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AlgoCoder
Case Studies · AI & LLM Engineering

AI & LLM Engineering

Most AI products demo a model that has never faced a regulator, never held custody, and never reconciled a transaction at 3am. AlgoCoder ships AI into production — the custody systems, the audit trails, the security architecture, and the inference pipelines that make the model a product instead of a notebook.

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Engineering Notes · 12 Notes

AI & LLM Engineering — recurring patterns.

AI & LLM EngineeringPilot purgatory

Pilot-to-Production Engagement for an Enterprise AI Initiative That Couldn't Ship

The board approved the AI initiative six months ago. The demo was great. Nothing had reached a user.

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AI & LLM EngineeringRAG accuracy

RAG Pipeline Accuracy Remediation for a Knowledge Assistant That Wasn't Working

The assistant returned wrong answers often enough that users had stopped using it.

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AI & LLM EngineeringVector databases at scale

Vector Database Migration for a Search Application Hitting Cost and Latency Limits

The hosted vector database had been the right choice. The application's growth had moved them past it.

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AI & LLM EngineeringPrivacy-first AI

Privacy-First AI Architecture for a Client Whose Data Couldn't Leave Their Environment

The use case was strong. The data couldn't be sent to a hosted model under any circumstances.

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AI & LLM EngineeringLLM hallucination control

Hallucination Control for an LLM-Powered Citation Generator

The model was generating citations to sources that didn't exist. The legal team was not amused.

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AI & LLM Engineering · with DevOps crossoverAI in regulated finance

AI Compliance Architecture for a Regulated Finance Product

The model worked. Surviving regulatory review was the engineering problem nobody had budgeted for.

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AI & LLM EngineeringMLOps + monitoring

Model Observability for a Production LLM System Whose Outputs Were Quietly Degrading

The system was working. The team didn't know that "working" was getting worse week over week.

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AI & LLM EngineeringPilot purgatory (extended into model strategy)

Fine-Tuning Engagement for a Domain-Specific Use Case Where General Models Underperformed

General-purpose models knew the language. They didn't know the domain.

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AI & LLM EngineeringRAG accuracy (extended into prompt engineering)

Prompt Engineering and Evaluation Framework for a Team Iterating on AI Features Without Methodology

The team was changing prompts daily. Nobody could tell whether the changes were helping.

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AI & LLM EngineeringMLOps + monitoring (extended into model strategy)

Multi-Model Routing Architecture for a Team Whose Single-Model Choice Was Capping Capability

One model couldn't be the right answer for every query. The team had been treating it that way.

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AI & LLM EngineeringPilot purgatory (extended into agent architecture)

AI Agent Architecture for a Workflow Automation Use Case That Multi-Step LLM Calls Couldn't Handle

The workflow needed reasoning across multiple tools and sources. Chained prompts weren't getting there.

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AI & LLM EngineeringVector databases at scale (extended into cost engineering)

LLM Application Cost Optimization for a Team Whose AI Bill Had Grown Faster Than Their Revenue

The model worked. The bill broke the unit economics.

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AI & LLM Engineering

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