ai-strategy-co-thinker

name	ai-strategy-co-thinker
description	Use when AI Strategy Co-Thinker is needed to produce a decision-ready strategy for social-media or digital-marketing work; use `ai-readiness-diagnostic` when its narrower outcome is requested.
metadata	{"portable":true,"compatible_with":["claude-code","codex"]}

AI Strategy Co-Thinker

Use When

• Use this skill when the requested outcome is specifically a decision-ready strategy and the supplied brief falls within ai strategy co-thinker.

Do Not Use When

• Use ai-readiness-diagnostic when its narrower output is the real deliverable; do not use this skill as a generic substitute.
• Do not use it to publish, send, spend, alter a live account, or make unsupported legal, platform, performance, or certification claims.

Required Inputs

Artefact	Source/provider	Required?	If absent
AI marketing use-case brief, intended human control point and success measure	Requester or approved brief	Yes	Stop and request the missing decision context.
Brand voice, offer facts, constraints and approvals	Client source pack or authorised owner	Conditional	State assumptions; do not invent names, prices, results or approvals.
Performance, platform or research evidence used for claims	Traceable export, URL, document or named source	Conditional	Issue a qualified finding and identify the evidence needed.

Capability and Permission Boundaries

Default to read-only: inspect supplied material and report findings. Editing, publishing, contacting people, spending, or changing live systems requires separate explicit authority. Minimum capabilities are read access to supplied files and search across the authorised evidence set. Use only the files, tools, accounts and evidence made available for the engagement, expose every unassessed check, and obtain explicit authority before any mutation.

Degraded Mode

Fallback: if files, network access, platform data, language review or production tools are unavailable, return the narrowest useful qualified decision-ready strategy; mark unavailable checks not assessed and never convert them into a pass.

Decision Rules

Choice	Action	Failure or risk avoided
Data readiness, AI maturity and risk support the proposed operating level	Choose the lowest viable automation level and define its human approval gate.	Automating an unsafe or unevaluable marketing process.
A required fact or approval is missing	Stop that claim or action; request it or use an explicit placeholder.	Fabricated facts, implied consent or unauthorised publication.
Evidence is partial but a useful draft is possible	Deliver a qualified draft with gaps and the next verification step.	Treating an unassessed requirement as passed.

Workflow

1. Confirm the exact decision-ready strategy, consumer, market, channel and approval boundary; route to ai-readiness-diagnostic if it is the closer match.
2. Inventory supplied facts, source provenance, constraints and missing inputs; stop if the objective, audience or authority is unknowable.
3. Select the domain method and record the material decision behind it before drafting.
4. Produce the smallest complete decision-ready strategy; keep facts traceable and placeholders visibly unresolved.
5. Test the result against the decision table, domain quality criteria and anti-slop gate; recover by narrowing or qualifying unsupported portions.
6. Deliver the artefact with evidence, assumptions, unassessed checks and the next approval or verification step.

Outputs

Artefact	Consumer	Observable acceptance condition
Decision-ready strategy	Requester, client reviewer or delivery team	The decision-ready strategy addresses the named audience and objective, records assumptions, and passes the skill's domain checks without invented facts.
Decision and gap note	Approver or next workflow	Names the chosen route, evidence used, unresolved inputs and any action requiring authority.

Evidence Produced

Evidence	Format	Acceptance condition
Finding-to-source register and unassessed-check list	Inline table, checklist or linked source note	Every material claim, decision and unavailable check is traceable.

Quality Standards

• Preserve the domain guidance and East African market context below; replace it only when the requester names another market.
• Use British English unless the target language or market requires otherwise, and verify names, figures, quotations and platform rules before use.
• Make the key choice visible, cover failure and edge cases, and keep the result ready for its named consumer.
• Run the repository's anti-ai-slop ship gate; a blocking factual, cultural, safety or permission defect stops release.

Anti-Patterns

• Writing before the objective and audience are known. Fix: stop and obtain the missing brief fields.
• Reusing a neighbouring skill's template because the headings look similar. Fix: route by the requested decision-ready strategy, not vocabulary overlap.
• Adding a price, result, quotation, platform limit or cultural claim without a traceable source. Fix: verify it or qualify/remove it.
• Treating missing access, evidence or native-language review as approval. Fix: mark the check not assessed and narrow the result.
• Publishing, sending, spending or changing a live account from drafting authority alone. Fix: obtain explicit action-specific authority and retain the approval record.

References

• ai-readiness-diagnostic is the nearest routing comparison for this skill.
• Repository agent guide defines the engine-wide market, safety and anti-slop gates.

Use this skill when the right strategic answer is not yet clear. AI is engaged as a dialogue partner — asking questions, surfacing blind spots, generating competing directions, and stress-testing assumptions. The human consultant selects, refines, and owns all final recommendations.

Required Input

Before beginning, gather the following:

1. Client business name — exact trading name
2. Industry — sector, sub-sector, and primary revenue model
3. Country/city — default: Uganda (specify city if relevant: Kampala, Mbarara, Jinja)
4. Current strategic challenge or question — the specific problem the strategy must solve; one or two sentences
5. Available context documents — paste or reference: client brief, audit report, audience personas, competitor analysis
6. Deadline for strategy delivery — date the final strategy document is due to the client

Co-Pilot vs Co-Thinker

The core distinction from Farri and Rosani (2025):

Mode	When to use	What AI does
Co-Pilot	You know what you want and need it faster	Drafts, summarises, formats, rewrites
Co-Thinker	You are not yet sure of the right answer	Challenges assumptions, generates options, maps blind spots

This skill is exclusively for Co-Thinker mode. The consultant does not yet have the answer; AI helps find it through structured dialogue.

For Co-Pilot drafting tasks — writing captions, formatting reports, producing first drafts — use prompt-engineering-library instead.

Multi-Step Dialogue Sequence for Brand Strategy

Run this five-step conversation before writing any strategy document. Paste AI responses into a working document as you go; these become the evidence base for the strategy.

Step 1 — Context brief

"Here is the client situation: [paste brief]. Summarise the core marketing challenge in one sentence."

Use the AI's summary to check your own framing. If the AI names a different problem than you expected, explore why before proceeding.

Step 2 — Stakeholder mapping

"Identify the 5 most important stakeholders for this brand's social media success. For each, what do they want, and what do they fear?"

Include internal stakeholders (owner, sales team) and external ones (customers, community, regulators). Fear is as strategically important as desire.

Step 3 — Pain point table

"Create a table of the top 5 unmet customer needs this brand could address through social media. Include: need, current solution, gap, emotional driver."

Review the output against the client brief and audience personas. Strike any row that contradicts known data; annotate rows that align.

Step 4 — Red flags

"What are the 3 most dangerous assumptions in this strategy brief? What would need to be true for each assumption to hold?"

This is the most valuable step. Assumptions that seem obvious are the ones most likely to sink a strategy. Document every flag — even if you decide to proceed, you are doing so with open eyes.

Step 5 — Strategic options

"Suggest 3 distinct strategic directions for [client]. For each: describe the approach, the primary audience it serves, the key risk, and the first action."

Do not skip to this step. The value of the options depends on the quality of the context built in steps 1–4.

MVOSSTE Workflow with AI

Apply the MVOSSTE framework (Randazzo, 2024) at every strategy stage. Use the prompt templates below; document each prompt and its output before moving to the next stage.

Stage	AI prompt template
Mission	"Draft 3 mission statement options for [client] in [industry] in Uganda that reflect [values]. Each under 20 words."
Vision	"Write a 5-year vision for [client] assuming [growth scenario]. Bold but credible."
Objective	"Generate 5 SMART social media objectives for [goal] over [timeframe]. Include metric and baseline."
Situation	"Conduct a SWOT analysis for [client] in [industry] in Uganda. Be specific — avoid generic points."
Strategy	"Suggest 3 social media strategy options for achieving [objective]. For each: approach, target audience, key channel, primary risk."
Tactics	"List 10 specific content tactics for [strategy] with a UGX [budget] monthly budget. Prioritise by expected impact."
Execution	"Create a 30-day action plan for [tactic]. Week-by-week milestones with named owner roles."

Each stage builds on the previous. Do not generate tactics before the strategy stage is agreed. Do not write execution plans before tactics are prioritised.

Job-to-be-Done Framing

Shifts the brief from "what should we post?" to "what job is our audience hiring this content to do?" (Randazzo, 2024).

Prompt:

"Using the Jobs-to-be-Done framework, what job is [client's target audience] in Uganda hiring social media content to do for them? List 3 functional jobs, 3 emotional jobs, and 3 social jobs."

Once the AI returns a list, audit the existing content strategy against it:

• Which jobs does the current content serve?
• Which jobs are unserved or underserved?
• Is there a mismatch between the content the brand is producing and the job the audience needs done?

Use this audit to justify content pivots or new content pillars in the strategy document.

Campaign Risk Mapping

Use AI to identify and stress-test assumptions before any campaign launches (Farri and Rosani, 2025). Run in three steps:

Step 1 — Assumption inventory

"List all the assumptions embedded in this campaign plan. Be exhaustive."

Do not filter at this stage. Include obvious assumptions alongside hidden ones.

Step 2 — Criticality ranking

"Rank these assumptions from most to least critical. Which, if wrong, would cause the campaign to fail?"

Focus on the top three. A campaign can tolerate minor assumption failures; it cannot survive critical ones.

Step 3 — Validation method

"For the top 3 critical assumptions, suggest the cheapest way to validate or invalidate each before the campaign launches."

Validation methods might include: a soft-launch post to test audience response, a WhatsApp poll to a sample of existing customers, a one-week pilot with a reduced budget. Include the validation plan in the campaign brief so the client knows the strategy has been tested before full deployment.

Prompt Footnoting Practice

Professional standard for AI-assisted strategy work (Randazzo, 2024). Every AI-generated output used in a client document must be cited.

Format:

Generated using Claude, prompt: "[exact prompt text]", [date].

Add this footnote directly below any table, list, or paragraph drawn from an AI output. This practice:

• Enables clients to audit, reproduce, or modify outputs independently
• Protects the consultant if outputs are later questioned or found to be inaccurate
• Creates a record of the strategy's development process — useful for retrospectives and case studies
• Demonstrates professional rigour to sophisticated clients

Never omit the footnote to make a deliverable look cleaner. If a client asks where an insight came from, the answer must always be available.

Quality Gate

AI generates options; the human consultant selects, refines, and takes responsibility. The following rules are non-negotiable:

• No direct delivery — never present AI-generated strategic options directly to a client without human editorial review. Every AI output must pass through the consultant's judgement before it reaches a client.
• Add market knowledge — layer in local market knowledge, client relationship context, and professional experience that AI does not have access to. A strategy that could have been written without knowing the client is not a strategy; it is a template.
• Flag unverifiables — if an AI output makes a claim that cannot be verified against a source, a known data point, or direct client knowledge, flag it before including it in a deliverable. Do not include unverifiable claims in client documents.
• Own the recommendation — the strategy document is signed by the consultant, not by the AI. The consultant is responsible for every recommendation, regardless of which tool was used to generate it.

Quality Criteria

• Multi-step dialogue sequence (all 5 steps) completed before any strategic recommendation is drafted
• MVOSSTE workflow applied with AI at each stage — all prompts documented with outputs
• Job-to-be-Done framing applied to at least one strategic question in the brief
• Campaign risk mapping completed — top 3 critical assumptions identified and a validation method assigned to each
• All AI-generated outputs reviewed and edited by the human consultant before any content reaches the client
• Prompt footnoting applied throughout the strategy document — every AI output cited with exact prompt and date
• Final strategy document reflects the consultant's professional judgement, not a compiled set of AI outputs

References

• Erné, J. (2024) The Artificial Intelligence Handbook for Management Consultants.
• Farri, E. and Rosani, G. (2025) HBR Guide to Generative AI for Managers. Harvard Business Review Press.
• Randazzo, G.W. (2024) Winning Marketing Strategies Using Generative AI. Business Expert Press.