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Insights

Practical writing for builders and buyers of AI.

The patterns we see in production engagements — what works, what fails, and the decisions that separate AI programs that last from pilots that quietly die.

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GovernanceMay 12, 2026·11 min read

The 2026 EU AI Act compliance checklist for non-EU companies

High-risk AI obligations land 2 August 2026. If you sell into the EU, here is the practical, non-lawyer checklist your team can act on now — and the traps that have already caught early adopters.

GenAIMay 5, 2026·13 min read

The eight ways enterprise RAG implementations fail (and how to fix them)

Retrieval-Augmented Generation looks easy in a demo and hard in production. Here are the eight failure modes we see again and again across enterprise rollouts — with the fix for each.

StrategyApr 22, 2026·14 min read

From PoC to production: why 70% of AI pilots die — and what to do differently

McKinsey, Gartner, IBM — every analyst publishes the same depressing number. We unpack why most AI pilots never reach production, and the seven practices that move the survival rate.

GenAIMay 20, 2026·12 min read

RAG, fine-tuning, or custom model — a decision framework

When does retrieval beat fine-tuning? When does fine-tuning beat both? A practical decision framework with the criteria that actually matter — cost, latency, freshness, and skill required.

DataMay 18, 2026·11 min read

What does AI training data actually cost in 2026?

Annotation, RLHF, synthetic data, expert-in-the-loop — five years into the data-labelling economy, here is what the market actually charges in 2026 and where the real cost shows up.

AgenticMay 15, 2026·10 min read

Agentic AI vs classical ML: a CIO decision framework

Agentic systems are not the answer to every problem — and many classical-ML problems are now being mis-sold as agent opportunities. Here is the framework we walk CIOs through.

MLOpsMay 10, 2026·12 min read

MLOps vs LLMOps vs AgentOps: what is actually different

Three overlapping disciplines, three sets of tools, one confusion. We break down what changes between MLOps, LLMOps, and the newer AgentOps — and which one your team needs.

SecurityMay 8, 2026·13 min read

A practical playbook for running an LLM red-team campaign

OWASP LLM Top 10, MITRE ATLAS, prompt injection, data exfiltration, jailbreaks — what a real red-team campaign looks like, from scoping to remediation, with the tools we actually use.

GovernanceMay 3, 2026·11 min read

The minimum viable AI governance stack for a 200-person company

You do not need a 40-person CoE. You do need a defined set of policies, controls, and review gates. Here is the lightweight governance stack that gets mid-market companies through procurement.

DataApr 28, 2026·14 min read

Vector databases compared in 2026: Pinecone, Weaviate, Milvus, pgvector, Qdrant

Pure vector store, hybrid lakehouse extension, or just Postgres? A practical 2026 comparison across performance, hybrid retrieval, scale-out, and the real cost at 100M and 1B vectors.

StrategyApr 25, 2026·10 min read

How to write an AI business case your CFO will approve

CFOs do not buy "AI transformation." They buy specific, time-boxed bets with defensible numbers. Here is the structure that survives finance review — and the four mistakes that kill most submissions.

MLOpsApr 18, 2026·15 min read

The 30 AI metrics that actually predict production success

Forget vanity model accuracy. These are the 30 metrics — engineering, business, and human — that separate models that survive contact with users from those that quietly die.

DataApr 15, 2026·12 min read

AI training data: build, buy, or label — choosing the right approach

When to scrape and synthesise, when to license, when to label, and when to do all three. The decision framework for sourcing the data your model will actually learn from.

GenAIApr 10, 2026·13 min read

Self-hosting LLMs vs API: a 2026 cost and risk comparison

GPU prices, model quality, fine-tune flexibility, regulatory exposure — when does self-hosting beat calling an API in 2026? A grounded comparison with the numbers we are actually seeing.

AgenticApr 5, 2026·14 min read

The agentic SDLC: how AI is changing how software gets built

Copilots were the first wave. Agentic SDLC is the second. We break down what changes between requirements, code, tests, and release when AI agents are first-class contributors.

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