game.millrace.ai
Playable autonomous-build artifacts. First public stress-test domain for generated builds, upgrades, prompts/specs, known gaps, and outputs.
- Status
- live experiment
- Role
- playable outputs
The proof layer starts with shipped systems, public surfaces, and honest limits. Logs, rubrics, prompts, output histories, and postmortems can deepen this archive over time.
These links separate the product site, live run surface, and generated-output stream without asking a first-time visitor to decode an internal naming system.
Playable autonomous-build artifacts. First public stress-test domain for generated builds, upgrades, prompts/specs, known gaps, and outputs.
Autonomous runs, execution loops, logs, checkpoints, outputs, and archived run state as the public factory floor.
The core runtime surface: product thesis, architecture, docs, package, comparisons, and release path.
Claim tested: Games are the first public artifact class because they are visible, playable, interactive, and useful for exposing real implementation issues.
Result: Live experiment started. The archive should be read as an opening public evidence stream, not a mature proof corpus.
Limitations: All-game artifacts are too narrow to prove general-purpose production SaaS or integration capability by themselves.
Open evidence ->Claim tested: TalentBoard identifies Tim as 9/10 "AI Transformative" for overall AI Fluency after third-party manual validation via Nate B. Jones.
Result: TalentBoard manually validated Tim as 9/10 "AI Transformative" for overall AI Fluency via Nate B. Jones.
Limitations: This is an external evaluation signal, not a substitute for inspecting shipped product surfaces, code, artifacts, and limitations.
Open evidence ->Claim tested: The operator story is not only infrastructure theory. TJOS is an applied product surface for church teams.
Result: The public TJOS site presents a system of progress for church teams, Planning Center alignment, action queues, nonlinear discipleship pipelines, and demo access.
Limitations: Public proof should deepen over time with customer stories, product walkthroughs, and implementation artifacts.
Open evidence ->Founder thesis, proof network, strategic conversation, and ecosystem context.
Open founder brief ->Applied AI systems, automation architecture, workflow design, and durable operating surfaces.
Discuss applied systems ->Runtime architecture, artifacts, repo, limitations, logs, and public proof surfaces.
Inspect technical surface ->Plain resume, TalentBoard profile, GitHub, LinkedIn, and conventional background.
Read resume ->