Sam, We Talked About This is an idle incremental game that puts players in charge of building an AI empire from the ground up. The experience blends strategy, simulation, and casual progression mechanics on PC, centering on data collection, model training, and steady expansion toward artificial general intelligence.
Gameplay
The core loop revolves around scraping websites with a cursor to gather raw data in the form of text, images, or video. Each data type feeds a dedicated AI model that trains independently and begins attracting subscribers. Those subscribers generate revenue that players reinvest into additional storage disks, server cabinets, compute resources, and staff hires. Money collected on the floor disappears after a short window, which encourages timely spending and efficient resource management.
Upgrades appear in a dedicated tree that accelerates scanning speeds and improves crew performance. Storage expands without limit because collected data never depletes. Players name and rack individual models, then allocate compute so the models can reach wider audiences. The process creates a self-reinforcing cycle where faster scraping leads to smarter models, higher earnings, and quicker upgrades.
Progress is tracked through a visible ranking of 500 companies displayed on the wall. Climbing this list represents incremental gains in scale and capability, with AGI positioned as the ultimate target at the top. The simulation elements emphasize long-term planning around hardware growth and staff efficiency rather than direct control of individual actions.
Game Modes
The game operates as a single-player idle experience without separate named modes. All activity occurs within one continuous progression system that rewards both active cursor-based scraping and passive model operation. Players switch focus between data types to diversify model training, but the underlying loop remains consistent across sessions.
Idle mechanics allow numbers to continue growing while the player steps away, with upgrades and staff continuing to generate returns. Active play involves rapid site stripping and strategic allocation of newly earned funds. This unified structure suits extended play sessions or shorter check-ins, as the simulation advances regardless of constant input.
Progression and Systems
Storage and hardware purchases form the foundation of expansion. Disks and cabinets increase capacity, while machines and staff multiply output. Nothing gathered is ever consumed, so every byte of data contributes permanently to model training. The upgrade tree provides targeted improvements to scanning speed and crew effectiveness, creating clear paths for optimization.
Model management adds a layer of customization. Each trained model receives a name and rack placement before compute allocation determines its reach. Different data types produce distinct model behaviors, encouraging players to balance text, image, and video collection. Revenue from subscribers funds the next round of purchases, tightening the connection between collection, training, and monetization.
Is It Worth Playing?
Sam, We Talked About This targets players who enjoy idle incremental titles built around exponential growth and system optimization. The focus on data scraping, model training, and hardware scaling delivers a steady stream of small decisions that compound over time. Those who appreciate watching numbers rise and unlocking faster loops will find the mechanics satisfying.
The game remains in development with a planned release in Q4 2026, so concrete player feedback is not yet available. Its appeal rests on the described loop of collection, training, and ranking progression rather than additional features or multiplayer elements. Fans of the genre who prefer single-player simulation and incremental advancement may find it aligns with their preferences once it launches.