LTSP26 Replay Edition – Pre-Conference Downloads Showcase

If your AI strategy answers all sound polished, confident, and strangely generic, you may not be getting insight - you may be getting trendslop. Francis Wade talks with Angelo Romasanta, the ESADE assistant professor whose research shows that LLMs often steer managers toward the same trendy recommendations, even when the underlying business situations call for something very different. Angelo breaks down how his team tested strategy questions across multiple management tensions - from explore vs. exploit to centralized vs. decentralized to automate vs. augment - and found a consistent pattern: AI tends to favor the sexier, socially desirable answer. Even small changes like reordering options or tweaking wording can shift the recommendation dramatically.

Most leaders are getting AI strategy wrong in one of two ways: they either sprinkle it everywhere, or avoid it completely. Francis Wade shows why both approaches fail, and why the real fix is not better prompting, but workflow-first clarity. At the Long Term Strategy Conference 2026, Francis breaks down the hidden reason AI creates “trend slop” inside strategy development, especially when teams treat a complex corporate planning process like a simple writing task.

Most companies are asking the wrong AI question. The real issue is not whether AI belongs in strategy, but where it belongs, where it doesn’t, and why most planning processes break down before they ever get useful. Francis Wade lays out a practical way to redesign strategy creation for the AI era, using the Endpoint Method.

The Hardest Part of Strategy Is Thinking Backward From the Future Most strategy plans fail at the exact moment teams stop thinking backward. Francis Wade shows why backcasting is the hardest stage of the endpoint method—and why handing it to AI can turn a real strategy into polished planning theater. If you lead strategy, sit in the C-suite, run planning retreats, or use AI to speed up decisions, this episode shows the danger in letting a model fill in the gaps.

Francis Wade and Joe Pine explore why many companies, especially banks, keep reaching for the same tired fixes even when innovation is clearly needed. The conversation centers on Pine’s progression of economic value and how it helps leaders see beyond products and services to experiences and transformations.

This session explores why strategy creation cannot be treated like factory-floor process improvement, especially as AI begins reshaping how organizations plan and decide. Francis Wade explains that strategy work is infrequent, ambiguous, and insight-driven, so teams need a different discipline from the one used for repetitive production systems. He introduces three lenses for the next 12 months: bottleneck-first thinking, decision-making optimized for brilliance rather than efficiency, and insight generation as the real engine of strategy.

Most companies know category design could transform their strategy. Almost none can afford the traditional way of doing it. Kevin Maney and Mike Damphousse reveal how AI is changing that math, turning what used to take expensive advisors and months of workshops into something smaller teams can actually use. They introduce Caddy, an interactive AI persona being built to help teams create category strategy without starting from a blank page or paying multiple six figures.

AI is about to make scenario planning fast, cheap, and usable — and that changes strategic planning for everyone. Mike Jackson reveals how organizations can move from slow, consultant-heavy workshops to dynamic foresight that helps leaders act before the future hits. For decades, scenario planning has been trapped in a broken model: expensive experts, months of work, and four extreme outcomes that often end up on a shelf.

AI can help you build a better strategy - but only if you use it to challenge your thinking, not replace it. Most companies are about to make the same mistake with AI: benchmarking everyone else, copying the market, and calling it strategy. Felipe Bovolon shows why that path leads to trend slop, parity, and zero real advantage - and what to do instead if you want a strategic plan that actually creates long-term value.

Prep Video #1 - Francis Wade reframes the Long-Term Strategy Conference 2026 around a simple but important idea: this is not passive screen time, it is an interactive experience designed to produce insight and, potentially, transformation. He explains why that distinction matters, how old webinar habits can sabotage the experience, and what participants should do differently before and during the conference.

This video explains how to get real value from the Long Term Strategy Conference 2026 by arriving with an actual strategic problem, not a vague aspiration. Francis Wade argues that the personas only become useful when you give them specific context, constraints, and data to work with. The core message is simple: if you want a transformational outcome, do the preparation first. A generic prompt gets a generic response, but a real, current business problem can unlock deeper questioning and more useful insight.

Prep Video #3 - Francis Wade explains why the conference’s AI interactives are designed to resist the “instant answer” habit most people bring from everyday LLM use. This episode matters because it reframes frustration, impatience, and the urge to shortcut as part of the process rather than signs that something is broken. He uses a fictional attendee, Marcus, and a personal coaching story to show why real strategy work takes committed time, reflection, and the right expectations.

(1:55) How can leaders prove that strategy creation is improving when the final verdict may be years away? Francis Wade argues that strategy can’t be managed like a factory—and introduces a practical alternative for spotting problems while the work is still underway. The core idea is SPEAR: Strategy Process Engineering for Analysis and Refinement. Rather than relying only on speed, cost, polished documents, or satisfaction scores, SPEAR focuses on identifying defects in the strategy process, addressing them at key stages, and measuring again. Wade also explains how AI can help on specific tasks where it may address a known problem, without assuming it should run the entire strategy process.