Dae Tan / Technical Portfolio

Northstar Mutual - AE-to-SE Decision Handoff

Fictional portfolio scenario. Northstar Mutual is not a customer. All values are illustrative and demonstrate the handoff method rather than a benchmark, quote, approved architecture, or financial recommendation.

Requested decision

Determine whether a regulated enterprise should advance a private retrieval-augmented generation workload into a bounded technical validation covering model quality, latency, throughput, security controls, infrastructure fit, and unit economics.

Current recommendation: advance conditionally to a controlled PoC. Do not select a final architecture or commercial option until representative workload, benchmark, security, operating-model, and pricing evidence are available.

Workload evidence

Input Illustrative value Evidence status Why it matters
Model class 70B parameters Illustrative Drives memory fit, precision, and parallelism options
Peak demand 45 requests per second Illustrative Anchors sustained and burst throughput tests
End-to-end latency target 900 ms Illustrative Constrains retrieval, reranking, generation, and network design
Governed source data 18 TB Illustrative Affects ingestion, indexing, freshness, storage, and residency
Annual demand growth 35% Illustrative Tests headroom and the future cost curve
Deployment posture Private or hybrid Assumption Adds identity, audit, connectivity, recovery, and operating constraints

What is known

Evidence still required

First-pass solution hypothesis

  1. Separate governed ingestion and indexing from online retrieval and generation.
  2. Use identity-aware access, private connectivity, source authorization, and reviewable audit events.
  3. Benchmark a scalable inference tier using representative prompt, token, concurrency, and traffic distributions.
  4. Instrument retrieval, generation, queueing, accelerator memory, utilization, latency, quality, and failure behavior.
  5. Compare cloud, hybrid, and owned operating models only after workload normalization and measured throughput.

This is a workshop hypothesis. It is not a final architecture, security approval, benchmark result, quote, or bill of materials.

PoC success plan

Gate Measurement Pass condition
Quality Approved question set with expected evidence and citation behavior Threshold agreed with the business and risk owners before testing
Throughput Sustained and burst tests at the representative traffic profile 45 RPS clears with agreed headroom
Latency End-to-end distribution under the same traffic profile Agreed percentile remains within the 900 ms target
Model fit Memory, precision, parallelism, batching, and eviction behavior Stable fit without unsafe interference or hidden quality loss
Security Identity, source authorization, isolation, audit, and retention tests Architecture and security reviewers accept the evidence
Reliability Component failure, retry, recovery, and rollback exercises Recovery remains within agreed objectives
Economics Cost per 1,000 requests using measured utilization and current prices Proposed case survives the agreed sensitivity range

Exact quality thresholds, observation windows, owners, and instrumentation must be agreed before the PoC. A test that cannot fail cannot support a defensible decision.

Commercial handoff

The financial model must normalize both operating states to the same workload, term, growth profile, and service objectives. It should include compute, storage, network, facilities or cloud services, implementation, migration, security review, operations, support, and transition risk.

The review should distinguish realized cash savings, avoided cost, deferred capital, and productivity capacity. No modeled value should be presented as guaranteed revenue or approved savings.

Stakeholder and next-action map

Stakeholder Required decision or evidence
Executive sponsor Confirm business priority, decision date, and value owner
Business and knowledge users Approve representative tasks and quality criteria
AI/ML and platform teams Provide workload trace, model constraints, and benchmark ownership
Security, risk, and data governance Approve data, identity, audit, retention, and recovery controls
Finance and procurement Validate baseline, price sources, term, value treatment, and sensitivity
AE and Solutions Engineer Maintain one evidence record and own the conditional next-step recommendation

Next action: run a discovery and validation-planning workshop to assign owners, replace illustrative inputs with approved evidence, and agree the PoC pass/fail gates.

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