Fable Without Fable: Sakana Fugu Ultra's Big Bet
Sakana's most interesting move is selling learned orchestration as a frontier-model substitute, with Fable-class pressure and very different production risks.
Evidence-first analysis of agentic systems, model evaluation, and the economics of AI software. We read the system card, find the primary source, and tell you what actually changed — and what didn't.
The gap between demo and production is the harness you build around the model, not the model you license.
Pillar guide → 02 · Search & GEOSearch is becoming synthesis. If ChatGPT, Perplexity, and Google's AI Overviews don't cite you, you're invisible, and…
Pillar guide → 03 · Agents & HarnessesExecution loops, externalized state, and verification gates now matter more than raw model IQ. Here's how the agents…
Pillar guide → 04 · AI ToolsFrontier labs now ship more AI-written code than human-written code, but the viral ROI numbers are wrong. Here is the…
Pillar guide →
AI EconomicsThe Nvidia question is now a workload-matching problem: memory bandwidth, utilization, and latency SLOs decide the real inference bill.
Model EvaluationA production eval program needs offline gates, calibrated human judgment, and live monitoring tied to the failures that cost you money.
AI FrontiersA legal-looking Code becomes a release checklist once you map each Article 53 duty to artifacts, owners, and audit trails.
AI FrontiersThe practical path to AI sovereignty now runs through distillation, quantization, and deployable open-weight models instead of frontier-model procurement theater.
AI FrontiersFeature stores are assumed in modern MLOps, but the real cutoff is production complexity, not ambition.
AI FrontiersThe 2026 shift is less about one miracle model and more about open weights, quantization, unified memory, and inference runtimes finally landing at the same time.
Memory & ContextMillion-token windows changed the default, but retrieval still wins when citations, query volume, and latency matter.
Model EvaluationA Codex SQLite logging bug turns telemetry from an abstract privacy concern into a measurable workstation endurance risk.
AI FrontiersThe winning AI product architecture is shifting from picking one frontier model to owning the policy that routes work across many.
AI FrontiersThe Anthropic Fable/Mythos shutdown turned model choice into a continuity problem for EU engineering teams.
Memory & ContextProduction RAG teams should choose a vector store by operating model, filter shape, and migration triggers, not by a vendor latency chart.
AI EconomicsThe practical video stack decision is no longer model quality alone; it is usable seconds, editing drag, rights clearance, and where the clip has to ship.
The gap between demo and production is the harness you build around the model, not the…
Explore →Search is becoming synthesis. If ChatGPT, Perplexity, and Google's AI Overviews don't cite…
Explore →Execution loops, externalized state, and verification gates now matter more than raw model…
Explore →Frontier labs now ship more AI-written code than human-written code, but the viral ROI…
Explore →Why static leaderboards lost authority, and how to build an eval program that survives…
Explore →Why the context window, not the prompt, is the real bottleneck, and how to engineer…
Explore →Why indirect prompt injection, tool-mediated exfiltration, and rogue agents now define LLM…
Explore →How the open-weight cluster closed the gap, why reasoning became the default, and which of…
Explore →A practitioner's map of frontier AI in mid-2026, where independent measurement finally…
Explore →