The public-access genesis. Fragile tools, real signal.
28 ENTRIES captured in the source-reviewed archive.
Memory Lane is DeepMoat's branded field memory: a selective, source-reviewed way to track public AI capability over time so client decisions are not made from the feed. It is evidence of attention, not client evidence.
Explore the releases and developments DeepMoat has selected and source-reviewed for operators: models, agent tools, enterprise platforms, governance, pricing, security, and changes to real-world capability. This archive records our coverage of the field, with each entry linked to a source.
Each bar uses the same scale from zero. Counts reflect this selected archive; coverage varies by year and the current year is partial.
28 ENTRIES captured in the source-reviewed archive.
55 ENTRIES captured in the source-reviewed archive.
79 ENTRIES captured in the source-reviewed archive.
88 ENTRIES captured in the source-reviewed archive.
Source-reviewed through August 31, 2026. Entries include frontier releases, access changes, frontier talent moves, government interventions, trust breaches, AI infrastructure buildouts, regulated-workflow guardrails, and governance or security events that materially changed the operating map. Trust is safety; unsupported or low-confidence items stay out until a source can defend them; high-stakes reported allegations stay labeled as allegations until the evidence record hardens.
AI decisions are timing decisions. What was impossible last year may be viable now, and what looks impressive today may still be too fragile for a client's business.
Memory Lane supports client work by grounding recommendations in capability history, product shifts, and the difference between durable signal and temporary hype.
A way to understand capability movement across years, not just announcements.
Public claims are tied to sources when they are used as support.
It does not disclose private work. It shows how DeepMoat tracks the field that client work depends on.
DeepMoat reads the source-backed signal, screens exposure, and helps decide what to build, buy, automate, prototype, train, govern, pause, watch, or sequence.