Posts about consulting
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What 16,000 Simon Willison posts reveal about the state of AI coding agents
Analysis of Simon Willison's blog corpus reveals AI coding agents crossed a reliability threshold in late 2025 and are now reshaping software engineering.
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The Architecture Biopsy
A method for finding gaps in AI systems that architecture reviews miss. Force a naming constraint, and the breaks reveal what's missing.
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Managing AI Agents Like Managing a Team
The governance patterns for autonomous AI agents are the same ones good managers already use: cadence reviews for normal flow, escalation channels for urgent anomalies, and human judgment only where it has maximum information value.
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Your AI Did the Research. You Didn't.
AI-prepared domain research creates false readiness. The vault says you know five regulatory jurisdictions. You can't name three.
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Inference Cost Collapse Is a Governance Liability
When AI agent calls approach zero cost, the natural rate-limiter on decision volume disappears — and oversight frameworks designed for prediction models break.
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The AI/DLT Conflation Trap in HKMA's March 2026 Strategic Review Mandate
HKMA's new strategic review circular bundles AI inference risk and smart contract risk into one workstream — a governance design flaw that will cause banks to under-govern both.
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Show Up with the Machine, Not the Idea
The highest-leverage consulting prep is building the tool before you need it
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Governance Is a Tax
The most useful reframe I've found for AI governance in financial services
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Impossibility Theorems as Consulting Tools
Mathematical impossibility results are the best meeting-room weapons I know.
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When Your AI Advisor Is Also Your AI Vendor's Partner
What does the Frontier Alliance actually mean for advice quality?
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The Fairness Impossibility Is Not a Bug
Every AI fairness debate is secretly a values debate disguised as a technical question.
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The Four Layers of Every AI Agent
Interaction, inference, orchestration, tooling. The boundaries between them must be enforcement points, not design principles.
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The Specificity Trap
Adding detail to a deliverable doesn't fix credibility — it creates new interrogation targets.
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Why AI Demands Experiments
Most technology decisions can be reasoned through. AI solution design can't — the domain is too empirical, too fast-moving, and too non-linear for theory alone.
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The Treadmill and the Loop
Getting ahead of AI best practices is a treadmill. The durable skill is testing assumptions faster than they expire.
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Enterprise AI Agents: The Transformation Is Organisational, Not Technical
The companies that win with AI agents aren't deploying the most agents — they're redesigning their organisations to work with them.
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When LangGraph Earns Its Keep
LangGraph is the SAP of agent orchestration — powerful at scale, overkill for most. Here's the line.
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Your AI Pipeline Is Probably MapReduce
Most AI workflows are parallel-then-aggregate, not agent graphs. Knowing the difference saves you from framework theatre.
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The Knowledge That Disappears When You Try to Capture It
Enterprise AI keeps promising to capture institutional knowledge. The most valuable kind resists capture by design.
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What AlphaSense Charges Ten Thousand Dollars For
I built an AI landscape intelligence pipeline for zero marginal cost. Here's what it does and what it can't.
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The Eval Gap
The scarce AI skill isn't building — it's knowing if what you built actually works.
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The Session Boundary Is Why You Still Don't Have AI Agents
The gap between AI assistants and AI agents isn't about reasoning capability — it's about whether the thing can survive your laptop closing.
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LLM evals aren't data science
Evaluating LLM systems requires judgment, not statistics. That shifts who's qualified to do it — and where the gap is in most organisations.
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Consulting Is Mostly About Reducing Uncertainty
Clients hire consultants to solve problems. What they're actually paying for is the reduction of a particular feeling. The distinction matters.
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When the Platform Is Mature, the Architect's Job Changes
The hardest phase of AI architecture isn't building the stack. It's the moment after the stack is built and eighteen teams start making independent decisions on top of it.
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The Upstream Constraint Pattern
In digital transformation, the bottleneck is almost always upstream of where the pain is felt. Mox is the cleanest case study.
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Building My Own Consulting Toolkit Before Day One
Most consultants arrive at a new firm and learn their tools from colleagues. I tried something different.
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The Real Reason Mox Won (and What It Means for AI Transformation)
Mox didn't win because they hired better designers. They won because they had no legacy to fight. The pattern applies directly to AI transformation.
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What Makes a Great AI Consultant (Beyond Technical Skills)
The most dangerous person in an AI consulting engagement knows how the model works but has never sat in a credit committee.
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Banking DS to AI Consulting: What the Transition Actually Teaches You
The operational instincts built in production banking don't belong in the past. They're exactly what makes a practitioner-turned-consultant useful.