# pawlowski-strategy-stack-ai-market-research-tension-map-2026-03-30

## Veille

Method article by Alex Pawlowski (The Strategy Stack, #151, March 30, 2026) proposing a major epistemic shift in *market research*: no longer collecting static reports but maintaining a ***living decision surface*** — a continuously evolving model of market dynamics. Central contribution: the **Tension Map**, which maps *contradictions and pressure points* (gaps between expectation and delivery, price tolerated without being embraced, incumbents without emotional resonance) rather than market share. Tooling in three modes (Discovery / Tension / Decision), a 7-step workflow, and an orchestrated tool stack (Perplexity for expansion → Claude for depth/continuity → ChatGPT for iteration → Multi-agent for challenge). Implicit reference: Richards Heuer's (CIA) *Analysis of Competing Hypotheses* method.

## Titre Article

How to Use AI for Market Research (Step-by-Step Guide) — AI Market Research Tension Map

## Date

2026-03-30

## URL

https://thestrategystack.substack.com/p/ai-market-research-tension-map

## Keywords

Alex Pawlowski, The Strategy Stack, AI market research, Tension Map, living decision surface, Discovery Mode, Tension Mode, Decision Mode, Observation-Tension-Decision framework, 7-step workflow, market question precision, raw signals, unpolished sources, structural analysis, stress-testing, alternative perspectives, updatable market model, Perplexity expansion, Claude continuity, ChatGPT iteration, multi-agent disagreement, analyst critic strategist roles, AI note-taking case study, premium pricing tolerated, incumbents emotional resonance, friction accepted, weak vs strong research questions, Analysis of Competing Hypotheses, Richards Heuer, CIA intelligence methodology, corpus persistence, Claude Projects, compounding analytical value, dynamic strain fields, dynamic markets, decision surface, polished summaries trap, vague questions trap, ungrounded confidence

## Authors

Alex Pawlowski (auteur de la newsletter Substack *The Strategy Stack*, focus stratégie et IA opérationnelle).

## Ton

**Profile**: A method article signed on Substack by an independent consultant/strategist. Pedagogical-conceptual guide format aimed at strategy, product management, market research, and consulting professionals. Target audience: product leaders, heads of strategy, competitive intelligence consultants, founders seeking to industrialize their competitive watch. English-speaking audience, not tech-native but comfortable with consumer AI tools (ChatGPT, Claude, Perplexity).

**Style**: A structuralist-prescriptive voice, in the tradition of quality Substack essays (Ben Thompson's Stratechery, Packy McCormick, Lenny Rachitsky). Pawlowski establishes his framework through systematic opposition to existing practices: traditional market research = collection (bad) vs AI-native market research = maintaining an operational system (good). Crisp sentences, grounded concrete examples (AI note-taking tools, SaaS evolution), crafted metaphors (*"dynamic strain-fields rather than static competitive landscapes"*, *"living decision surface"*).

**Crafted metaphors**: the **Tension Map** as a mapping of frictions rather than positions; markets as *strain-fields* (mechanical stress fields); the role of research as an *operational system* rather than a discrete project. Vocabulary borrowed from **strategic intelligence** (Heuer methodology, CIA), signaling methodological rigor above the average AI-marketing content.

**Authority**: built through a dual posture — (1) clear prescription (7 named steps, 3 named modes, the signature Tension Map framework) and (2) reliance on the strategic-analysis tradition (CIA / Heuer). No heavy institutional credentials visible — authority through the coherence of the proposed system. Pawlowski cites his own earlier essays on AI operating models, proprietary data, and agentic workflows, signaling a consolidated corpus on AI-native enterprise strategy.

**Epistemic stance**: neither techno-utopian nor alarmist. Pawlowski takes up the diagnosis that *"the bottleneck is no longer information but its interpretation"* — typical of the 2026 moment (report saturation + AI's capacity to structure). He pushes a strong operational thesis: value lies not in the output (the report) but in the **system that produces and updates the output**. It is a *market research* application of the *AI-native* doctrine circulating in 2026 (cf. compounding engineering at Every, context flywheel at Tessl, semantic agent per Seale).

## Pense-betes

- **Date / source**: March 30, 2026, *The Strategy Stack* (Substack), article #151. Author: **Alex Pawlowski**.
- **Starting diagnosis**: three fundamental problems with traditional market research: 1. **Information overabundance** creates noise, not clarity. 2. **Delayed reports** — describe the past, not emerging movements. 3. **Insight rarely translated into action** — analysis dies before the decision.
- **Central thesis**: shift from the *static report* to the ***living decision surface*** — an evolving model of market dynamics, maintained as an operational system. The market is treated as a *dynamic strain-field*, not a *static competitive landscape*.
- **Tension Map (main contribution)**: mapping of **contradictions and pressure points** rather than market share. Four dimensions illustrated:
- *"Where users want more than products deliver"* — expectation/delivery gap.
- **Misalignment** between price and perceived value.
- **Strong incumbents but without emotional resonance**.
- **Friction accepted only for lack of a better alternative**.
- **Visualization**: the Tension Map illustrates the *opportunity spaces* between simple and complex product positioning.
- **Three research modes**: | Mode | Function | |------|----------| | **Discovery Mode** | Baseline — who the players are, which patterns are visible | | **Tension Mode** | Locate dissatisfaction, unmet expectations, underserved segments | | **Decision Mode** | Convert interpretation into strategic action |
- **7-step workflow**: 1. **Define the market question** — precision > generality. 2. **Collect raw signals** — prioritize *unpolished* sources (reviews, documentation, transcripts) over synthesized reports. 3. **Build the Tension Map**. 4. **Use AI for structural analysis** — patterns, clustering, contradictions. 5. **Stress-test** interpretations — challenge, alternative perspectives. 6. **Convert tensions into strategic decisions**. 7. **Preserve the output** as an *updatable market model* — not a one-off project but an asset that compounds over time.
- **Orchestrated tool stack**: | Tool | Phase | Role | |-------|-------|------| | **Perplexity** | Discovery | Expansion — broaden awareness, spot blind spots, validate global patterns | | **Claude** | Depth / continuity | Large context window, preserve nuance across contradictory signals | | **ChatGPT** | Iteration / speed | Reframing, generating alternative structures, translating observation → usable models | | **Multi-agent** | Validation | Productive disagreement via assigned roles (analyst, critic, strategist) |
- **Recommended sequence**: Perplexity (expansion) → **Claude (corpus analysis)** → ChatGPT (structuring) → Multi-agent (validation).
- **Weak vs strong research questions**:
- **Weak**: *"What are the trends?"*
- **Strong**: *"Where does pricing feel tolerated rather than embraced?"*
- Principle: question quality determines 80% of analysis quality.
- **Observation-Tension-Decision framework**: structured progression for translating market signals → strategic moves. Each line of analysis passes through the three stages.
- **Application case — AI note-taking tools**:
- Users value the *automation promise* but encounter *post-meeting accuracy* problems.
- Premium pricing tolerated in teams but perceived as unfair individually.
- Incumbent trust competing with emerging excitement.
- **Stress-testing — questions to ask systematically**:
- *"What evidence would invalidate the interpretation?"*
- *"Which weakest assumptions merit scrutiny?"*
- *"What would skeptical competitors dispute?"*
- **Corpus persistence**: keep the source material stable in **Claude Projects** (or equivalent) to create *compounding analytical value* — analysis is enriched with each cycle instead of starting from scratch.
- **Living model maintenance**: saving outputs enables iterative refinement, turning research into a living asset.
- **Four common failure modes**: 1. **Vague initial questions** → polished but superficial outputs. 2. **Over-reliance on polished summaries** rather than raw signals. 3. **Validation skipped** → ungrounded confidence. 4. **Insights never translated into decisions** → lost leverage.
- **Major methodological reference**: Richards Heuer's ***Analysis of Competing Hypotheses*** (ACH) — a **CIA** analysis methodology for evaluating several competing hypotheses in parallel. Pawlowski transposes this adversarial analysis protocol to AI-native market research.
- **Self-citations (Pawlowski)**: earlier essays on AI operating models, proprietary data, agentic workflows. Consistent with a consolidated corpus.
- **Connection to the watch dossier**:
- A piece of **strategic transposition** of agentic theses into the *market research / strategic intelligence* domain. Fills a gap in the watch dossier (so far dominated by coding agents and organizational topics).
- **Tension Map** = the strategy-side equivalent of the **Knowledge Graph** (Seale 2025-05-30 *Philosophy Eats AI*) or the **CDLC** (Debois/Tessl 2026-02-19) applied to the market.
- **Living decision surface** = direct parallel to the **Context Flywheel** (Debois/Tessl 2026-02-26) on the coding side and **Compound Engineering** (Shipper/Klaassen 2025-12-11) on the delivery side.
- **Orchestrated Perplexity → Claude → ChatGPT → Multi-agent stack** = the *market research* counterpart of the coding agents' **agentic stack** (Karpathy 2026-04-29, Osmani 2026-04-19, Trivedy 2026-03-10).
- **Stress-testing with adversarial roles** = equivalent to Anthropic's **planner/evaluator split** (cited by Osmani) applied to strategic analysis. *"Separating generation from evaluation outperforms self-evaluation."*
- **CIA / Richards Heuer / ACH** = grounding in a pre-AI analytical tradition that gives the framework methodological rigor above the average *content marketing / AI-strategy* piece.
- The **"polished summaries trap" failure mode** corroborates Karpathy's *"raw signals over polished apps"* thesis (MenuGen vs Nanobanana, 2026-04-29): value lies in the raw material, polish hides the pattern.
- **To draw on for**: executive presentations on AI-native competitive intelligence; product / strategy team training; consulting arguments on industrializing strategic intelligence; design of annual strategic review processes.

## RésuméDe400mots

Alex Pawlowski publishes in *The Strategy Stack* a method guide that repositions *market research* for the AI era. His diagnosis opens with three flaws: information overabundance that creates noise, delayed reports describing the past, and insight rarely translated into action. His thesis: value no longer lies in the static report but in a **living decision surface** — an evolving model maintained as an operational system. Markets are treated there as *dynamic strain-fields*, not as fixed competitive landscapes.

His central contribution is the **Tension Map**: instead of mapping competitors and market share, it identifies contradictions and pressure points — *"where users want more than products deliver"*, price/value misalignment, powerful incumbents lacking emotional resonance, friction accepted for lack of an alternative. The Tension Map reveals *opportunity spaces* invisible to classic analyses.

Three research modes structure the method: **Discovery Mode** establishes the baseline (players, visible patterns); **Tension Mode** locates dissatisfaction and underserved segments; **Decision Mode** converts interpretation into action. The **7-step workflow** operationalizes this: (1) define a precise question, (2) collect *raw signals* (reviews, docs, transcripts — not synthesized reports), (3) build the Tension Map, (4) AI-driven structural analysis, (5) stress-test through adversarial perspectives, (6) convert tensions into decisions, (7) preserve as an *updatable market model*.

The tool stack is orchestrated by phase: **Perplexity** for expansion (Discovery), **Claude** for depth and continuity (large context, contradictory signals), **ChatGPT** for iteration speed (reframing, alternative structures), **multi-agent** for *productive disagreement* via assigned roles (analyst, critic, strategist). Question strength is central — *"Where does pricing feel tolerated rather than embraced?"* (strong) vs *"What are the trends?"* (weak).

Pawlowski illustrates this with the AI note-taking tools market: the automation promise is appreciated but post-meeting accuracy is problematic, premium pricing is tolerated in teams but resented individually, incumbent trust competes against emerging excitement. **Stress-testing** is a ritual step: *"what would invalidate the interpretation?"*, *"what would skeptical competitors dispute?"*

Four failure modes loom: vague questions producing polished but superficial outputs, over-reliance on *polished summaries* at the expense of raw signals, skipped validation creating ungrounded confidence, insights never translated into decisions. **Corpus persistence** in Claude Projects and **living model maintenance** turn research into a compounding asset. Methodological reference: Richards Heuer's (CIA) *Analysis of Competing Hypotheses*, transposed to AI. Market research becomes a continuous operational system, not a succession of discrete projects.

## GrapheDeConnaissance

- Alex Pawlowski —publie→ The Strategy Stack (ORGANISATION, 0.96)
- Alex Pawlowski —a_créé→ Tension Map (METHODOLOGIE, 0.97)
- Tension Map —s_applique_à→ contradictions et points de pression marché (CONCEPT, 0.96)
- Tension Map —s_oppose_à→ analyse parts de marché classique (METHODOLOGIE, 0.93)
- Living decision surface —remplace→ rapport statique de market research (CONCEPT, 0.95)
- AI market research —utilise→ 7 étapes / 3 modes (CONCEPT, 0.96)
- Perplexity —s_applique_à→ Discovery / expansion (METHODOLOGIE, 0.94)
- Claude —s_applique_à→ profondeur / continuité corpus (METHODOLOGIE, 0.95)
- ChatGPT —s_applique_à→ itération / structuration (METHODOLOGIE, 0.94)
- Multi-agent setup —permet→ productive disagreement (CONCEPT, 0.93)
- Raw signals —surpasse→ polished summaries (CONCEPT, 0.95)
- Question précise —améliore→ qualité de l'analyse (CONCEPT, 0.94)
- Stress-testing (Pawlowski) —affine→ interprétations (CONCEPT, 0.95)
- Corpus persistence —permet→ compounding analytical value (CONCEPT, 0.93)
- Tension Map —est_basé_sur→ Analysis of Competing Hypotheses (ACH) (METHODOLOGIE, 0.85)
- Richards Heuer —a_créé→ Analysis of Competing Hypotheses (ACH) (METHODOLOGIE, 0.97)
- Analysis of Competing Hypotheses (ACH) —fait_partie_de→ méthodologie d'analyse de la CIA (METHODOLOGIE, 0.96)
- Vague initial questions —permet→ outputs polis mais superficiels (CONCEPT, 0.94)
- Decision Mode —permet→ conversion des tensions en décisions stratégiques (CONCEPT, 0.95)
- Marché —est_instance_de→ dynamic strain-field (CONCEPT, 0.92)

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