Latif · enterprise GTM operator · AI systems builder
I work where enterprise GTM, executive trust, and hands-on AI implementation meet. Most teams already have the tools. The hard part is deciding what changes, what the tools can see, who reviews the work, and what the business keeps for itself.
Current Architecture
ATOM is the model: decide what should change, where context lives, who reviews it, and what proof counts.
Joan is the company I am building around shared context, memory, and review for AI work.
Sidekick starts with meetings and revenue work.
Founder OS keeps the work honest because it runs my own business every day.
20+
Years Enterprise GTM
13
Years Cisco Systems
11x
Cisco Sales Champion/President's Club
$100M+
Career Sales
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ATOM / Enterprise AI Implementation
Access is not adoption. ATOM is the method I use when a company has AI tools but the daily work is still messy: context is scattered, review is unclear, and value is hard to prove.
Buying another license does not change how people work. The change has to show up in the workflow.
Context, memory, approvals, evidence, and handoffs are where AI becomes part of the business instead of another side channel.
The readout shows what to keep in existing tools, what to stop, and where custom software or agents are worth building.
The Story
20+ years in enterprise sales taught me that technology never lands in a vacuum. It collides with incentives, budgets, politics, trust, and human behavior.
So I do not start with a model picker. I start with the work: what people are trying to do, where it breaks, what needs review, and what has to be remembered.
ATOM is the name for that method. Joan is the company I am building around it. Sidekick starts with meetings and revenue. Founder OS keeps it honest because it runs my business every day.
I build to make the upside real without pretending adoption happens because a new tool showed up.
Featured Projects
Start here: Founder OS shows the work running, ATOM explains the method, Joan is the company direction, and Sidekick starts with meetings and revenue.
Founder OS · Running Business
01The best proof is whether the system can carry real business work without creating chaos.
Founder OS briefs me, researches accounts, plans work, prepares follow-up, and keeps review points around anything that can create risk.
Daily briefs | Review gates | Real business work
ATOM + Joan · Method + Company
02Companies are already using AI, but the useful context is scattered across private chats, vendor accounts, meeting tools, docs, CRM, and people's heads.
Joan is the direction for pulling that context into one product layer: what happened, what changed, who reviewed it, and what should happen next.
Shared context | Review trail | Product direction
Sidekick · Meetings + Revenue
03Meetings and revenue work are where context, commitments, follow-through, and judgment collide, but the software usually stops at notes or isolated assistant output.
Sidekick folds the old meeting, sales, and team-sidekick ideas into one product family: prep the meeting, capture what matters, close it out, and carry the work forward.
Meetings | Revenue work | Follow-through
How I Work
The pattern is simple: own the customer relationship, shape the commercial path, understand the system, and stay accountable for what happens after the deal is signed.
20+ years across enterprise GTM, 13 years at Cisco, strategic account roles, founder-led consulting, and C-suite-facing AI implementation work.
The work spans ambiguous market entry, partner-led go-to-market, Microsoft-aligned AI work, and revenue systems rather than simple handoff selling.
ATOM, Joan, Sidekick, and Founder OS connect commercial judgment with system design, delivery quality, and follow-through.
Latif is actively building with AI: owned memory, meeting intelligence, recommendations grounded in real work, agent workflows, and Azure-native production systems.
Section 06 / Resume
Download the resume if you want the clean summary. The resume gives the clean summary; the entries below show the work behind it: enterprise accounts, company building, AI product work, and the systems I run now.
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Role / Project Fit
The Latif AI Guide compares the brief with the work shown here and calls out strong matches, partial matches, and real gaps.