AI-generated concept art of a Wallbound arena. The image shows a towering multi-level arena filled with black ropes, hanging nets, neon lighting, and dense fog. Players move across the walls and suspended structures instead of the floor, creating a futuristic vertical battleground designed around climbing, endurance, and team combat.
Wallbound is a vertical team sport played inside a tall neon arena filled with ropes, nets, ledges, bridges, and foggy maze-like rooms. Players climb, hang, swing, brace, grapple, and fight to stay attached to the walls while trying to eliminate the other team.
The Arena
The game takes place in a multi-level indoor arena, usually two to three stories tall. The walls are covered with black ropes, cargo nets, hanging grips, and flexible climbing routes. Different maps can include hallways, rooms, bridges, corners, narrow passages, and open vertical chambers.
The atmosphere is dark, foggy, and futuristic, with neon lighting similar to a laser tag arena.
The Teams
Wallbound is played by two opposing teams with different rules.
The Wallbound Team
The Wallbound team cannot touch the floor.
They win if at least one player is still on the wall when the timer ends.
Their strategy is based on endurance, climbing skill, teamwork, evasion, and smart positioning.
The Hunter Team
The Hunter team is allowed to touch the floor a limited number of times.
They win by eliminating every Wallbound player before time runs out.
Their strategy is based on pursuit, pressure, grappling, route control, and coordinated attacks.
How Players Are Eliminated
Each player wears multiple removable outer layers over a base layer.
To eliminate a player, opponents must strip off enough of their layers until the player is down to their base layer.
This makes the game physical without being based on striking. Players battle through grip strength, leverage, balance, restraint, and timing.
Core Skills
Grip strength
Climbing endurance
Body control
Tactical movement
Grappling
Stamina management
Teamwork
Environmental awareness
Players must decide when to fight, when to flee, when to help a teammate, and when to conserve energy.
Strategy
The game is not only about being strong. A player who burns too much stamina early can become easy to eliminate later.
Teams can spread out across the arena, form defensive clusters, lure opponents into bad positions, block routes, or protect weaker players.
A single well-timed assist can change the entire match.
Player Styles
Different players naturally develop different roles.
Anchors are strong defensive players who can hold position for a long time.
Climbers are fast movers who travel quickly through nets and ropes.
Hunters are aggressive players who specialize in stripping layers and forcing eliminations.
Bulldozers use size and power to overwhelm groups.
Swingers use momentum, reach, and timing to attack from unexpected angles.
Winning the Game
The Wallbound team wins by surviving.
The Hunter team wins by clearing the walls.
Every match becomes a test of endurance, teamwork, strength, and adaptation inside a glowing vertical maze.
Exploring the gap between AI’s “theoretical capability” and its real-world performance.
AI has quickly become one of the most discussed technologies in everyday life. It shows up in conversations with coworkers, friends, and family. You overhear people discussing it while eating out, and it fills social media feeds with predictions about how it will reshape work and society. Much of the conversation centers on whether AI will replace human jobs, but my experience using these tools has led me to see the situation somewhat differently.
In my own work with AI systems, I’ve found them to be incredibly useful in certain areas. They excel at brainstorming ideas, expanding knowledge, summarizing large amounts of information, and organizing complex topics into more understandable formats. Used well, these capabilities can save a significant amount of time and allow people to process information much more efficiently. In that sense, AI clearly has the ability to expand human productivity and make many tasks easier.
At the same time, regular use of these tools also makes their limitations visible. One example that stands out is computation. AI systems may correctly identify the formula needed to solve a problem but still produce an incorrect result when executing the math itself. In situations where precision matters, that creates a clear need for verification. While highly specialized systems designed only for a narrow type of calculation could address this issue, doing so sacrifices the flexibility that makes general AI tools appealing in the first place.
Another limitation appears in the way AI approaches problem solving. AI often presents the first reasonable solution it generates and then continues expanding on that approach. Humans, by contrast, frequently question whether an entirely different method might produce a better result. Much of human progress comes from this instinct to challenge existing systems and reinvent processes, even when current solutions appear to work well. AI systems are trained on existing knowledge and historical patterns, but they do not independently generate the motivation to push beyond those patterns unless they are explicitly guided to do so.
Recently I encountered a visual chart circulating online that attempts to map which occupational categories AI could theoretically cover. The chart separates “theoretical capability” from “observed usage,” suggesting that AI already has the potential to perform many tasks in fields such as management, business and finance, computer and mathematical work, architecture and engineering, legal services, arts and media, and office administration. In practice, the observed use of AI appears to mirror these categories, but at a smaller scale.
Discussions surrounding the chart often emphasize that AI will not necessarily replace entire jobs, but instead automate specific tasks within them. Some commentators suggest that companies able to automate 20 to 40 percent of knowledge work will significantly outperform organizations that do not adopt these tools. Others argue that the real shift will occur as workers learn how to direct, audit, and integrate AI systems into existing workflows.
There is likely truth in parts of this perspective. AI clearly has the ability to assist with many tasks inside existing roles. However, interpreting this as evidence that AI will broadly replace workers oversimplifies how organizations and systems actually evolve.
From my perspective, the chart itself also overlooks something important. If anything, AI’s potential usefulness may be more broadly distributed across occupational categories than the model suggests. Fields such as management, architecture and engineering, life and social sciences, legal work, education, personal care, and office administration all share characteristics that make AI particularly helpful as a supporting tool. These areas often involve large quantities of information, historical knowledge, and complex interpretation, which are environments where AI’s ability to synthesize information can provide real advantages.
Office and administrative work provides a good example. Many small repetitive tasks within these roles can be automated, allowing workflows to move faster and reducing time spent on routine work. At the same time, automation tends to push human involvement toward the more complicated or unusual situations that fall outside predictable patterns. Rather than removing people from the process entirely, AI often shifts their role toward solving problems that require judgment and creativity.
Legal work presents a similar dynamic. The field contains enormous volumes of information, and AI tools can dramatically accelerate research, document review, and information retrieval. Yet small nuances in wording can determine the outcome of a case, meaning human interpretation remains essential. Education follows a related pattern as well. Many foundational tasks help people build expertise over time, and removing too many of these steps could ultimately weaken how professionals develop their skills.
One of the most important differences between humans and AI systems comes from experience. People move between organizations, industries, and social environments. Along the way they encounter ideas that have nothing to do with their immediate work but later become the source of an important breakthrough. Sometimes the insight that saves a company or creates an entirely new opportunity comes from something learned in a completely unrelated context.
AI systems, by comparison, often operate within more confined boundaries. A system trained heavily on a single organization’s data may become extremely efficient at performing tasks within that environment, but it also risks becoming limited by it. Humans introduce the unexpected connections that allow systems to adapt and evolve over time.
Because of this, I see AI not as a replacement for human workers, but as a powerful tool that works best when paired with human judgment. AI can process information, summarize knowledge, and automate repetitive digital tasks at remarkable speed. Humans contribute creativity, curiosity, and the ability to question existing approaches. Together, those capabilities can strengthen organizations far more than either could alone.
It is possible that some companies will attempt to remove large numbers of roles in pursuit of automation. If that happens, they may discover that systems relying too heavily on automation risk becoming stagnant over time. Growth often depends on experimentation, unexpected insights, and new ways of thinking that emerge from human interaction.
AI will almost certainly reshape many aspects of work, but the most meaningful changes are likely to come from how humans learn to use these systems as tools rather than substitutes. Machines can accelerate processes, but the curiosity and imagination that drive progress still belong to people.
The United States relies on individual taxpayers to accurately file federal income tax returns, yet most students graduate high school without basic procedural knowledge of how filing works, what forms to expect (e.g., W-2, 1099), how to determine whether they must file, where to access free filing tools, or what penalties apply for late or incorrect filing. This gap contributes to avoidable errors, missed benefits, and late-filing and late-payment penalties that can compound financial instability for new adults.
Federal policy should address this gap by using education and tax-code levers to expand access to practical tax-filing literacy while preserving state and local control over curriculum design. This memo evaluates four complementary approaches: (1) conditioning existing federal K-12 education funding on inclusion of minimum tax-filing competencies, (2) expanding adult tax-filing education through established adult education systems, (3) integrating community-based filing support programs as educational and quality-assurance partners, and (4) offering a limited, individual-only tax incentive for completion of a certified tax-filing literacy module.
The recommended approach is a coordinated, multi-layered strategy that establishes tax-filing literacy as a basic civic competency while providing flexible implementation pathways and practical support for both students and adults.
Introduction
Each year, millions of individuals enter adulthood and the workforce with W-2s, 1099s, and withholding statements in hand but without procedural literacy regarding federal income tax filing. Many do not know how to determine whether they are required to file, which documents are relevant, how refunds or balances due are calculated at a basic level, where to file for free, or what deadlines and penalties apply.
The consequence is not merely confusion, but avoidable noncompliance costs. Late filing penalties can accrue at approximately 5 percent per month (up to 25 percent of unpaid tax), while late payment penalties may accrue at 0.5 percent per month (also up to 25 percent). These penalties disproportionately affect new adults and lower-income filers for whom even modest financial setbacks can have cascading effects.
At the same time, the federal government implicitly expects taxpayers to navigate this system independently, despite the existence of free filing tools and assistance programs that are not widely known or consistently integrated into education systems. This disconnect highlights a structural gap between obligation and preparation.
1. Issue / Problem
Students routinely graduate without practical tax-filing literacy.
Federal income tax filing is a widespread obligation with real penalties for late or incorrect filing.
The absence of baseline education shifts risk and cost onto individuals, particularly those without access to informal guidance.
2. Background / Context
State and local governments retain primary authority over curriculum decisions; the federal role typically operates through standards-setting, guidance, and funding incentives rather than direct mandates.
The Internal Revenue Service already administers free and assisted filing options, including free filing tools and community-based assistance programs, but awareness and uptake vary widely.
3. Scope: Definition of “Tax-Filing Literacy”
For purposes of this proposal, tax education is narrowly defined as procedural literacy related to individual federal income tax filing, not comprehensive tax law or accounting instruction. Minimum competencies would include:
How to determine whether an individual must file (basic filing thresholds and dependency concepts)
Common tax documents individuals receive (e.g., W-2, common 1099 forms)
A basic explanation of withholding, refunds, and balances due
Where and how to file for free, including awareness of free filing tools and community assistance programs
Filing deadlines and a basic understanding of penalties for failure to file or pay
This scoped approach avoids overburdening curricula while ensuring practical relevance.
4. Who Is Affected / Why It Matters
New adults entering the workforce, who face filing obligations for the first time
Low-income and first-generation students, who are less likely to have informal guidance networks
Government administrative efficiency, as improved baseline literacy can reduce preventable errors, confusion, and downstream remediation costs
5. Policy Options and Analysis
Part 1: Tie Minimum Tax-Filing Competencies to Existing Federal K-12 Funding Streams
Mechanism
Use an existing federal education grant framework rather than attempting to directly mandate curriculum changes. A natural fit is the Title IV-A Student Support and Academic Enrichment program, which already supports “well-rounded education” initiatives.
What This Does
Establishes a federally defined minimum competency framework aligned with the scope outlined above
Allows states and local education agencies to determine how content is delivered (e.g., standalone unit, civics course, personal finance module)
Ties reporting or assurance requirements to existing funding streams
Advantages
More politically and constitutionally viable than a direct federal curriculum mandate
Scalable and adaptable across diverse education systems
Preserves flexibility for inclusion of state-specific tax content
Challenges / Barriers
Risk of “unfunded mandate” criticism if not paired with sufficient resources
Variation in implementation quality without model curricula or assessment tools
Anticipated Challenges
Curriculum crowding and teacher training constraints
Need for periodic updates as filing tools and processes evolve
Part 2: Adult Education Pathway
Mechanism
Leverage the existing federal-state-local adult education framework to reach individuals who did not receive tax-filing instruction in secondary school.
What This Does
Funds short, practical “Tax Filing Basics” modules through adult education providers, libraries, and workforce centers
Integrates clear referral pathways to community-based filing assistance
Advantages
Reaches adults already in the workforce
Can be timed to align with tax season for immediate applicability
Challenges / Barriers
Participation is voluntary and may not reach all high-need populations
Program capacity varies by locality
Part 3: Integrate Community Filing Support as Educational and Quality-Assurance Partners
Rather than operating solely as stand-alone assistance programs, community-based filing support initiatives can be integrated as a support and quality layer for newly established K-12 and adult education efforts.
Expanded Role
Curriculum support: Provide standardized, up-to-date reference materials aligned with current filing practices
Experiential bridge: Support optional supervised mock-filing exercises using anonymized or simulated returns and provide a clear transition to real-world assistance
Quality control and feedback: Offer aggregated, non-identifying insights into common misconceptions and recurring errors to inform curriculum updates
Targeted Incentives for Certified Quality Roles
Limited, individual-only tax incentives could be offered to individuals who complete advanced certification and meet established accuracy and supervision benchmarks. Incentives would apply only after demonstrated competency and would be restricted to quality review, mentoring, or instructional support roles.
Poorly structured incentives risk undermining program quality; accordingly, any incentive should be narrowly tailored to post-certification roles and contingent on verified accuracy and performance.
Advantages
Grounds education in real filing experience
Reduces errors by pairing instruction with guided support
Creates a feedback loop between education and administration
Challenges / Barriers
Relies on volunteer capacity and local partner infrastructure
Part 4: Tax Incentive for Completing a Certified Tax-Filing Literacy Module
Mechanism
Create a one-time, modest, individual-only tax credit for completion of an approved tax-filing literacy module. The credit would be claimable only by the individual, not by parents or guardians on behalf of dependents.
Advantages
Encourages voluntary participation, particularly among adults
Does not require curriculum changes to produce impact
Challenges / Barriers
Administrative overhead related to certification and fraud prevention
Individuals who fail to file entirely may not access the incentive
Conclusion
The lack of practical tax-filing education represents a structural gap between civic obligation and institutional preparation. No single intervention can fully address this gap. A coordinated approach—combining K-12 minimum competencies, adult education pathways, integrated community support, and carefully designed incentives—creates a durable foundation for improving tax-filing literacy while preserving state flexibility and program integrity.
By emphasizing education, access, and quality rather than enforcement alone, this approach aligns taxpayer expectations with meaningful institutional support and promotes more equitable, efficient compliance over time.
Areas for Further Consideration
Several components of this proposal would benefit from additional specification during implementation planning to ensure effectiveness, equity, and program integrity.
Incentive Design for Quality-Control Roles
Any incentives associated with advanced certification or quality-review participation should be carefully calibrated to recognize demonstrated competence without undermining the volunteer-driven nature or trust of community filing support programs.
Structure of Individual Tax Incentives
Further consideration is needed to define appropriate incentive levels, eligibility verification, and accessibility for low-income filers so that participation is encouraged without creating unnecessary administrative complexity.
Certification and Content Governance
Clear responsibility for setting, maintaining, and updating certification standards and educational content will be necessary to ensure accuracy as tax filing tools and procedures evolve over time.
Capacity and Equity Across Jurisdictions
Implementation will need to account for variation in state and local capacity to deliver education and support, particularly in underserved or resource-constrained communities.
Evaluation and Feedback Mechanisms
Identifying high-level indicators of success will help ensure the system can be refined over time without relying on invasive data collection or enforcement-based measures.
