THE EXECUTION LAYER OF AI
JADEN
GARZA.
Systems architect.
Agent infrastructure builder.
Operator.
HALF AS SMART / GARZA OS
Connecting model intelligence to persistent memory, coordinated agents, and verifiable execution.
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THE PERSPECTIVE
CEO & BUILDER
HALF AS SMART
GARZA OS
The model is one layer.
The system is the work.
Jaden Garza works at the boundary between machine intelligence and executable systems. A CEO and AI systems architect, he is the builder behind Half as Smart, the umbrella brand for his AI-product portfolio, and GARZA OS, his agent operating stack.
His work connects context engineering, persistent memory, protocol integration, and agent runtime semantics with the operational realities of authority, recovery, cost, and independent verification. His approach combines architectural direction, direct experimentation, and AI-assisted implementation.
Not just what a model can infer.
What a system can actually do.
02 / TECHNICAL TERRITORY
The architecture
behind autonomy.
Deep technical scope, from inference behavior to the control planes surrounding autonomous work.
01Inference & context
Capability-aware model selection, token economics, context-budget allocation, compaction invariants, and task-conditioned evidence assembly.
Model behavior / harness boundaries / information density02Memory & continuity
Persistent identity, semantic and lexical retrieval, temporal knowledge graphs, recall/retain workflows, shared-memory boundaries, and background consolidation.
Context ≠ memory / persistence contracts / provenance03Tools & execution
MCP architecture, API adapters, composable skills, coding-agent harnesses, session multiplexing, structured subprocess control, and asynchronous lifecycle semantics.
Tool contracts / runtime adapters / protocol mediation04Coordination & verification
A2A delegation, worker-context partitioning, dependency-aware parallelism, perspective-conditioned review, correlated-error control, and evidence-based acceptance.
Delegation envelopes / generator–verifier separation05Authority & infrastructure
Hosted agent computers, container and credential isolation, replaceable compute, action-bound approvals, durable continuations, and side-effect reconciliation.
Control planes / least privilege / restart recovery06Products & economics
Inference gateways, customer tenancy, provisioning state machines, authoritative usage ledgers, entitlement enforcement, and cost per verified outcome.
Runtime productization / metering / commercial control
THE CENTRAL THESIS
Agent capability is a
systems property.
Not a model feature.
The meaningful unit of AI performance is a verified outcome, not a convincing response.
03 / ON THE AGENDA
Conversations worth
having on stage.
Specific architectural questions. Clear audience takeaways. Built for people moving beyond the demo.
01AGENT INFRASTRUCTUREThe Execution Layer
Where agentic AI becomes
a systems problem.
The Execution Layer
Follow the path from model-generated intent to authorized action: context assembly, capability discovery, tool dispatch, persistence, failure handling, and acceptance.
The takeaway: A framework for locating failures in the model, memory, tools, runtime, policy, or orchestration rather than blaming “the AI.”
02PERSISTENT AGENTSWhat Survives the Restart?
State continuity
is the architecture.
What Survives the Restart?
Separate context capacity, stored history, memory, workspaces, and process lifetime. Examine what must be retained to resume an interrupted operation safely.
The takeaway: A precise way to evaluate persistence claims and define recovery contracts.
03MULTI-AGENT SYSTEMSMore Agents. Better Outcomes?
Coordination, correlated errors,
and the cost of being wrong.
More Agents. Better Outcomes?
Examine delegation contracts, context partitioning, workspace ownership, and independent review to understand when parallel agents create value and when they multiply failure.
The takeaway: A decision framework for choosing single-agent execution, specialist delegation, or independent verification.
04INTEROPERABILITY & GOVERNANCEConnected Does Not Mean Authorized.
MCP is the connection.
Authority is the boundary.
Connected Does Not Mean Authorized.
Explore scoped toolsets, credential containment, action-bound approvals, and the distinction between a cooperative agent and an enforced execution boundary.
The takeaway: A clear separation of capability, identity, permission, and successful execution.
05VERIFICATION & QA“Done” Is Not an Acceptance Criterion.
The agent that made it
should not be the only judge.
“Done” Is Not an Acceptance Criterion.
Connect executable specifications, browser-based evidence, isolated repairs, independent retesting, and bounded remediation loops.
The takeaway: Replace self-reported completion with explicit acceptance conditions and inspectable evidence.
06AI PRODUCT ARCHITECTUREFrom Runtime to Real Product.
The infrastructure
around the intelligence.
From Runtime to Real Product.
Map the systems around an agent: customer isolation, provisioning, gateways, credits, entitlements, durable state, and operational control.
The takeaway: Understand what must exist between a capable runtime and an operable commercial service.
04 / FOR ORGANIZERS
The speaker kit.
Ready-to-use copy for conference applications, event programs, and host introductions.
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