Trivista AI Discussion

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Trivista AI Practice / Simon Farmer
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Early Foundations

Discussion Topics & Field Notes

A scratchpad of observations and open questions as we prepare for our conversation. Click any topic below to explore.

01

Onboarding Documentation

Capturing setup workflows into a repeatable reference for future team members.

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02

Workspace & Data Isolation

Partitioning, virtualized environments, and customer infosec compliance.

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03

AI Model Governance

Client cloud VPCs, enterprise ZDR, and personal frontier model boundaries.

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04

Visibility & Progress

Demystifying technical progress through blueprints and run summaries.

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05

Modular Tooling

Composable primitives (MCP connectors, database tools) over rigid harnesses.

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06

Reliability & Evals

Golden test sets, automated regression checks, and deterministic outputs.

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DAY-1 DISCOVERY Toolchains & Access Steps REAL-TIME CAPTURE Living Notes & Gotchas REPEATABLE GUIDE Frictionless Team Scale
TOPIC 01

Onboarding Documentation

"When starting out in a new technical environment, the initial setup often surfaces useful details. Keeping clear notes on environment setups, access steps, and conventions as they happen could be a helpful reference for future team members."

LOCAL PARTITIONING Dedicated 100GB Volume Encrypted Drive / Clean Tree STANDARD SPEED VIRTUAL CONTAINERS Dev Containers / Docker Isolated OS / WSL Instances HIGH ISOLATION MANAGED HARDWARE Client-Issued Laptops Cloud VDI Perimeters MAX COMPLIANCE
TOPIC 02

Workspace & Data Isolation

"Different projects and clients often have varying security requirements. Finding practical ways to keep environments cleanly separated without adding unnecessary friction is something I would be glad to explore further."

ROUTING & TENANCY CLIENT CLOUD VPC Azure OpenAI / AWS Bedrock Perimeter ENTERPRISE ZDR Zero Data Retention / Discard Logging PERSONAL FRONTIER Codex & Gemini (Tool Scaffolding • Sanitized)
TOPIC 03

AI Model Governance & Tenancy

"Organizing AI model access involves balancing data privacy, compliance, and developer workflow. There are differences between using enterprise zero-data-retention endpoints, client-managed cloud accounts, or personal developer accounts with frontier models like Codex or Gemini. Establishing clean access patterns upfront helps work stay compliant while keeping developers productive."

EXECUTION TRACE Prompts, Tools, Retries STRUCTURED ARTIFACT Architecture & Blueprints CLIENT REVIEW Clear Milestone Sign-off
TOPIC 04

Visibility & Communicating Progress

"AI work can sometimes appear opaque to external stakeholders. Clear communication around results and progress makes a big difference. Providing concise overviews, architecture summaries, or run reports can make the technical work more accessible."

MONOLITHIC HARNESS Rigid Agent Frameworks High Maintenance Overhead Brittle as models advance VS COMPOSABLE PRIMITIVES MCP SERVERS DB TOOLS EVAL HARNESS Agile • Reusable • Model-Agnostic
TOPIC 05

Modular Tooling

"Frontier models are often most effective when supported by focused, modular tools rather than large, rigid frameworks. Small primitives, such as database connectors, lightweight utilities, or data ingestion scripts, provide good developer productivity while remaining easy to adapt."

GOLDEN SETS Curated Edge Cases EVAL SUITES Continuous Regression SCHEMA RIGOR Deterministic JSON CLIENT READY Confidence Intervals
TOPIC 06

Reliability Standards & Evals

"Moving from initial prototypes to dependable solutions usually requires consistent testing. Applying structured evaluation standards and benchmarks helps verify real-world reliability."