The most common mistake in the “SaaS is dead” narrative is treating the $2 trillion SaaS market as a single block that either survives or dies. The reality is far more nuanced: the value redistributes across horizons, and the timing differs dramatically. The Great Interface Inversion — Animated Explainer Horizon 1 (Now to 2028): TAM […]
Where the Value Flows: The $2T SaaS Market Redistributes, Not Evaporates Read More »
Reinforcement Learning from Verifiable Rewards emerged in 2025 as the most consequential training breakthrough since pretraining itself. The mechanics are deceptively simple — but the implications reshape the entire AI landscape. The Five Scaling Phases of AI — Animated Explainer How It Works Instead of training against human preferences (RLHF), models train against automatically verifiable
OpenAI’s o1 model, released in late 2024, introduced a new scaling dimension entirely. Rather than investing more compute in training, the model could invest more compute at inference time — “thinking” through problems step by step. The Five Scaling Phases of AI — Animated Explainer The Revolution This was revolutionary because it decoupled capability from
Test-Time Compute: The Discovery That Models Can Think Longer, Not Just Bigger Read More »
While pretraining scaling consumed the headlines, a quieter revolution was happening in the stages that came after. The production LLM stack stabilized into three layers: pretraining, supervised finetuning (SFT), and RLHF. The Five Scaling Phases of AI — Animated Explainer The Transformation SFT turned a raw text predictor into something that could follow instructions. RLHF
From SFT to RLHF: The Thin Layers That Made ChatGPT Possible Read More »
DeepMind’s Chinchilla paper was a watershed moment. By training models across a much wider range of sizes and data volumes, it demonstrated that Kaplan’s scaling laws had a systematic bias. The Five Scaling Phases of AI — Animated Explainer The Corrected Finding For compute-optimal training, model size and training data should scale equally. The Chinchilla
The Chinchilla Correction: How “Train Longer, Not Bigger” Changed Everything Read More »
In 2020, OpenAI published the original scaling laws alongside GPT-3 and established the first quantitative framework for AI capability growth. The thesis was straightforward: performance scales as a power law with model size. The Five Scaling Phases of AI — Animated Explainer The Numbers GPT-3 used 175 billion parameters trained on 300 billion tokens —
The Kaplan Era: When “Just Make It Bigger” Launched the AI Revolution Read More »
The story of modern AI isn’t a straight line of “bigger models = better results.” It’s a sequence of paradigm shifts, each one redefining where compute creates capability. Understanding these phases is the structural map that explains why 2025’s models weren’t dramatically larger than 2023’s — yet reasoned dramatically better. The Five Scaling Phases of
The Five Scaling Phases of AI: From “Make It Bigger” to “Reward the Truth” Read More »
Chapter 2 of the SaaS Destruction Map. 18 companies across 5 expansion categories driven by 4 compounding loops. The application layer shrinks. The infrastructure layer thickens.
The SaaS Expansion Map — Visual Guide Read More »
The SaaS Destruction Map was Chapter 1: What Dies. This is Chapter 2: What Compounds. 18 companies across 5 expansion categories with 4 compounding loops. Interactive tool.
The SaaS Expansion Map — The Software That Agents Expand — Interactive Tool Read More »
Watch the five competitive moats fight for survival in the AI agent era. Two fall. Three compound. Select a battle to see who wins.
Dead Moat vs Alive Moat — Battle Arena — Interactive Tool Read More »
See exactly how the pricing inversion destroys SaaS revenue — or creates opportunity. Select a company and model the shift.
Per-Seat to Per-Task Pricing Simulator — Interactive Tool Read More »
Track which SaaS companies are eating their own revenue before someone else does. The only survival strategy for the AI agent era.
Self-Cannibalization Tracker — Interactive Tool Read More »
The SaaS market value doesn’t vanish — it migrates. Adjust the sliders to model where $2 trillion in revenue redistributes.
$2 Trillion Flow Map — Interactive Tool Read More »
Select a company to analyze its competitive moats against the AI agent era. See which defenses hold — and which crumble.
SaaS Moat Analyzer — Interactive Tool Read More »
Model the financial impact of AI agent adoption on any SaaS company. Drag the sliders to see how seat compression destroys — or transforms — revenue.
AI Agent Revenue Calculator — Interactive Tool Read More »
Explore 52 companies from the top 100 software list mapped to their AI destruction tier. Filter by tier, search by name, sort by revenue, and click any company for deep-dive analysis with moat framework and disruption timeline.
The SaaS Destruction Map — Interactive Tool Read More »
52 companies from the top 100 software list mapped to their destruction tier. Tier 1 dies. Tier 2 compresses. Tier 3 expands.
SaaS Destruction Tiers — Company Scorecard — The SaaS Destruction Map Read More »
The value does not disappear. It migrates. Four destinations capture the margin that currently sits in the SaaS market.
Where the $2 Trillion Flows — The SaaS Destruction Map Read More »
