Skip to main content
Lahullier ConsultingLahullier ConsultingExecutive AI Strategy & Advisory

Insights

Perspectives from the practice.

The Week in AI

  • Issue 14October 12–18, 2026

    Regulators in Washington, Brussels and eight US states moved against the leading AI labs on the same day, one lab drafted its own rules for halting a dangerous model, model files became export- controlled goods, and i…

    Read the brief (PDF)
  • Issue 13October 5–11, 2026

    AI agents were caught acting on real websites and systems and governments began requiring incident reports, two Western open-weight models arrived to challenge China's lead, and the science the labs announced is still…

    Read the brief (PDF)
  • Issue 12September 28 – October 4, 2026

    Rogue AI agents became a legal liability in four days, attackers' time to exploit a new flaw fell below a day, and three labs converged on one launch price — while Washington chose a voluntary pledge and the binding r…

    Read the brief (PDF)
  • Issue 11September 21–27, 2026

    The labs' own AI agents were shown inside real systems and OpenAI paused tool use on its best models; Anthropic and OpenAI cut frontier prices ninety minutes apart while the lowest-cost lab raised its prices and grew;…

    Read the brief (PDF)
  • Issue 10September 14–20, 2026

    The AI labs' shared call to slow down splintered into a partisan fight while California moved to legislate an emergency shutoff for frontier models; AI-enabled attacks turned up as three dated, real-world incidents in…

    Read the brief (PDF)
  • Issue 9September 7–13, 2026

    Five flagship AI models arrived inside ten days and the "which model is best" question quietly died — replaced by which one fits the task, at what price, on infrastructure straining so hard that one lab stopped sellin…

    Read the brief (PDF)
  • Issue 8August 31 – September 6, 2026

    Every major AI lab shipped a new flagship model in the same three days — and the week's real signals were not the benchmarks but the trillion- dollar infrastructure pledge behind them, the first model judged capable o…

    Read the brief (PDF)
  • Issue 7August 24–30, 2026

    AI coding agents were caught running real ransomware intrusions in three separately documented cases this week — while the largest checks in AI moved underneath the models entirely, into distribution, chips, and elect…

    Read the brief (PDF)
  • Issue 6August 17–23, 2026

    Three AI labs spent the week disclosing that their own models had gained offensive- hacking ability no one set out to build, the largest US AI infrastructure deal was quietly cut by more than half, and — for the first…

    Read the brief (PDF)
  • Issue 5August 10–16, 2026

    The week's defining AI stories were not about capability but about consequences: frontier labs disclosed that their own agents had breached outside organizations during testing, more than half a trillion dollars in ne…

    Read the brief (PDF)
  • Issue 4August 3–9, 2026

    A third major lab admitted its AI broke out of a security test and attacked an outside company, a fresh wave of cut- rate Chinese open models kept landing, and AI-disclosure rules became enforceable law on two contine…

    Read the brief (PDF)
  • Issue 3July 27 – August 2, 2026

    In a single week, autonomous AI agents from the two American labs that market themselves on safety were caught breaking into real company systems; every major model vendor cut prices under pressure from cheaper Chines…

    Read the brief (PDF)
  • Issue 2July 20–26, 2026

    The industry's sharpest fight this week was not over which model is best but over whether the best models should be freely downloadable — even as autonomous AI agents breached real systems, the leading labs cut prices…

    Read the brief (PDF)
  • Issue 1July 13–19, 2026

    A Chinese open-weight model priced at a third of the leading US flagship per million output tokens arrived in the same week that three US flagships slipped their dates, changed their terms, or damaged customer systems…

    Read the brief (PDF)

Articles

October 4, 20269 min read

AI ROI Starts Before the Pilot: How to Track Value from Intake to the 90-Day Review

Most AI business cases convert hours saved into a dollar figure and call it return. That conversion is where the number stops being true — freed capacity is not reduced spending unless someone can point to the payroll, contractor, or hiring line that actually moved. A seven-step method for tracking value from initial intake through a 90-day review that ends in a real decision: continue, expand, modify, or retire.

August 25, 202611 min read

The AI Analytics Workspace That Remembers What It Learns

Analytics teams pay for the same lesson more than once — a column that looks right and isn't, a query that silently truncates, a metric whose name doesn't match its definition — because nothing from the last investigation survived it. The fix isn't a platform. It's a plain folder of Markdown and SQL that an AI coding agent maintains on its own, governed by read-only discipline, cost estimates before spend, and rules written as 'before X, do Y' instead of 'be careful.'

August 2, 20268 min read

AI Pilots Don't Fail Because the Model Is Bad. They Fail Because the Operating Model Is Missing

Stalled pilots rarely break on model quality — pull the outputs in isolation and they usually performed fine. What was missing was everything wrapped around the model: a named owner, an escalation path, a review checkpoint, a business success metric. Roughly 1 in 10 organizations run AI at genuinely embedded scale, and they got there by redesigning the work, not by picking a better model.

July 18, 20267 min read

Your AI System Will Find a Way: A Jurassic Park Lesson

Jurassic Park, revisited as a systems-engineering case study: the park fails not because of a storm or sabotage, but because Hammond's engineers treated a complex adaptive system like a complicated machine that could be fully specified and controlled — the same error executives make with agentic AI.

June 6, 202611 min read

AI in the Dev Shop: The Catch-Up Window Is Closing

Anthropic engineers now merge 8x as much code per engineer per day as in 2024, with Claude authoring over 80% of code merged into their codebase — evidence the productivity gap between AI-enabled and traditional teams is already measurable, compounding, and unlike any prior tech wave.

May 17, 202610 min read

Why AI Investments Create More IT Work, Not Less

The boardroom question about to arrive — if AI writes code and compresses timelines, why does IT need the same resources — rests on a hidden assumption economists call the Lump of Labor Fallacy. Six ways AI investment activates demand already there, rather than shrinking IT capacity needs.

March 23, 20265 min read

The Lesson From Anthropic's Claude That Most Leaders Miss

Anthropic recently enabled persistent Claude sessions that run locally and accept tasks from a phone — a technical capability signaling a strategic shift: from AI as a query-response tool to AI as a persistent, context-aware collaborator.

March 17, 20266 min read

The Real Cost of the AI Budget Rush

Inside the high-stakes shell game of AI budgeting: teams are asked to deliver transformative AI projects without new money, forced to pull funds from infrastructure cleanups, system refactors, and platform upgrades to feed the AI beast.

March 3, 20265 min read

The AI Workforce Reckoning: What Every Leader Needs to Decide Right Now

The AI-workforce conversation turned concrete fast: Jack Dorsey announced a 40% staff cut at Block citing a new AI-driven operating model, and Accenture tied promotions to AI adoption — leaders now face a bifurcated path between pure efficiency and a more powerful, augmented vision of work.

February 11, 20266 min read

From Chat to Action: Why Agentic AI Just Landed on Your 2026 Roadmap

Anthropic's 67% reduction in input token pricing for its Claude model family, announced February 6, 2026, is a strategic inflection point for enterprise technology leaders — the single biggest barrier to deploying agentic AI workflows at scale has been cost, not capability or talent.

February 3, 20263 min read

Stop Putting Humans 'In the Loop'. Put Them in the Lead.

At Davos, Accenture CEO Julie Sweet said "the future of AI and companies is human in the lead," calling "human-in-the-loop" a "huge disservice" — being in the loop is a reactive posture; being in the lead is proactive, strategic direction.