BILLHOOD.AI · POWERED BY AI-ME.AI

Meet Bill's AI-Me

Ask questions. Explore his work. Interview him. See how he'd approach your problem.

Decades of building networks, systems, security, cloud, and AI—made available through one governed conversation.

Start a conversation Does Bill fit?
AI portrait of Bill Hood wearing a blue capAI BILL · FOUNDING EDITION

TECHNOLOGIST · ARCHITECT · ENTREPRENEUR · TEACHER

Bill Hood

Four decades turning difficult business and technical problems into working software, networks, cloud platforms, secure infrastructure, and governed AI systems.

1978
Technology journey begins
1998
Founded Network Partners
2012
AWS and SoftNAS
Today
AI-assisted engineering

Most AI knows a little about everything. This one is learning a great deal about one life of building things that work.

ONE RECORD · DIFFERENT CONVERSATIONS

Choose how
you want to ask.

Each experience draws from the same governed record. The conversation changes its emphasis—not the underlying facts.

01

Interview Bill

A formal, executive conversation about leadership, experience, architecture, delivery, and the decisions behind the résumé.

Begin the interview FORMAL · EXECUTIVE · EVIDENCE-LED
02

Ask Bill

A hands-on technical collaborator for AI, networks, cloud, security, systems design, and difficult implementation choices.

Open Engineer Mode TECHNICAL · EVIDENCE-LED · PLAN-DRIVEN

Phase 1 is intentionally chat-only. Voice is planned for Phase 2; full-motion personas remain separate Phase 3 research.

ASK BILL · FOUNDING EDITION

Bring a real problem.

Ask about technology, architecture, risk, delivery, or experience. Every answer stays inside Bill's approved record.

STARTING POINTS

CURATED RESPONSE● BILL-APPROVED SOURCE

“What is Next of Mind?”

It is a way to capture a person while they are actively thinking, let them govern the result while living, and preserve an honest conversational legacy for people who have not even been born yet. This first edition is curated; it answers only from material Bill has approved.
THE THREAD

A living point of view, preserved with consent.

HONEST ROLE REVIEW

Could Bill help
with this role?

Upload or paste a job description. Phase 1 compares its requirements with Bill's approved career evidence and separates substantiated strengths from unproven claims.

The document is read in your browser. Anonymous comparisons stay on this device; after sign-in, extracted text is sent securely for the live assessment but is not stored or added to Bill's knowledge record.

01

Give me the role.
I'll give you the honest answer.

The assessment will identify direct evidence, adjacent experience, material gaps, and the questions a hiring team should still ask.

THE WORK

From LANs
to living AI.

More than three decades translating difficult technology into useful, resilient systems.

Download current résumé
THE BOOK

A life,
still in motion.

Preview the stories, turning points, and ideas behind the technical record.

BOOK PREVIEW · COMING SOON

CAREER EXPERIENCE · CHRONOLOGICAL

1978 TO PRESENT

A career spent
building forward.

From an early minicomputer-based business system to enterprise AI: the high-level chronology of Bill's work, leadership, teaching, and company-building experience.

01
1978–1979

TeleCheck, Inc.

First exposure to a DEC-minicomputer-based business system—the experience that inspired Bill to learn programming.

02
1983–1985

GAF Dallas

Built a BASIC production-data and reporting application on an IBM PC while attending college; Bill’s first successful business application.

03
Approximately 1985–1986

InterFirst Bank Dallas

Designed internal banking solutions in his first post-college technology position.

04
Approximately 1986–1989

Price Waterhouse

Consulted on technology supporting NCNB bank acquisitions and integrations.

05
Approximately 1989–1998

Guaranty Federal Bank

Directed technical architecture supporting more than 150 locations, branch acquisitions, enterprise networks, and an early cross-system banking data warehouse.

06
1996–2012

Globe Products

Served as lead systems designer for a SQL-based manufacturing and operations platform in an overlapping client engagement.

07
1998–2013

Network Partners, Inc.

Founded and led the company through thousands of application, infrastructure, network, wireless, security, and cloud-transition projects; successful exit in 2013.

08
2012–2015

SoftNAS

Cofounded the company and served as technical lead for its Linux and ZFS cloud NAS platform; successful exit in 2015.

09
2013–2019

Consulting engagements

Worked as a senior consultant and cloud architect across commercial and federal systems.

10
2016–2017

Relay2

Served as a presales engineer for enterprise wireless access points with embedded Linux and fog-computing capabilities.

11
2017–2021

University of New Mexico–Taos

Taught computer science, networking, data and databases, Python, and cloud-related subjects as an adjunct instructor.

12
2021–2023

New Apprenticeship

Taught AWS architecture with Python to a professional apprenticeship cohort.

13
2024–2025

True Kids 1

Served as Director of Technology.

14
2025–2026

Taos Academy

Taught mathematics and computer science.

15
2025–2026

SmarTek21

Designed and implemented enterprise AI architecture, governed reasoning, data analysis, specialist workflows, and AWS-native integrations.

16
2018–Present

Sahara · Partnership with Fred Cary

An ongoing partnership that began with traditional development methods and evolved into human-directed AI engineering with Codex and Claude. Sahara is an AI-based entrepreneurial assistant designed to help entrepreneurs develop a proper business plan.

17
2019–Present

inPro.ai

Architects and prototypes practical AI applications, agentic workflows, knowledge systems, integrations, and customer solutions.

18
2022–Present

Taos Ski Valley

Works as a professional ski instructor, combining technical precision, situational judgment, communication, and individualized teaching.

The chronology stays grounded in Bill's résumé archive and direct confirmations; uncertain dates remain visibly marked.

INTERVIEW BILL · EVIDENCE-LED

CHOOSE THE ROOM

Ask the question
behind the résumé.

INTERVIEWER SAMPLE QUESTIONS

AI BILL RESPONSE● GROUNDED IN BILL'S RECORD

“How do you use Codex differently from a traditional development workflow?”

My loop is understand, plan, approve, build, test, and review. Codex expands how much code, architecture, data flow, documentation, and test evidence I can examine, but I retain responsibility for the requirements, constraints, security, architecture, validation, and final decision. It accelerates engineering judgment; it does not replace it.

Ask for the evidence behind the answer.

Interview mode changes the emphasis—not the underlying facts or evidence boundary.

Download current résumé

ENGINEER MODE · BILL'S ANGLE

BRING THE SYSTEM

Build the plan.
Prove the result.

Bill starts with the business objective, verifies the relevant experience, and turns the technical question into a practical, testable project.

SAMPLE TECHNICAL DESIGN QUESTIONS

TECHNICAL DESIGN CONFIRMED● GROUNDED IN BILL'S RECORD

“How would Bill design and deploy a secure enterprise AI application on AWS?”

Yes—this is a technical design question, and Bill has documented experience in AWS and cloud architecture. It also overlaps with Python, software, and APIs. Here is the disciplined starting plan Bill would use.
01 · OVERALL OBJECTIVE STATEMENT

Deliver a secure, supportable solution to: “How would Bill design and deploy a secure enterprise AI application on AWS?” Define measurable success first, preserve what already works, and choose the least-complex architecture that meets the business need.

02 · EXPERIENCE VALIDATION

The key technical area is AWS and cloud architecture. Bill's approved record establishes: Hands-on AWS work since at least 2012, including SoftNAS, serverless genomic compute, AWS instruction, and recent enterprise AI systems. Evidence: Current résumé; SoftNAS 2012–2015; Jackrabbit 2019; New Apprenticeship 2021–2023.

03 · ITEMS REQUIRING MODIFICATION
  • Business requirements, success measures, constraints, and ownership
  • The existing AWS and cloud architecture, Python, software, and APIs components and their interfaces
  • Data flows, identity, permissions, security boundaries, and failure paths
  • Build, test, deployment, observability, recovery, and operating documentation
04 · STEP-BY-STEP PLAN
  1. Understand the business objective, users, current system, constraints, and definition of done.
  2. Inventory the architecture, dependencies, data, environments, security controls, costs, and known failure modes.
  3. Confirm the evidence, reproduce the problem where applicable, and identify the smallest safe change boundary.
  4. Compare a traditional proven design with viable alternatives, documenting tradeoffs, risks, cost, and rollback.
  5. Create the implementation plan, acceptance tests, security checks, migration sequence, owners, and approval gates.
  6. Build in controlled increments; test each boundary before expanding the change.
05 · PROJECT CAPSTONE

Execute the approved solution through a controlled production change, preserving rollback and capturing the exact configuration and decisions used.

06 · VALIDATE THE SOLUTION
  • Run functional and end-to-end acceptance tests against the original objective.
  • Verify security, permissions, data integrity, performance, logging, cost, recovery, and rollback behavior.
  • Obtain stakeholder confirmation that the result solves the business problem—not merely that the deployment completed.
07 · PROJECT WRAP-UP

Close with a concise record of the objective, work completed, tests and evidence, problems encountered, how each was overcome, remaining risks, operating instructions, and recommended next actions.

Challenge the architecture, tradeoffs, assumptions, or evidence. Bill will refine the plan.

Understand the objective. Validate the experience. Plan the smallest safe change. Execute, test, and document the evidence.

GROUNDED IN BILL'S RECORD

THE KNOWLEDGE BOUNDARY

Bill's experience.
Bill's control.

AI Bill answers from materials Bill has provided, reviewed, or personally confirmed—including résumés, project histories, written stories, technical documentation, and direct recollections.

Source material may inform an answer without being publicly displayed. When the record does not support a claim, AI Bill should say so rather than guess.

Bill retains control over what is included, what remains private, and what may be shared publicly. This is my AI-me.ai—and I could build one for you, too.

CONTACT BILL

START A CONVERSATION

Let's build
what's next.

This is Bill's governed message channel. Messages are stored privately so AI-me can become the authority of record for what reaches Bill and, later, help determine what requires his attention.

Submitting stores the information and attachments privately in Bill's AWS account. They are visible only through Bill's authenticated owner inbox and are not added to AI Bill's public knowledge.

BILL'S PRIVATE MESSAGE RECORD

OWNER INBOX

Every message.
One record.

No messages have been received yet.

IMPROVE MY AI-ME · OWNER WORKSPACE

ADD · REVIEW · GOVERN

Teach AI Bill.
Keep control.

Preserve original sources, inspect the extracted record, and explicitly decide what is approved, private, public, or excluded.

INGEST A DOCUMENT

ADD A STRUCTURED MEMORY

SOURCE REVIEW

0 records

No governed sources have been added through this workspace yet.

New material remains private and pending until Bill makes an explicit evidence decision. Approval does not automatically publish the original document.

THE BRIEFING ROOM · PRIVATE GMAIL

READ-ONLY · NOT CONNECTED

What needs
your attention?

This private briefing stores matching message details, bounded conversation context, and AI Bill's private notes for 30 days. It cannot send, forward, delete, or modify mail, and nothing becomes public AI Bill evidence automatically.

TECHNICAL JUDGMENT

FOUR DECADES · AMPLIFIED BY AI

Know what
to build.

My technical judgment is grounded in more than four decades of building, architecting, troubleshooting, and explaining software systems—and today it is amplified by AI.

I focus first on understanding the business objective and the system that already exists, then determining the simplest, safest path forward rather than reaching immediately for new technology.

I use tools such as Codex to dramatically expand how much code, architecture, data, and documentation I can examine, while keeping requirements, architecture, security, testing, governance, and final decisions under human control.

Experience has taught me that good engineering is rarely about writing the most code; it is about knowing what to build, what not to build, what to question, and when the evidence says you are ready to move forward.

PROJECT HISTORY · REVERSE CHRONOLOGICAL

PROJECT EVIDENCE · 1983 TO PRESENT

The work
behind the work.

Selected projects recovered from Bill’s résumé archive and confirmed career evidence. Dates marked approximate or unresolved remain that way by design.

01
2025–2026

Enterprise AI platform · SmarTek21

Built governed workflows spanning structured and unstructured ingestion, retrieval, natural-language and SQL analysis, specialist orchestration, human approvals, AWS discovery, configuration drift, and evidence-bounded reporting.

Enterprise AIAWSGovernance
02
2019–Present

AI solution prototypes · inPro.ai

Architected conversational AI, retrieval, agentic workflows, knowledge systems, integrations, and rapid customer proofs of concept connecting emerging AI to practical business needs.

AIRAGPrototyping
03
September 3, 2019

Jackrabbit genomic-compute orchestration

Designed a web-initiated, Lambda-and-Boto3 control plane for dedicated EC2 instances running long-duration customer DNA-analysis algorithms.

AWSPythonGenomics
04
2018–Present

Sahara · Partnership with Fred Cary

A sustained partnership that began with traditional development methods and evolved into AI-enabled applications through human-directed Codex and Claude workflows. Sahara is an AI-based entrepreneurial assistant designed to help entrepreneurs develop a proper business plan, moving from requirements and architecture to working software, tests, and demonstrations.

EntrepreneurshipAI engineeringBusiness planning
05
2018

QR cash-transfer proof of concept

Built a GCP proof of concept combining account seeding, QR-code cash transfer, SMS interaction, and mobile redemption.

GCPFintechMobile
06
2012–2015

SoftNAS cloud storage platform

Cofounded and helped engineer a Linux and ZFS virtual NAS that aggregated AWS EBS volumes into RAID arrays and launched through AWS Marketplace; successful exit in 2015.

AWSLinuxZFS
07
Summer 2009

BarackObama.com infrastructure migration

Led network engineering and project management for infrastructure and DNS migration, with reported downtime below one minute.

NetworksDNSMigration
08
1998–2013

Network Partners project portfolio

Founded and led thousands of software, infrastructure, network, wireless, security, and cloud-transition projects through a successful 2013 exit.

InfrastructureNetworksSecurity
09
Dates not isolated in source

Large-scale wireless environments

Designed and delivered wireless environments for CDW, St. Edward’s University, NOAA, the Department of the Navy, and the Democratic National Convention.

WirelessEnterpriseFederal
10
1996–2012

Globe Products manufacturing system

Designed a SQL-based manufacturing and operations platform supporting tool-and-die work, production planning, inventory forecasting, and operational visibility.

SQLManufacturingOperations
11
Approximately 1990–1995

Guaranty Federal Bank data warehouse

Extracted isolated savings, lending, and operational data into common structures so the bank could report across systems; the platform progressed toward Microsoft SQL Server.

Data warehouseBankingSQL
12
Approximately 1989–1998

Guaranty Federal Bank enterprise infrastructure

Directed technical architecture supporting more than 150 locations and branch acquisitions.

Enterprise architectureBankingNetworks
13
Approximately 1986–1989

NCNB acquisition integrations · Price Waterhouse

Supported banking acquisition and integration work as a technology consultant.

IntegrationBankingConsulting
14
Approximately 1985–1986

InterFirst Bank internal systems

Designed internal banking solutions in Bill’s first post-college technology position.

BankingApplicationsSystems
15
1983–1985

GAF production-data application

Built a BASIC application on an IBM PC for production-data entry, database storage, and predefined operational reporting—Bill’s first successful business application.

BASICIBM PCOperations

This record will grow as additional source material is reviewed and Bill confirms the details.

PHASE 1 · CHAT● LIVE

Does Bill have experience designing secure AI systems on AWS?

Yes. Bill's approved record includes AWS work beginning with SoftNAS in 2012, serverless compute orchestration, AWS instruction, and recent governed enterprise AI systems.

EVIDENCE

Current résumé · SoftNAS · Jackrabbit · Enterprise AI portfolio

Ask your technical question

THE STANDARD

Preserve the person,
not a performance.

01

Alive, not archived

Capture a point of view while it can still grow, disagree, and become more precise.

02

Governed by its owner

Bill decides what belongs, what stays private, and what should never be inferred.

03

Honest about its limits

A trusted voice says “I don't know” when the approved record does not support an answer.