01
AI agents
Evidence becomes structured judgment.
01Evidence
02Research
03Reasoning
04Tool use
05Structured output
Research, reasoning, controlled tools, and structured outputs—with provenance and guardrails.
AI systems engineer · product builder
I turn manual business operations into intelligent software systems.
I build AI agents, durable automation, and full-stack products for revenue, finance, customer, and internal operations—around the tools businesses already use.
Keep your stackHuman control where it mattersStart with one workflow
30 minutes · No obligation · No production access required
SYSTEM VISUALIZATION
INPUTEvidence
INTELLIGENCEInterpret + structure
DETERMINISTIC CODEEnforce boundaries
HUMANAuthorize consequence
EXISTING SYSTEMExecute + remember
AI interpretsCode constrainsPeople control
What I build
The intelligence, the workflow, and the product around it.
Three engineering layers. One operating system when they work together.
02
Automation systems
Intent becomes durable execution.
01Event
02Worker
03Durable state
04Approval
05Side effect
06Recovery
Events move through persisted state, approval boundaries, side effects, and explicit recovery.
03
Full-stack products
The intelligence becomes operable.
01Interface
02API
03Auth
04Data
05Operations
06Deployment
The interface, API, permissions, data, operations, and deployment around the model.
ALL THREE LAYERSRevenueOS combines all three.See the flagship system ↓
ONE PRODUCT THESIS
Intelligent business operations
REVENUE OPSRevenueOS
FINANCE OPSFinanceOps
CUSTOMER OPSSupportOS
Featured systems
The work is the evidence.
Architecture, workflow state, control boundaries, and failure handling—not decorative dashboards.
01 / Revenue operations
RevenueOS
AI Revenue Operating System
DOCUMENTED CHECKPOINT
Turns inbound leads into evidence-backed intelligence, deterministic qualification, human-approved outreach, and durable CRM workflows.
Open engineering case study ↗Northstar Systems
Domainnorthstar.example
RoleVP Revenue
Data qualityIdentity resolved
01
Hiring signalRevenue operations role opened · source attached
0.9202
Expansion signalNew enterprise segment · source attached
0.8603
Conflicting size dataRequires evidence merge policy
REVIEW01ContextPERSISTED
02Data qualityPERSISTED
03ResearchPERSISTED
04Evidence mergePERSISTED
05Conflict resolutionPERSISTED
06Company analysisPERSISTED
07Pain signalsPERSISTED
08Buying signalsPERSISTED
09ICP scoreCURRENT
10StrategyQUEUED
11OutreachQUEUED
12PolicyQUEUED
13PersistenceQUEUED
14Approval handoffQUEUED
DETERMINISTIC ICPREVIEW
Rule band, not a claimed metric
CONTROL BOUNDARYAwaiting human approval
Agent completed. No outbound action yet.
OUTBOUND STATEBLOCKED BY APPROVALOutbox intent not created
DURABLE EXECUTION
01Event
02Transactional outbox
03Worker
04Idempotent side effect
05Reconciliation
State, not a chat loop.
Typed graph structure, bounded tools, persisted step outputs, and evidence-aware transitions.
Intent survives failure.
Worker execution, transactional outbox, retry boundaries, and reconciliation for uncertain outcomes.
Approval is architectural.
RBAC, tenant boundaries, least privilege, and an explicit human gate before outbound work.
No stale numbers.
Numeric metrics are withheld until the living RevenueOS repository can be re-verified.
02 / Finance operations
FinanceOps
Document validation, reconciliation, exception handling, and controlled ERP handoff.
PRODUCT DIRECTION · IN DEVELOPMENTView system direction ↗
SYSTEM VISUALIZATION · SYNTHETIC DOCUMENT
INVOICE / SYNTHETICINV-2048
EXTRACTED FIELDS
SupplierNorthstar Ltd
VALIDPOPO-8892
MATCHGRNGRN-147
MATCHTax total1,940
CHECKRECONCILIATION
INVOICEPOGRN
EXCEPTIONTax total outside toleranceRoute to human review · no payment action
ERP HANDOFFLOCKED
03 / Customer operations
SupportOS
Context-aware resolution, policy checks, SLA routing, and human escalation—not a chatbot.
PRODUCT DIRECTION · IN DEVELOPMENTView system direction ↗
SYSTEM VISUALIZATION · SYNTHETIC TICKET
CUSTOMER REQUEST / SYNTHETIC“The renewal total doesn’t match our agreement.”Enterprise · SLA window active
RETRIEVED CONTEXT
AgreementMSA-EXAMPLE
AccountEnterprise / EU
Prior caseRelated case attached
RESOLUTION RECOMMENDATION
Pricing term may conflict with the renewal line item. Do not resolve automatically.
POLICYHuman review required
CONFIDENCEBelow controlled threshold
SLA / OWNEREscalate to billing specialistFull evidence package attached
Business relevance
Important operations should not depend on fragmented manual handoffs.
Revenue
Research · qualification · CRM updates
Finance
Document validation · reconciliation · exceptions
Customer
Triage · context · escalation · SLA
Internal
Data movement · approvals · repetitive operations
Existing stack
Keep your systems. Upgrade the workflow.
Integrate around the tools that already carry the business. Increase access only after proof.
ARCHITECTURE
EXISTINGCRM
EXISTINGERP / FINANCE
EXISTINGEMAIL
EXISTINGSHEETS
EXISTINGDATABASE
EXISTINGINTERNAL APPS
APIWEBHOOKEVENTDATA
AIInterpret evidence
WORKFLOWPersist state
CODEEnforce rules
HUMANAuthorize risk
EXISTING OPERATIONSNo unnecessary rip-and-replace
READ-ONLY FIRSTLEAST PRIVILEGESCOPED WRITE ACCESS
How I work
From uncertain workflow to controlled system.
Every stage produces an artifact that reduces the next decision.
STAGE ARTIFACT / 01
01 / DIAGNOSTIC WORKFLOW SPECREDACTED MAPPING
01 TRIGGER
Inbound Email / API PayloadUNSTRUCTURED02 GAP
Manual Copy-Paste [latency: 4.2h · drop risk]BOTTLENECK03 TARGET
System of Record [CRM / ERP Write]UNTRACKEDTARGET: EXTRACT DETERMINISTIC RULE BOUNDARIES · ZERO CREDENTIALS
No production access required
Workflow map
Trigger → people → systems → decisions → failure points
Risk infrastructure
Lower risk by design.
Authority expands only after the workflow proves value.
01
Free auditNo credentials
02
DiscoveryRedacted examples
03
PrototypeSynthetic / sandbox
04
PilotLimited permissions
05
ProductionScoped authority + monitoring
06
ExpansionOnly after proof
ENGINEERING CONTROLS
01Read-only first
02Least privilege
03Human approval
04Idempotent actions
05Recoverable failures
06Audit trails
TOOLS collect factsAI interprets factsCODE enforces rulesHUMANS authorize consequenceDATABASE remembers stateLOGS explain what happened
Choose the right conversation
The evidence changes with the question.
Can he own serious AI and backend work?
Start with architecture, reliability, and implementation boundaries.
Review engineering evidence ↗Can this workflow improve safely?
Map one real operating problem and the smallest useful first system.
Free AI workflow audit ↗Is there a coherent product direction?
Start with the three-system thesis and product decisions.
Explore what I'm building ↗FAQ
Serious questions deserve visible answers.
Access, control, failure, integration, and commercial scope—handled before commitment.
Data & security
Do you need production access for the audit?
No. The first audit works from a workflow explanation, screenshots, redacted examples, or synthetic data. Credentials and production access are not required.
What happens to sensitive business data?
The architecture defines the boundary. I minimize data exposure, map provider and storage paths, and avoid privacy claims the actual system cannot guarantee.
AI control
What if the AI is wrong?
AI interprets evidence and proposes structured outcomes. Deterministic code enforces hard rules, while people authorize consequential actions.
Can AI take irreversible actions?
Not by default. High-consequence actions should sit behind explicit policy, permissions, confidence thresholds, and human approval.
Reliability
What happens when automation fails halfway through?
The workflow should persist state, retry safely, use idempotency at action boundaries, and expose failures for recovery.
What if an action happened but confirmation was lost?
The system needs an uncertain state and reconciliation path instead of blindly repeating the external action.
Integration
Do we need to replace our current tools?
Usually not. The default is to keep the CRM, ERP, email, spreadsheets, databases, and internal applications that already work.
How much access does an integration need?
Start read-only where possible, follow least privilege, and add narrowly scoped write access only after the workflow justifies it.
Commercial
What should we automate first?
One repetitive, measurable workflow with clear friction and a safe boundary. The audit exists to identify that step—or say when AI is unnecessary.
How long and how much will implementation take?
That depends on integrations, permissions, reliability, data sensitivity, and product scope. A meaningful estimate follows workflow mapping.
Free AI workflow audit
Still unsure whether your workflow should use AI?
That’s exactly why the first conversation is an audit—not a sales commitment.
Get my free AI workflow audit ↗30 MINUTES · NO OBLIGATION · NO PRODUCTION ACCESS REQUIRED