AI

Token Management

I managed token limits in LLM applications where context windows are constrained and costs scale directly.

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Used on

AI Course Writer

2024–2026

Generates long structured documents by filling a template's placeholders from source documents, built for an external training-material business.

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Stories where it mattered

2024 · Kray.AI search and document assistant

One model for everyone, or one per customer

Situation
A document assistant for a fleet operator needed an architecture, and one model trained on every vessel's documents was the assumed default.
Task
Lay out the real trade-offs of cost, latency and access control instead of just picking one.
Action
I wrote both options out for client and team: one shared model versus one model per vessel, with pros, cons and the replica arithmetic.
Result
The partitioned design went forward, with the loss of cross-fleet questions accepted openly.
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2026 · Regulatory medical-writing platform

A cache that remembered the failures

Situation
On a regulatory document platform, generated documents came out wrong in ways that did not reproduce, and retries repeated the bad output.
Task
Find the true cause in a pipeline whose output reaches a client in a regulated industry.
Action
I traced it to a global result cache that also stored partial failed runs, then re-architected generation around per-step isolation with failure-aware cleanup.
Result
Failed runs stopped affecting later ones, a retry became a real retry, and the written root cause let the team review it.
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2026 · Regulatory medical-writing platform

Tables that arrived in the client's document as raw markup

Situation
Medical writing deliverables showed misplaced tables, detached titles, and sometimes raw markup visible as text in the client's document.
Task
Produce one root cause analysis for three separately reported bugs before anyone wrote a fix.
Action
I found three causes: raw XML mutation, incomplete model-emitted HTML, and context-blind placeholders. I moved tables to a structured contract with neighbour context.
Result
The whole class of defect went away, not just the three reported instances.
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2024 · Regulatory medical-writing platform

Asking what onboarding was supposed to produce

Situation
Two engineers were joining a document platform module covering audit logs, automatic mapping and server management.
Task
Give onboarding an intended outcome rather than just an activity.
Action
I asked the lead for the target outcome, how we would judge pace, and when production value was expected, and offered a reference checklist.
Result
Onboarding ran against a stated target and a first-value date, and the checklist was reused.
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Prompt EngineeringLLMsRAGVector SearchEmbeddingsCost Modelling

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