WKWissam Kazan Connect on LinkedIn ↗

AI executive · Operator · Hands-on builder

One person.
A team of AI agents.

I help leaders multiply what each employee can accomplish. One person directs 5–10 specialized agents that work in parallel, coordinate with one another, and bring back work they can review and use.

Connect on LinkedIn ↗ See how it works ↓
AI at Stanford Computer science · 2005–2006 Enterprise leadership OCI · Amazon · Microsoft Hands-on building Agent workflows and systems 16 U.S. patents Named co-inventor · Explore the record ↗
Explore the idea

The 10× employee

Give each employee
a team of agents.

An AI agent can use tools and carry out a task across multiple steps. Give several agents complementary responsibilities and a way to share their work, and one person can move several tasks forward at once. The ambition: every engineer a 10× engineer, every employee a 10× employee.

One engineer · Five agentsIllustrative example
◎
THE PERSONAdd a reliable export feature

Set the goal, constraints, and acceptance criteria.

↓ Assign clear responsibilities
01ResearchMap the data and APIs
02BuildImplement the agreed change
03TestCheck behavior and edge cases
04SecurityReview access and data exposure
05DocumentExplain usage and operation
↔
Shared context. Direct coordination.

Agents exchange findings, flag dependencies, and update the same change package.

↓ Converge, check, and review
✓
One reviewed deliverable

Code + test evidence + review findings + documentation.
The engineer decides whether it is ready to release.

01 / 04
Expand what one person can accomplish.

A person’s time limits what they can complete alone. Agents can take on complementary tasks while that person directs the work.

More useful work per personMeasure output, quality, time, and cost
01

Expand individual capacity

Expand what one person can accomplish.

Identify work that one person could direct across a team of agents: research, analysis, implementation, testing, and review.

02

Redesign the work

Break the work into parallel streams.

Give agents clear tasks, shared context, and ways to coordinate with one another. One person's direction can now move several streams of work forward at once.

03

Direct a team of agents

Give each person 5–10 AI agents.

An engineer might direct 5–10 specialized agents. Research and test preparation can overlap; implementation and review use the findings as they become available.

04

Multiply individual output

Build the 10× employee.

Judge the result by accepted work, delivery time, quality, and total cost, including the person’s review. 10× is the ambition; the gain must be demonstrated for each workflow.

Perspective from leading teams

Comparable scope.
Different organizations.

I have led organizations of 500+ people and, in a different organization, roughly 150 people with comparable operating scope. That experience informs how I think about team design and individual capacity.

These are separate organizations, with different operating contexts. This comparison is career context; it does not measure the effect of AI or establish a 10× productivity gain.

500+people in one organization
~150people in another organization

Illustrative agent workflows

See the work and the result.

Explore examples for engineering, operations, and executive research. These are explanatory scenarios with sample artifacts, not live executions or measured client results. Each ends at a clear human decision.

ENGINEERING
ILLUSTRATIVE WORKFLOW

Illustrative workflow · Export feature

A change package ready for review.

EXAMPLE DELIVERABLE

Example review package · CSV export

Goal: export only records the signed-in user can access.
Change: export endpoint and download control.
Test plan: permissions, empty data, large exports, CSV escaping.
Review questions: access checks and spreadsheet formula handling.
Documentation: usage, limits, and rollback instructions.
Status: illustrative package, not an executed test result.
Human decisionEngineer reviews the change and authorizes release
End state shownReview package prepared; release still pending

AI Agent Workflow Sprint

One workflow.
A working pilot.

A focused engagement to build and evaluate one agent workflow. A typical target is four to six weeks, with scope and timing agreed after confirming access to the data, tools, and a workflow owner. The deliverable is an evaluated pilot, team handover, and a rollout plan. Production launch and ongoing support are scoped separately.

Discuss a sprint ↗
  1. 01
    Choose the workflowAgree the goal, owner, and baseline for today’s work
  2. 02
    Define successAgree quality, delivery time, review effort, and total cost criteria
  3. 03
    Design the agent systemDefine agent tasks, shared context, dependencies, and approval points
  4. 04
    Build the pilotA working implementation evaluated against the agreed baseline
  5. 05
    Hand over and plan rolloutDocumentation, team walkthrough, known limits, and next steps

Experience behind the approach

AI at Stanford.
Enterprise leadership.

2005–2006

AI at
Stanford.

M.S. in Computer Science, specializing in artificial intelligence, years before the current generative-AI boom.

Cloud operationsOracle OCI

AI operations leadership, with the reliability and operating demands of cloud infrastructure.

Technology leadershipAmazon

Former CTO, Book Depository. Experience connecting engineering decisions to the needs of an operating business.

Product engineeringMicrosoft

Technology leadership and co-invention across data access, synchronization, and user interfaces.

Selected researchLearning
by building

Co-author of “Remote Internetworking Laboratory,” published in the 2006 ASEE conference proceedings. Read the paper ↗

A record of invention · 2011–2023

Ideas made
concrete.

16

U.S. patent grants
Named co-inventor

From moving data across devices to connecting people with content. Grouped into 11 titles, with related grants together. Each patent number links to its published record.

How I engage

Executive judgment.
Builder-level depth.

For enterprise leaders, private-equity portfolio companies, and founders deciding where agents can create value and how to put them to work.

Start a conversation

Start with one workflow.

Bring a task your team needs to deliver better. Let’s explore what one person and a team of agents could accomplish, and how we would measure the result.

Connect on LinkedIn ↗