The Next Big Plan: From an Attention Platform to a Trusted Artificial Intelligence Cross-Domain Collaboration Network

Document positioning

This document redesigns the next-stage plan based on the central contradiction revealed in the conversation. The original concept emphasized artificial intelligence, open-source ecosystems, international exchange, education, communities, and industry–academia collaboration, with the ambition to build influence and integrate resources. However, if execution still depends on unconfirmed resources, vague future opportunities, unlimited unpaid work, person-centered decisions, and disregard for professional execution, the larger the vision, the greater the risk borne by participants.

Therefore, the next big plan will no longer treat attention, titles, occasions, or relationships as its primary outcomes. It will establish collaboration infrastructure that converts vision into needs, budgets, responsibilities, delivery, learning outcomes, and fair returns. The following six interconnected Amazon-style PRFAQs can be piloted independently and integrated in sequence into a complete plan.

“Amazon-style PRFAQ” here refers only to the method of writing a future press release first and then testing the plan backward through frequently asked questions. It does not mean Amazon or any of its affiliates participates in, supports, or endorses this plan.

First PRFAQ

Program name: Public AI Problem Lab

One-sentence summary

Do not build a massive platform first. Select real user problems and complete small artificial-intelligence solutions that can be validated within twelve weeks.

Press release

Taipei, scheduled release date: April 1, 2027. The Public AI Problem Lab today announced completion of its first twelve-week pilot, bringing together technologists, domain practitioners, user representatives, and education partners to address three clearly scoped public and industry problems.

The lab changes the old sequence of building a brand, gathering attention, inviting important people, and waiting for concrete work to appear. Every project begins with a user problem confirmed through interviews and describes the current process, specific pain points, affected people, data limitations, suitability of artificial intelligence, and alternatives that do not use artificial intelligence.

The first round has no more than twelve people per project and lasts no longer than twelve weeks. Each project must have a service recipient, product owner, technical owner, domain reviewer, data steward, confirmed budget, delivery definition, risk list, and stop conditions. If a problem is not suitable for artificial intelligence, the team may use automation, process improvement, knowledge organization, or an existing tool instead of adding complexity to chase a popular topic.

Public outcomes include the problem statement, prototype, test results, limitations, cost, user feedback, and the decision on whether to continue. Incomplete projects also preserve the original objective and reasons; the starting point cannot be completely rewritten when results are below expectations.

The first-phase success criteria are that all three pilots complete testing with real users, at least two demonstrate improvement in time, quality, or accessibility, all data has a legal source and clear use, every public statement links to evidence, and no unconfirmed international collaboration or important person’s name is used as a substitute for product value.

“The next big plan is not writing artificial intelligence into more slogans. It is giving one real user a measurable improvement in one real process,” the program team said.

Frequently Asked Questions

Q: Who are the primary users?

A: The first phase serves small institutions, education teams, and public-service organizations that need to improve data organization, knowledge retrieval, case classification, content maintenance, or cross-organization collaboration.

Q: How are problems selected?

A: Selection is based on user pain, impact, data availability, the ability to test within twelve weeks, and risk—not on whether the topic is popular or easy to attract media attention.

Q: Must every problem use artificial intelligence?

A: No. Artificial intelligence is a means, not the goal. If rule-based automation, existing software, or process improvement is more appropriate, the team should choose the simpler method.

Q: Who is responsible for technical errors?

A: Responsibility is distributed by role. The technical owner handles system quality, the data steward handles sources and permissions, the product owner confirms needs and publication, and the domain reviewer checks practical risks. No one may claim to bear all risk while leaving actual decisions and work to others.

Q: How are outcomes measured?

A: Compare before and after operating time, answer quality, error rate, completion rate, user satisfaction, and maintenance cost. Event attendance, social posts, and photos are not primary measures of effectiveness.

Q: What is the North Star metric?

A: Among users who complete testing, how many are willing to continue using the solution after understanding its limitations and cost.

Q: What are the stop conditions?

A: If legal data cannot be obtained, real users are unavailable, risk exceeds benefit, maintenance costs cannot be carried, or improvement cannot be verified after twelve weeks, the project stops or narrows.

Second PRFAQ

Program name: Open-Source Trusted Component Library

One-sentence summary

Turn reusable code, documentation, tests, governance templates, and failure experience from each project into public components that other teams can adopt independently.

Press release

Taipei, scheduled release date: July 1, 2027. The Open-Source Trusted Component Library today launched formally, initially providing twelve reusable artificial-intelligence and collaboration components, including needs-interview templates, data-source inventories, model-evaluation methods, risk checklists, user-consent templates, deployment guides, and maintenance records.

In the past, open-source communities often treated events, talks, and calls to action as their main outputs. People who actually wanted to use a component could not find installation instructions, version information, licensing, limitations, or maintainers. The new library requires every published item to have an executable example, appropriate and inappropriate use cases, test results, license, contributors, maintenance responsibility, and a method for stopping maintenance.

The library does not equate a large membership with a healthy community. Each core component has a clear maintainer and backup person. Contributors can inspect their records and receive attribution for actual work. If a company or institution incorporates a community outcome into a commercial service, it must follow the license and any agreed return terms.

The first-phase success criteria are that at least six components are successfully adopted by users outside the original team, every component has basic tests and documentation, major issues receive a response within five business days, and no component depends on one person alone for deployment or maintenance.

Frequently Asked Questions

Q: How is the library different from an ordinary code repository?

A: In addition to code, it includes needs, data, tests, risks, consent, deployment, maintenance, and exit documents so that technology can be used safely rather than merely displayed.

Q: Who can contribute?

A: Anyone who agrees to the contribution rules. Tasks, review standards, and maintenance requirements are public. People do not need private relationships or a long period of unpaid performance to qualify.

Q: Is maintenance work paid?

A: Core maintenance that is fixed and essential should have a budget or a clear exchange. Short-term volunteer contributions need a scope and time limit. Formal operations cannot be placed permanently on free labor.

Q: How is attribution handled?

A: Records cover design, code, documentation, testing, review, and maintenance according to actual contribution. The external representative does not automatically become the main author of every component.

Q: What happens to components that are no longer maintained?

A: Publish their status, last supported version, alternatives, and archive date so users do not mistakenly believe ongoing support exists.

Q: What is the North Star metric?

A: The proportion of users outside the original team who successfully adopt a component without relying on private assistance.

Q: What are the stop conditions?

A: If a component has no users, documentation remains broken, risks go unhandled, or maintenance depends entirely on one unpaid person, stop promotion and archive it.

Third PRFAQ

Program name: Trusted Talent Academy

One-sentence summary

Give learners technical capabilities, work samples, judgment methods, and work records they can continue using after leaving teachers and platforms.

Press release

Taipei, scheduled release date: October 1, 2027. The Trusted Talent Academy today announced its first hands-on artificial-intelligence and open-source collaboration course. The course does not use titles, proximity to the center, or unconfirmed travel as its primary appeal. Its commitments are the curriculum, guidance, work samples, feedback, work boundaries, and portable outcomes.

The first course lasts twelve weeks and covers needs interviews, data governance, prototype design, model evaluation, open-source collaboration, risk communication, and outcome presentation. Every learner completes a verifiable work sample, a method explanation, two rounds of peer review, and one real-user test.

The academy clearly distinguishes practice from formal work. Practice has learning objectives, demonstrations, feedback, and a workload limit. If a learner’s outcome is used in formal operations, public publishing, or a commercial service, the platform must obtain separate authorization and handle attribution and returns according to prior rules.

The academy does not promise jobs, recommendations, overseas travel, or a seat with important people. If an additional opportunity actually exists, it is announced separately under public conditions. Declining an extra activity does not affect course outcomes, certification, or eligibility to apply fairly in the future.

The first-phase success criteria are that at least 85% of learners complete a work sample, at least 80% find the actual workload consistent with the advance description, at least 70% use the methods again within three months, and all learner outcomes used formally have authorization and attribution.

Frequently Asked Questions

Q: How do you distinguish learning from free labor?

A: Learning must include a clear objective, demonstration, practice, feedback, and an outcome the learner can take away. If the platform receives most of the value and the work enters daily operations, it should be treated as formal work.

Q: How are mentors selected?

A: Based on verifiable experience, content accuracy, feedback ability, available time, and interest disclosure—not attention, titles, or relationships with the founders.

Q: Can learners question mentors?

A: Yes. Pointing out data errors, methodological limitations, or conflicts of interest does not lower evaluation. One outcome of education is that learners can independently examine authoritative claims.

Q: Are instructor titles provided?

A: Only people with the corresponding teaching capability and actual teaching responsibility receive a role name that matches the scope. A title does not come before capability, authority, and responsibility.

Q: Can learners leave partway through?

A: Yes. They may leave after necessary handover. Existing work and contributions remain under the original terms, and leaving is not interpreted as a lack of ambition or loyalty.

Q: What is the North Star metric?

A: The proportion of learners who can independently use the methods, show their work, and evaluate new opportunities three months after leaving the course.

Q: What are the stop conditions?

A: If the course continues to treat operational work as learning, mentors cannot provide feedback, work samples cannot demonstrate capability, or learner rights cannot be protected, pause enrollment.

Fourth PRFAQ

Program name: Cross-Border Collaboration Evidence Layer

One-sentence summary

Accurately distinguish contact, exchange, advice, intention, resource commitment, formal collaboration, and shared accountability so internationalization is built on facts rather than imagination.

Press release

Taipei, scheduled release date: January 15, 2028. The Cross-Border Collaboration Evidence Layer today launched formally, providing status management, bilingual confirmation, resource disclosure, travel governance, and public-description rules for cross-city, cross-language, and cross-organization collaboration.

The system classifies relationships into eight states: public-event contact, information exchange, advice, expression of interest, awaiting internal approval, resource investment, formal collaboration, and shared accountability. Each state has appropriate public wording, necessary evidence, an owner, and an update date.

One meeting means only that a meeting occurred. One appearance is not endorsement. Saying “willing to talk again” is not existing collaboration. Any content using a person’s name, title, organization name, photo, logo, or quotation must match the authorized purpose and period.

Cross-border projects provide bilingual summaries, read-back of key conditions, and time for dissent. Language differences are not simplified into judgments of ability, and a lack of objection is not interpreted as complete consent. Partners are evaluated through needs understanding, delivery quality, and reliability rather than accent, nationality, or performance at an occasion.

Travel opportunities are formally announced only after budget, selection method, insurance, responsibilities, and outcome requirements are confirmed. Resources still being applied for may only be used for an interest survey and cannot require participants to invest heavily in advance or make irreversible arrangements.

The first-phase success criteria are that all public relationship descriptions link to consent records, major status changes are updated within five business days, every trip has definite cost information, and partners’ mutual understanding of responsibilities reaches 90% or higher.

Frequently Asked Questions

Q: Will accurate descriptions weaken the international image?

A: They may reduce short-term drama but improve long-term credibility. Genuine international capability comes from cross-language understanding, reliable delivery, risk management, and continued collaboration.

Q: Can group photos be published?

A: Consent for the public scope is required, and the relationship description must be accurate. Permission to take a photo is not permission to describe it as collaboration or endorsement.

Q: How are language differences handled?

A: Use bilingual documents, translation, read-back, and written confirmation. Communication efficiency should be improved through methods rather than stereotypes about the other party’s professional value.

Q: Can recruitment begin while a subsidy is still under application?

A: Interest can be collected, but the status must be marked unconfirmed. Full subsidy cannot be promised, and it cannot be exchanged for long-term unpaid work.

Q: How are international outcomes measured?

A: Measure shared delivery, problem improvement, knowledge transfer, later use, and repeat collaboration rather than only travel count, event prestige, or photos.

Q: What is the North Star metric?

A: The proportion of cases in which both parties have the same understanding of relationship status, resources, responsibilities, and next steps.

Q: What are the stop conditions?

A: If resources are not confirmed by the deadline, the parties understand their responsibilities differently, data and safety conditions are insufficient, or public image exceeds actual collaboration, pause the project.

Fifth PRFAQ

Program name: Fair Resource and Opportunity Exchange

One-sentence summary

Distribute funding, travel, teaching, representation, recommendations, and project opportunities through clear criteria instead of using private closeness, public praise, or unpaid work as a hidden admission ticket.

Press release

Taipei, scheduled release date: April 1, 2028. The Fair Resource and Opportunity Exchange today completed its first pilot, publicly managing conditions, selection processes, conflicts of interest, and result explanations for projects, teaching roles, travel, grants, representation, and collaboration places.

The exchange classifies resources into four types: public application, task-based recommendation, partner designation, and emergency assignment. Each type must state purpose, minimum conditions, evaluators, conflicts of interest, fee range, decision date, and complaint method. A direct beneficiary cannot decide a resource allocation alone.

Participants do not need long-term free work, private dinners, public praise, or loyalty to a single person to obtain information. Important opportunities are made public within reasonable limits. People who are not selected can learn task-related reasons without being labeled as flawed in character or lacking vision.

The first-phase success criteria are that all major opportunities have explainable conditions, all conflicts of interest are recorded, participants rate procedural fairness at 80% or higher, and people who decline extra work can still apply for future opportunities under the same standards.

Frequently Asked Questions

Q: Must every opportunity be completely public?

A: Not necessarily. Confidentiality, time sensitivity, or a partner’s designation can limit the scope, but the selection basis and conflicts of interest must still be recorded. Personal preference cannot be disguised as objective procedure.

Q: Should long-term contribution receive priority?

A: It can be considered when related to the task, but it should be evaluated through actual capability and reliable records. Total unpaid labor cannot become a loyalty score.

Q: Who handles complaints?

A: Someone not directly involved in the original decision. A complaint checks procedure and facts; it does not promise that the result will change.

Q: What if a partner designates a candidate?

A: That can be respected, but it must be labeled as partner designation rather than public competition. The designated person must still have the necessary capability.

Q: What is the North Star metric?

A: Whether qualified participants believe that, even without private relationships, they have a real opportunity to obtain information and receive a fair evaluation.

Q: What are the stop conditions?

A: If standards are created only after results appear, direct beneficiaries control decisions for a long period, or people who refuse are continually excluded implicitly, stop allocation and reset governance.

Sixth PRFAQ

Program name: Centerless Trusted Collaboration Network

One-sentence summary

Enable artificial intelligence, open source, education, and international collaboration to continue operating under shared rules when founders or core figures are absent.

Press release

Taipei, scheduled release date: October 1, 2028. The Centerless Trusted Collaboration Network today announced that its first city node completed three rounds of delivery validation and has begun transferring the method to a second independent team.

The city node integrates the Public AI Problem Lab, Open-Source Trusted Component Library, Trusted Talent Academy, Cross-Border Collaboration Evidence Layer, and Fair Resource and Opportunity Exchange. Each plan begins with a need and has confirmed minimum resources, role divisions, delivery evidence, contribution records, dissent channels, and stop conditions.

The node does not use a large membership, advisor list, or personal attention as its primary evidence of success. External representation, resource approval, complaint facilitation, data management, and outcome publication cannot remain concentrated in one person. Core roles have terms, handover, and conflict-of-interest disclosure; important decisions preserve reasons and dissent.

Members can collaborate directly under clear data, confidentiality, authorization, and commercial agreements. All relationships do not have to return to the center. The platform does not own people’s futures or automatically include every later outcome in the founder’s personal brand.

A second city begins only after one node completes three consecutive delivery cycles, full costs are sustainable, core roles have rotated, the node can operate for four weeks while any one core person pauses, and another team can use the method independently.

The first-phase success criteria are that at least 90% of established work continues under the rules while core figures pause, at least 75% of participants are willing to collaborate again, everyone who leaves retains lawful outcomes and credit records, and the second team can complete its first small project with limited support.

The program team said: “A truly large plan does not build a larger center. It lets more people obtain information, build capability, deliver work, and share outcomes fairly without depending on the center.”

Frequently Asked Questions

Q: Does centerless mean there is no leadership?

A: No. There are still roles, decision-makers, and final accountability. Information, resources, narrative, and complaints are simply not permanently concentrated in one person.

Q: What role does the founder retain?

A: Authority matching actual contribution, legal ownership, and formal responsibility, but not permanent control over all relationships, outcomes, and future direction.

Q: How are core members selected?

A: By stable delivery, professional judgment, governance capability, willingness to hand over work, interest disclosure, and a record of respecting dissent—not public praise or private closeness.

Q: Is direct collaboration by members the same as bypassing the platform?

A: If it does not violate a specific agreement, direct collaboration can demonstrate that the platform has reduced collaboration costs. If the platform wants revenue from introductions, it must establish transparent rules in advance.

Q: How do you prevent a new inner circle from forming?

A: Publish important access points and conditions, set role terms, rotate representatives, preserve newcomer tasks, and regularly check whether information, stage, resources, and administrative work remain concentrated among a few people.

Q: What is the North Star metric?

A: When any core person is absent, whether commitments, decisions, delivery, complaints, data, and outcome distribution still operate reliably.

Q: What are the stop conditions?

A: If regular operations still rely on unlimited unpaid work, core people cannot hand over work, dissenters are excluded, full costs have no source, or the method cannot be used independently by another team, do not expand.

Overall sequence

The six proposals must be validated in sequence rather than packaged as six large brands at once.

Phase one runs the Public AI Problem Lab, proving through one real problem that the team can move from need to delivery.

Phase two organizes reusable outcomes in the Open-Source Trusted Component Library so code, documents, tests, governance, and failure experience can be used by others.

Phase three establishes the Trusted Talent Academy, turning validated methods into a learning path with a curriculum, feedback, and portable work samples.

Phase four activates the Cross-Border Collaboration Evidence Layer so external relationships, travel, resources, and public statements do not exceed the facts.

Phase five introduces the Fair Resource and Opportunity Exchange, distributing teaching, travel, recommendations, representation, and project opportunities through clear conditions.

Only phase six establishes the Centerless Trusted Collaboration Network, integrating the first five capabilities into nodes that can be handed over, rotated, and replicated across cities.

First 90-day actions

During the first 15 days, stop announcing new plans without a clear need, budget, owner, and deadline. Organize existing commitments, collaboration names, unconfirmed resources, unpaid amounts, work rights, and data-use status.

Before day 30, interview at least ten potential users, select one specific problem, and complete the problem statement, current process, user impact, and alternative that does not use artificial intelligence.

Before day 45, confirm a pilot team of no more than twelve people and list each role’s authority, work, hours, compensation or volunteer status, outcome rights, and exit method.

Before day 60, complete data sources, minimum prototype, test method, risk list, budget, and stop conditions. Sponsorship, travel, and collaboration that remain unconfirmed may only be marked as possibilities.

Before day 75, have real users complete the first round of testing and record successes, errors, limitations, maintenance burden, and improvements.

On day 90, publish a factual report covering the original goal, actual completion, full cost, contribution distribution, user feedback, unfinished responsibilities, and the decision to continue, narrow, or stop.

Shared North Star metric

The shared North Star metric is the proportion of participants and users who, after understanding outcomes, limitations, costs, and collaboration conditions, still freely choose to use or collaborate again without titles, personal favors, unconfirmed travel, important people, or central pressure.

Supporting metrics include user-problem improvement rate, delivery completion rate, workload forecast variance, on-time fee rate, renewed consent for scope changes, attribution accuracy, cross-border understanding alignment, perceived fairness of opportunity allocation, skill use after three months, independent component adoption rate, and dependence on any single person.

Shared stop conditions

Any plan must pause if it continues to attract investment through unconfirmed travel, recommendations, positions, titles, or contact with important people; depends on unlimited unpaid labor; dismisses actual execution; reduces partners or specific groups to negative stereotypes; concentrates successful credit while distributing failure; uses names, photos, data, or work without consent; suppresses dissent; causes people who leave to lose outcomes; or expands before stable delivery exists.

A complete stop must handle unpaid amounts, deliverables, data preservation or deletion, attribution, public status, corrections, and future contact. Stopping is not betrayal of the vision; it is governance that protects participant rights and platform credibility.

Final vision

The next big plan is not packaging ordinary things as a heroic myth or having more people build a platform for free while waiting for benefits that have not been confirmed. It is infrastructure that turns artificial intelligence, open source, education, and international collaboration into real user value.

Within this system, vision cannot replace need, attention cannot replace delivery, titles cannot replace capability, an occasion cannot replace collaboration, exposure cannot replace fair return, politeness cannot replace consent, trust cannot cancel verification, and education cannot require dependence.

It allows leaders to set a broad direction while requiring them to respect professional detail, disclose limitations, and bear the consequences of decisions. It allows a platform to build a brand while requiring the brand to remain faithful to facts. It allows participants to pursue experience, networks, and opportunities while protecting their right to refuse, question, leave, and take lawful outcomes with them.

The next big plan worth demonstrating is not how many important names enter the blueprint. It is how many real problems improve, how many components can be adopted independently, how many learners can create value after leaving teachers, how many international partners are willing to collaborate again under clear conditions, and whether the whole system still operates reliably when core figures are absent.