Game Discovery Is an Evidence Problem
How game marketplaces can expose source-qualified game discovery evidence to personal agents without publishing private player data or ranking models.
Read the paperSoftware systems / Product reliability / Applied AI
Long-form arguments, evidence and practical operating models for systems people need to trust.
How game marketplaces can expose source-qualified game discovery evidence to personal agents without publishing private player data or ranking models.
Read the paperWhy executable game mods need immutable release identity, explicit capabilities, staged updates and runtime revocation.
Read the paperWhat current games and research show about bounded language-model interaction, likely next steps and the design work around them.
Read the paperA client-state model for measuring reliability from published build to verified launchable state.
Read the paperHow competitive play can provide repeated practice in feedback and coordination, while professional value still depends on engineering evidence.
Read the paperWhy implementation fluency can conceal an incomplete system contract, and how review can expose the assumptions that matter.
Read the paperWhy average success rates are incomplete for probabilistic workflows, and how repeated evidence can define a defensible operating boundary.
Read the paperA layered model for operational evidence, consumer policy and safe routing when agents select MCP tools dynamically.
Read the paperHow faster retries, adaptation and parallel operations change defensive priorities and the controls that retain their value.
Read the paperWhy autonomous agents need bounded, stateful authority that cannot expand through delegation, concurrency or cross-domain execution.
Read the paperWhy agent evaluations need independent controls for execution, network access, credentials, external effects, grading and incident response.
Read the paperWhy AI inventories need deployment identity, evidence classes and operational links before they can support security, change and incident response.
Read the paperWhy mature semantic models and analytics investments shorten the path to reliable enterprise AI consumption.
Read the paperPersistent agent memory creates obligations for provenance, scope, freshness, correction, expiry and audit.
Read the paperA decision framework for choosing between instructions, Agent Skills, existing tools and a new MCP server.
Read the paperAI assistants govern attention before a person makes a decision. This paper examines silent omissions, public evidence gaps and a practical way to test these systems.
Read the paperWhy versioned Markdown and static HTML provide a practical human review boundary as software agents gain more operational autonomy.
Read the paperRemote work widened the lives compatible with engineering. This paper examines return-to-office mandates, lived experience engineering and the consequences of narrowing participation.
Read the paperA reliability model for AI products whose behaviour can fail while their infrastructure remains available and inside its latency target.
Read the paperTelemetry creates value when evidence reaches a person or system that can make a better decision, not when another dashboard is created.
Read the paperService health becomes a product surface when customers can use it to retry, fail over, pause work, communicate impact or wait.
Read the paperTelemetry volume can grow faster than decision value, increasing storage, query, engineering and cognitive costs.
Read the paperCloud abstraction removes some component operation while introducing dependency, control-plane, recovery, support and exit responsibilities.
Read the paperRecovery depends on how evidence, authority, ownership and communication move between a failing system and the organisation responding to it.
Read the paperAll papers are available here as static HTML and downloadable Markdown.