Published analysis.
Strategy, applied AI, and the records behind high-stakes decisions — with trade policy as a worked example. Analysis that demonstrates capability, not content that fills a marketing calendar.
The Data Moat: Why Proprietary Data Wins
Google's AI doesn't want your keywords anymore. It wants your source data. Zero-click search broke the old SEO playbook — here is the business case for building a data moat instead, and what it actually takes.
The compliance risk of ungrounded LLM outputs
Ungrounded generation produces fluent, confident text with no verifiable source behind it. The measured error rates are high enough that the exposure is no longer theoretical — and the fix is architectural, not a matter of better prompting.
Defending AI-assisted decisions to a regulator
When a regulator, tribunal, or auditor asks how an AI-assisted decision was reached, the defence is not the model — it is the record. Here is what a defensible file contains, what Canada's Directive on Automated Decision-Making requires, and how to build the chain before you need it.
How to audit what your AI actually cited
If you cannot reconstruct which source produced an AI-assisted answer, you cannot defend the decision built on it. Here is what an AI citation audit checks, why grounding changes the error profile, and the record-keeping regulators and enterprise buyers increasingly expect.
The public-record platform blueprint: how FOI data was structured to be citable
A technical account of how End The Wait Ontario turns freedom-of-information responses and government records into a platform that institutions and AI systems cite: the data model, the source-chain rules, the publishing architecture, and what we would do differently.
When AI answers questions about your organization, whose data does it use?
Search engines and AI answer systems now decide whose version of the record becomes the answer. Most organizations' data isn't structured to be found, checked, or cited — so something weaker gets cited instead. Here is what citers actually need, a five-step method to fix it, and a public case study anyone can verify.
CUSMA wasn't renewed on July 1. Here's what actually changed
On July 1, 2026, the United States declined to renew CUSMA for a further sixteen years. The agreement did not end — it shifted to an annual review running through 2036. For Canadian manufacturers, a one-time event just became a standing risk.
Canada's AI for All strategy: what it means for adoption, sovereignty, and trusted AI
Canada launched its national AI strategy — AI for All — on June 4, 2026, built around trust, opportunity, and sovereignty, with a target to lift business AI adoption from just over 12% to 60% by 2034. Here is what it means for businesses and public institutions, and how to adopt AI without losing control of the record.
Navigating US tariff escalation: a strategic playbook for Canadian exporters
The 2025-2026 US tariff escalation cycle has fundamentally altered the risk calculus for Canadian exporters. This analysis maps the tariff timeline, identifies the most exposed sectors by HS code, and provides an operational framework for supply chain diversification, CUSMA origin optimization, and market repositioning.
CUSMA 2026 review: what Canadian manufacturers need to know now
The CUSMA/USMCA joint review creates a narrow window of concentrated policy risk for Canadian manufacturers with US supply chain exposure. Most companies are not preparing. Here is what the review actually changes, and what to do about it.
Open-source research: a practical framework for corporate decision-makers
Open-source research has moved from specialist functions to corporate decision-making. This analysis covers the full research cycle as applied to private-sector operations — from collection planning through dissemination — with specific tools, data sources, legal boundaries, and illustrative scenarios.
Why Canadian industry is unprepared for the coming trade disruption
Canada has allocated significant government funding toward trade disruption response. But the companies that need it most have no internal capability to assess their exposure, develop strategy, or execute against it. This is a structural gap, not an information gap.
Open-source research and the future of competitive intelligence
Open-source research — drawing on filings, patents, trade data, and other public records — is becoming an essential competitive discipline for private-sector organizations navigating complex information environments.
Intelligence briefings
Field notes on strategy, applied AI, and turning records into decisions. Published when it matters, not on a schedule.