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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.
Gen α AI · Field notes for AI builders
Depth over hype, for people who bet on AI.
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.
Evidence over vibesDepth over volumeHonest about uncertainty
121Deep dives published
9Evergreen pillar guides
BiweeklyThe field briefing
Editor’s picksNew here? These are the pieces we’d hand you first.
01 · AI Tools
AI Coding Tools in 2026: The Power-User Field Guide
The gap between demo and production is the harness you build around the model, not the model you license.
Pillar guide → 02 · Search & GEOGenerative Engine Optimization: How to Earn AI Citations
Search is becoming synthesis. If ChatGPT, Perplexity, and Google's AI Overviews don't cite you, you're invisible, and…
Pillar guide → 03 · Agents & HarnessesAgent Harness Engineering and Agentic Loops: 2026 Field Guide
Execution loops, externalized state, and verification gates now matter more than raw model IQ. Here's how the agents…
Pillar guide → 04 · AI ToolsAI Coding Agent Economics: Real ROI and Cost per Pull Request
Frontier labs now ship more AI-written code than human-written code, but the viral ROI numbers are wrong. Here is the…
Pillar guide →The latestFresh analysis, published continuously — the full archive lives in the rail and the pillars below.
AI FrontiersFrontier Model Access Can Vanish. EU Teams Need a Plan
The Anthropic Fable/Mythos shutdown turned model choice into a continuity problem for EU engineering teams.
11 minJune 22, 2026→
Memory & ContextVector Database Comparison: Speed Is the Trap
Production RAG teams should choose a vector store by operating model, filter shape, and migration triggers, not by a vendor latency chart.
12 minJune 22, 2026→
AI EconomicsAI Video Generator Comparison: Pick What Ships
The 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.
13 minJune 22, 2026→
AI EconomicsSelf Hosted Open Models Win After This Cost Cliff
Self-hosting is now a workload decision: privacy, latency, volume, and ops capacity decide more than ideology.
11 minJune 22, 2026→
Model EvaluationLLM as Judge Needs Calibration Before CI Gates
LLM judges can scale review, but only if you measure bias, calibrate against humans, and treat disagreement as signal instead of noise.
10 minJune 22, 2026→
AI FrontiersAI Product UX Is Moving Past the Chatbox
The products users trust in 2026 make AI work visible, reversible, and recoverable before they make it autonomous.
11 minJune 22, 2026→
Memory & ContextProduction RAG Chunking Breaks at the Boundary
Semantic chunking helps when boundary errors dominate retrieval failures, but fixed and structure-aware chunks still win when latency, auditability, or corpus shape matters more.
11 minJune 21, 2026→
AI FrontiersEU AI Act Compliance Has an Audit Gap Problem
The fastest path to readiness is to treat Article 9, data lineage, logging, and oversight as production controls an auditor can replay.
11 minJune 21, 2026→
Model EvaluationLLM Observability Must Catch Drift Before Incidents
Production LLM monitoring works when it watches user-visible failure signals before prompt drift, hallucinations, latency, and cost spikes turn into incidents.
11 minJune 21, 2026→
Security & SafetyAI Safety Routing Is Real. The Audit Trail Isn't Yet
Routing risky prompts to safer models can be a serious governance control, but only if buyers can inspect the classifier, fallback chain, logs, and audit evidence.
12 minJune 21, 2026→
AI EconomicsKV Cache Compression Is the New Inference Lever
The highest-leverage serving work in 2026 is no longer just faster kernels; it is shrinking the cache that long-context models reread on every decode step.
11 minJune 21, 2026→
Agents & HarnessesThe MCP Server Boom Moved the Moat to Gateways
The protocol is becoming boring infrastructure; the hard decisions now live in authorization, isolation, observability, and gateway choice.
11 minJune 21, 2026→
Explore the pillarsNine durable guides that organize everything we publish.
AI Tools15 pieces
AI Coding Tools in 2026: The Power-User Field Guide
The gap between demo and production is the harness you build around the model, not the…
Explore →Search & GEO9 pieces
Generative Engine Optimization: How to Earn AI Citations
Search is becoming synthesis. If ChatGPT, Perplexity, and Google's AI Overviews don't cite…
Explore →Agents & Harnesses17 pieces
Agent Harness Engineering and Agentic Loops: 2026 Field Guide
Execution loops, externalized state, and verification gates now matter more than raw model…
Explore →AI Economics12 pieces
AI Coding Agent Economics: Real ROI and Cost per Pull Request
Frontier labs now ship more AI-written code than human-written code, but the viral ROI…
Explore →Model Evaluation15 pieces
Evaluating AI Models and Agents: The 2026 Field Guide
Why static leaderboards lost authority, and how to build an eval program that survives…
Explore →Memory & Context13 pieces
Context Engineering for AI Agents: Memory, RAG & MCP
Why the context window, not the prompt, is the real bottleneck, and how to engineer…
Explore →Security & Safety8 pieces
Securing AI Agents and LLM Apps: The 2026 Threat Model
Why indirect prompt injection, tool-mediated exfiltration, and rogue agents now define LLM…
Explore →Models & Releases11 pieces
AI Models 2026: The Mid-Year Frontier and Open-Weight Map
How the open-weight cluster closed the gap, why reasoning became the default, and which of…
Explore →AI Frontiers21 pieces
AI Frontiers 2026: Diffusion Models, Multimodal AI & More
A practitioner's map of frontier AI in mid-2026, where independent measurement finally…
Explore →