony See how I'd build it ↓

$30M+partner-influenced revenue supported

Focus: Partner programs · Revenue operations
Scale: Enterprise · Midsize · Startup #39
Based: Remote, US

Your build will be custom. Here's how I think about it.

The director and senior-manager roles hiring right now are all solving the same handful of problems, at different levels of scale. So what follows isn't a highlight reel from another company. It's how I'd work through each part of the build, with the receipts that I've done it before.

Build itThe data model, the program, the economics underneath.
Run itTrusted numbers, a steady cadence, AI-native leverage.
Teach itPartners and the field selling and delivering without you.

Build it

Design the system before you run it. The data model, the program, and the economics underneath decide what everything above them can ever do.

The operating system & data layer

Most partner motions break in the same place: the data was never modeled for the questions leadership eventually asks. By then the reporting is a patch over a foundation that can't answer them.

How I'd build it

Start from the decisions the business needs to make, then model backward to the partner object and its relationships.
Set deal-registration rules, SLAs, and conflict resolution with direct sellers before the first workflow.
Fix the attribution logic before the dashboards, so every number traces to a rule instead of a guess.
Specify what Systems builds and own the logic; I write requirements precise enough to hand off.

The baryou can specify what needs to be built, not just describe the problem.

Root-caused a failing 8-platform integration by replaying the API calls, and delivered the $375K audit a month early.

Partner Account

relTechnology Stack
relCapabilities
relCertifications
relCustomer Segments
relBusiness Model
relPartner Intelligence

One account, six related records, so the data answers real questions.

The program & its economics

Most programs pay for activity. Partners collect benefits for showing up, and the behavior the company actually needs never gets funded.

How I'd build it

Name the behavior worth paying for first, then design tiering with thresholds that gate on it.
Wire benefits, requirements, MDF, and rebates so the incentive and the goal point the same way.
Model the effect on the P&L and on partner behavior before launch, not after.
Keep the rules simple enough that the field and the partner can both explain them.

The barthe program pays for the behavior you want, and you can prove it does.

Built a program from zero as first hire, and grew it from 450 to 2,000 agencies and 40% of company ARR.

Each tier earns what the tier above pays for in behavior.

Meet partners where they're strongest

A reseller, an ISV, an SI, and an MSP go to market in completely different ways. Most programs still make all of them earn recognition on the same terms, so no one gets rewarded for what they are actually good at.

How I'd build it

Sort partners by how they go to market: sell, build, deliver, or manage.
Recognize and enable each track for its own strength, not one tier for everyone.
Let a partner hold more than one track, and move between them as it grows.
Route each track to the resources, programs, and benefits that fit how it works.

The barevery partner is recognized and enabled for what it is actually good at.

Framework credit: Pablo Hanono, Books of the Channel, from Partner Ecosystems Fundamentals. What I bring is the conviction to design the tiers and enablement around it, so partners are met where they are strongest.

SellResell or influence salesVARs · resellers · agents · VADs

BuildCreate apps, integrations, IPISVs · OEMs · developers · tech partners

DeliverImplement, deploy, configureSIs · consultants · agencies

ManageOperate, optimize, run itMSPs · operators · lifecycle firms

Partners engage by how they go to market, and evolve across tracks as they grow.

Run it

A program you can't measure is a program you can't defend. Running it means trusted numbers, a steady cadence, and enough leverage to do it without a big team.

The measurement layer

Leadership rarely agrees on what a partner-sourced dollar is, so no one fully trusts the number. The partner team spends the QBR defending arithmetic instead of making decisions.

How I'd build it

Settle the definitions first: sourced, influenced, and certified delivery capacity, in writing.
Instrument those definitions so the report is a read of the system, not a monthly rebuild.
Show where capacity is thin, not just where revenue landed.
Bring Finance and the field into the definitions early, so the number survives contact with both.

The barnumbers you can defend to Finance and the field, not just produce.

Supported $30M+ in partner-influenced revenue, and $7.7M annualized from 553 proposals.

North-star

Partner Revenue Growth

Revenue streams

Partner-Sourced Revenue

Partner-Influenced Revenue

Services / Attach

Partner-sourced decomposes into

Active Partners

Revenue / Active Partner

Operating inputs

Recruited PartnersQualified PartnersActivated PartnersTime to ActivationCertification RateDeal RegistrationPartner Pipeline

Every operating metric traces up to one number. Fix the input, move the top.

AI-native operations

The roles hiring now expect AI fluency and clean schemas an agent can use. Most partner operations were never built for that, so AI gets bolted on and quietly trusted too much.

How I'd build it

Get the data governed first; an agent is only as good as the schema underneath it.
Build a pipeline that turns a partner call into a governed Salesforce record, human-validated.
Keep a decision log of what AI may and may not touch, so leverage never costs you trust.
Use AI to let one operator do the work of several, and check it where judgment matters.

The barAI raises leverage without eroding the numbers you just made defensible.

Synthetic dataA current build, on synthetic data, that a hiring manager can inspect rather than take on faith.

Date	Decision	DRI	Approver	Rationale	Impact
Oct 4	Salesforce remains the authoritative partner system	Partner Ops	VP Partnerships	Reduces duplicate master data	Architecture
Oct 8	Technology stack modeled as related records	Partner Ops	RevOps	Partners have multiple technologies	Data
Oct 11	AI does not overwrite strategic fields without validation	Partner Ops	IT / Partnerships	Governance requirement	AI

What AI may and may not touch, on the record.

Teach it

The best partner program runs when you leave the room. Teaching it means partners and the field can sell and deliver without you standing behind them.

Signed to productive

Companies sign partners faster than they can activate them. Signed looks like progress; producing is the thing that was actually promised.

How I'd build it

Map the real path from signed to first deal, and find where the time actually goes.
Treat onboarding as a product with owners and SLAs, not a welcome email and a checklist.
Set the readiness bar that lets a partner deliver competently without us in the room.
Run the long tail directly, and hand strategic partners the same framework.

The bara partner can deliver well without you present.

Rebuilt onboarding and cut time-to-first-referral from 60 to 25 days, and set the readiness bar for 600+ partners.

Onboarding rebuilt as a product: the same path, half the time.

Field & partner enablement

Partners and the field can't sell what they can't run. Enablement gets measured by content shipped and courses completed, not by whether anyone is actually ready.

How I'd build it

Build role-based paths for execs, sellers, SEs, and delivery, not one deck for everyone.
Make certification mean something: tie it to what a partner must prove, then measure readiness.
Give the field co-sell plays and account-mapping they will actually use in a live deal.
Close the loop with win/loss and field usage, and cut what no one opens.

The barenablement measured by readiness and pipeline, not slides shipped.

Grew certification completions 200% across ~240 partners, and co-authored two Crossbeam partner-operations features.

Above the readiness bar, a partner delivers without us.

$30M+

annual partner-influenced revenue supported

Fortune 100 cloud company

+200%

increase in certification completions

across ~240 partners

450 → 2,000

referring agencies in 2.5 years

startup scale

$375K

systems audit across 8 platforms

delivered one month early

$7.7M

annualized revenue supported

from 553 proposals

Companies sign partners faster than they can teach, measure, or pay them. I build the system that closes that gap. Three times now, at three different scales.

What others say.

He spearheaded the launch of the partner program … a year ahead of schedule.

Scott OlsenCustomer Marketing & GTM LeaderWorked with Tony from a partner company · 2019

A trusted advisor who partners and colleagues know they can count on.

Phoebe TruongGTM & Enablement leaderSenior to Tony · 2025

Hire him. You won't regret it.

Tony LeSolutions Engineering ManagerCross-functional colleague · 2022

Clipped from LinkedIn recommendations. Full quotes on request; authors' permission to be confirmed before launch.

The same problem, at every scale.

Technical support at a 39-person startup to director-level partner operations at enterprise scale, in thirteen years. The problem never changed: companies need someone to turn a signed partner into a productive one.

I'm technical enough to find a commission error by replaying API calls, and operational enough to have legal, finance, and security in the room before launch. I've done both.