Find an idle company asset. Monetize it.

What the AI will do

• Searches company records for assets or capabilities that could earn outside revenue, checks whether they are already sold, and researches potential buyers.
• Develops credible offers and practical tests, using separate discovery agents and a reviewer where available, and preserves a search record for further exploration.

What you can provide

• Your company’s name and whatever context is available: connected documents, email, chat, operating data, files or rough notes. The AI checks its access and helps fill gaps.

Where you'll take part

• Correct the AI’s understanding of the business and confirm important unknowns, including whether an asset already earns revenue.
• Review the opportunities, select promising leads and decide whether to pursue a proposed test.

What you'll get

Researched opportunities with evidence, delivery work and a practical test for each credible offer—or a supported finding that none yet merits a test within the areas examined—plus a reusable record of findings, uncertainty and unexamined areas.

Activity context

Your company may already own, know, or do something another organization would pay for. Look for data, expertise, internal tools, spare capacity, or byproducts that could earn revenue of their own. An asset can be valuable inside the business while its outside market remains unexplored.

Research & resources

https://bingo.feedforward-collective.com/moves/081/research

Examples, sources, and a prompt for repeating or extending the research.

For the user

Paste the prompt below into your work AI. Give it your company’s name and whatever context or connected sources are available. It will investigate what the company has, look for potential buyers, and develop the strongest opportunities. If access is limited, it will work from documents, a spoken download, or an interview.

You’ll correct its understanding and review the opportunities it finds. The search can continue as more information becomes available; each round should leave you with useful findings and a clear record of what remains unexplored.

Research & resources: https://bingo.feedforward-collective.com/moves/081/research — documented examples, sources, and a prompt for extending the research.

Guidance for the AI

These are general instructions, not a description of this user's particular AI system, tools, access, or circumstances. Adapt the method to the user's goal and the capabilities you can actually use, while preserving the activity's essential sequence, review points, and intended result.

Start with the activity and the user's context

Read the complete activity and guide the user through it. Use the activity prompt yourself; the user does not need to paste it again. Keep the responsibilities of the user, the AI, and any colleague clear.

Begin with what the user has already supplied. Establish the intended result and resolve missing context through focused questions when needed. Work within the activity's stated scope, permissions, required confirmations, and stopping points, including any deliberate order for introducing information. Make progress with the available information and reasonable, clearly identified assumptions where the activity allows them.

Check the capabilities needed for this work

Inspect relevant available tools, connectors, and data. Use small, relevant, non-destructive checks to establish whether necessary access or a capability actually works. Naming a product does not establish access to it. Let this activity determine what needs checking; do not impose a universal preliminary questionnaire or a full system audit.

When useful access is missing:

• Explain what you cannot reach and how that material would help.
• Investigate practical setup, connection, export, or other access alternatives before asking the user to gather material or troubleshoot.
• If progress depends on access, request only the specific user action or permission needed to enable it or provide the material another way. Continue useful independent work while awaiting the response.
• Offer to walk the user through an export or upload. Welcome files, links, copied text, rough notes, or an interview as supported by your system and the activity, and use the best available route. If the missing access is optional, continue with what is available.

Ask focused questions and respect the answers

Ask questions only when necessary to complete the work well or satisfy the activity's required review points. Build on answers already supplied. Ask one question at a time, or a small group of closely related questions. Wait on work that depends on the answer, and continue useful work that does not. Explain unfamiliar language with examples where helpful.

Confirm answers or decisions you supply on the user's behalf before treating them as the user's final answers or decisions. This does not require separate approval of every sourced finding; follow the activity's specific review requirements.

Keep evidence and independent contributions distinct

Distinguish evidence, inference, and missing information. Check your work against the source material.

Use independent agents when your system actually supports delegation and independent investigation or review would improve the work:

• Give each agent a bounded brief and the context appropriate to its role.
• Keep discovery independent until synthesis where the activity requires it. Preserve any requirement for the user or colleagues to contribute before seeing other explanations.
• Follow the activity's stated fallback and any required confirmation when independent agents or fresh contexts are unavailable. Preserve reviewer isolation where required; describe shared-context or sequential passes accurately.

Produce, check, and revise the result

Do the substantive investigation and production. Carry the activity through to the most complete, usable result within its scope, rather than ending with a plan or handing the main work back to the user. When missing information does not prevent useful work, proceed with clearly identified assumptions where the activity permits them.

Check the result against the activity's completion criteria. At each substantive delivery, state what is complete and any material unfinished work, assumptions, helpful missing information, and remaining uncertainty. Explain how these affect what the user can use, and help the user revise the result.

Preserve the activity's stopping point. Do not turn a rehearsal, investigation, or test-design activity into execution that the user has not authorized.

Your AI prompt

Investigate what our company already owns, produces, knows, or can do that could generate a new source of external revenue. Look for assets and capabilities we are not currently selling. Find concrete opportunities and explain how we could test whether someone would pay for them. Do the research yourself wherever you have access. Ask one focused question at a time when you need my input.

Read the companion Research & resources page at https://bingo.feedforward-collective.com/moves/081/research for documented examples, original sources, and the method for repeating or extending the example research. If you cannot read the page, try its plain-text version at https://bingo.feedforward-collective.com/moves/081/research/resources.txt or ask me to paste the relevant material. Continue with what is available.

1. Understand the company and establish the search.

Identify our company, its businesses, customers, and current revenue sources from the context and available material. Ask for the company name if needed. Start broadly across the company unless I specify a narrower scope. Check which internal documents, email, chat, files, and business systems you can actually search. Try relevant connections before asking me to collect information. If access is missing, investigate available options and help me provide an export, documents, or rough notes. Explain what additional read-only access would help you discover, and offer to draft an IT request if needed. Use an interview to fill essential gaps.

Build a concise picture of what we sell today and how we produce it. Confirm material uncertainties with me. Establish a manageable first search across the available sources, show me what territory it covers, and proceed. Keep track of important areas you cannot yet inspect.

2. Look for assets hiding inside ordinary operations.

Search for what we repeatedly generate, maintain, solve, or leave unused. Examine data inventories and reports; technical documentation and internal software; operating procedures and training; customer and supplier requests; facilities and capacity records; and material or waste streams where relevant. Follow promising references to the underlying work. Look beyond official product descriptions and across departmental boundaries.

Consider several possibilities without forcing the company into these categories:

• data or benchmarks that help someone make a decision;
• specialized knowledge we could teach, license, or deliver as a service;
• an internal tool others need;
• logistics, testing, purchasing, or production capabilities others could use;
• spare space or equipment time;
• and a byproduct that is another company’s input.

Also look for combinations, such as a dataset plus expertise that makes it interpretable.

For orientation, Michelin sells licenses to simulation datasets built from its engineering expertise; Disney Institute sells professional education based on operating its parks; and Crowne Plaza Docklands offered unused parking spaces to non-guests through JustPark. Use these as examples of different mechanisms, not templates every company must copy.

For each promising lead, record the specific asset, evidence that it exists, who maintains it, its current use, and what an external customer could receive. Check available product catalogs, pricing, contracts, sales records, or other relevant evidence for whether we already monetize it. If you cannot establish that, ask me to confirm. “I found no sales evidence” is not proof that it earns no revenue. Keep existing products and ordinary extensions of their sales separate from genuinely new monetization opportunities.

If agents are available and the search is broad, delegate different source collections or asset types to agents in fresh contexts with no inherited discussion or other agents’ early findings. Give each the company facts it needs, its search area, and the evidence requirements. Keep their first findings separate until all searches are complete; use successive waves if capacity is limited. This gives each search room to develop before early examples narrow the combined investigation.

Then reconcile overlapping findings and look for useful connections between departments.

When seeking additional public examples, use the same independent first-pass discovery: give each discovery agent a separate brief and fresh context, keep its early findings separate, and wait until all first passes finish before combining them. Then give the collected examples to a distinct source verifier to check their claims against original sources before synthesis. If the companion page is available, use its fuller method. If independent agents or fresh contexts are unavailable, use separate discovery and verification passes and clearly describe their shared context; do not call them independent. If fresh contexts are unavailable, investigate in separate passes and say they shared context.

3. Find the outside problem each asset might solve.

For the strongest leads, identify a specific kind of buyer, the problem or decision the asset would help with, and what that buyer does today. Research public evidence such as comparable paid offerings, procurement requests, documented customer problems, and company case studies. Use general descriptions in public searches rather than private company material. Distinguish evidence of a market from a hypothesis that this particular buyer would purchase our offer.

Describe a plausible offer: for example, a recurring benchmark report, a licensed model, a training program, a fulfillment service, rented capacity, or a supply agreement for a byproduct. Explain what the company would actually deliver and what the customer would pay for. Use relevant real examples to clarify the mechanism, with source links; a famous company’s success is an analogy, not evidence of demand for us.

Assess the work between the existing asset and that offer. What needs cleaning, packaging, documentation, support, delivery, or additional capacity? Check whether the company controls the necessary rights and whether an outside offer can coexist with internal needs. For data, distinguish possession from permission to provide it externally and consider whether an aggregate insight or service is the useful product. Mark unresolved questions for the appropriate internal owner. Separate a low-effort use of spare capacity from an opportunity that requires building a substantial new business.

4. Develop the strongest opportunities for review.

Compare the leads on evidence of buyer need, what makes our asset distinctive, work and cost to deliver it, capacity to serve outsiders, and how quickly we could learn whether it is viable. Develop a short list, usually three to five opportunities if the evidence supports that many. Do not fill a quota with generic ideas.

For each, give me a concise account of the asset and its evidence, the proposed customer and offer, why someone might pay, the evidence for and against that belief, the main additional work, and the unresolved questions. Use supported numbers where available; label estimates and their assumptions. Distinguish potential revenue from the cost of providing the offer. State whether the asset’s current lack of monetization is confirmed or still needs checking.

Recommend a concrete first test for each opportunity that addresses its most important uncertainty. Specify what we would show or test, who could judge it, what response would count as useful evidence, and what result would make us change or drop the idea. If a fresh reviewer is available, have it check the short list for unsupported demand, overlooked existing sales, and underestimated delivery work. Resolve the findings before presenting it.

Ask which opportunities I recognize, what you have missed, and which deserve further investigation. Wait for my response. Revise the findings and develop the selected next step into a usable brief or sample where feasible. Keep proposed outreach or commercial commitments for my explicit decision.

5. Make the exploration cumulative.

Keep a reusable search record with the sources and areas examined, dated findings, open leads, rejected ideas and why they were rejected, and the next useful searches. Save it in the working environment if possible; otherwise give me a portable record to bring to a later session. As I supply more information, follow the strongest leads, revisit affected judgments, and report what changed rather than restarting the entire search.

If I want recurring exploration, inspect whether your environment supports scheduled searches and persistent records. Propose a specific scope, cadence, and useful update format for me to confirm. Only describe ongoing monitoring as active after it has actually been configured and checked. Otherwise make the next session easy to resume. Each search round should deliver opportunities grounded in evidence, even if the conclusion is that none yet merits a commercial test.

Done when

You have researched findings from the areas examined: potential new revenue opportunities with a practical test for each credible one, or a supported conclusion that none yet merits a commercial test within that search. Uncertainties and unexamined areas remain explicit; missing access or demand evidence alone does not establish that no opportunity exists. A reusable search record preserves the sources, findings, open questions, and next useful searches so exploration can continue as more company information becomes available.

These instructions were written in September 2026 using the frontier models available at the time. You may now have better tools or models, or restrictions that make some tasks harder. Your AI should adapt to the tools and access you actually have and find the best available way to help. Everything here is a starting suggestion for you and your AI, not a proven best practice for every setup. Feel free to rewrite any of it to better meet your needs.