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All writing

124 long-form pieces on architecture, training, inference, agents and safety.

All Model Architecture19 Training & Alignment22 Inference & Serving18 Agents & Orchestration11 Reasoning & Evaluation26 Safety, Security & Governance7 Platforms & Practice21
Reasoning & Evaluation 18 min

Test-Time Compute: How Reasoning Models Buy Intelligence by the Token

A 7B model that thinks for thirty seconds can outscore a 70B model that answers instantly. Test-time compute is the lever that makes this possible, and it is quietly rewriting the economics of model design.

reasoning test-time-compute inference reinforcement-learning ∑ ◫
Training & Alignment 9 min

The $8M trillion: when frontier-grade training falls out of the lab

DeepSeek shipped a 1.6T-parameter model in April 2026 with native Ascend inference support while OpenAI committed $500B to Stargate. Both can be right, but only one of them is a moat.

training compute scaling economics ∑
Agents & Orchestration 27 min

The Agentic Runtime: Why the Orchestration Layer Is Becoming More Valuable Than the Model

A frontier model can write a function. An agentic runtime can read a codebase, plan a migration, edit forty files, run the tests, fix what broke, and open a pull request. The difference is not intelligence; it is the system that …

agents runtime orchestration claude-code ∑ ◫
Training & Alignment 26 min

The Alignment Problem in Speech Recognition: CTC, RNN-T, and the Cost of Not Waiting

A ten-second utterance is a thousand acoustic frames. Its transcript is forty characters. Nobody wrote down which frames make which character, and the number of ways to line them up is astronomical. Every major speech architectur…

speech asr ctc rnn-t ∑ ◫
Platforms & Practice 26 min

The Anthropic Platform Stack: An Architect's Guide to Building on Claude

Most teams still treat Anthropic as 'the Claude API.' That framing misses the platform that has grown around it: managed agents, a universal integration protocol adopted by every major AI vendor, a governance layer with 28 securi…

anthropic claude enterprise-ai mcp ∑ ◫
Training & Alignment 24 min

The Bandwidth Wall: How Low-Communication Training Unbundled the Datacentre

Data-parallel training all-reduces the entire gradient after every step, which is why frontier pretraining happens inside one building with a purpose-built fabric. DiLoCo synchronises every five hundred steps instead of every one…

distributed-training scaling infrastructure optimisation ∑ ◫
Reasoning & Evaluation 24 min

The Bayesian Workflow: Why Fitting a Posterior Is the Easy Part

A 700-draw run of the eight-schools model reported R-hat of 1.01 and put the 2.5% quantile of the between-school spread at 0.89, while the exact posterior holds almost 18% of its mass below that value. Calling a sampler takes one…

bayesian-methods statistics uncertainty calibration ∑ ◫
Training & Alignment 26 min

The Bias-Variance Tradeoff Is a Special Case: Double Descent, Benign Overfitting, and Grokking

A network that fits ImageNet with randomly shuffled labels should not generalise on real ones. It does. That single experiment invalidated the textbook account of why machine learning works, and the three phenomena that replaced …

training-dynamics generalisation double-descent grokking ∑ ◫
Platforms & Practice 7 min

The Claude Stack Goes to Work: How Anthropic's Product Ecosystem Reshapes Marketing and Creative Labour

Anthropic stopped shipping a chatbot and started shipping an ecosystem. From Artifacts to Cowork to Design, the through-line is the same: move the model out of the chat box and into the work. For marketing teams, that change is n…

anthropic claude marketing agents
Agents & Orchestration 24 min

The Context Economics of Agents: Why Every 2025 Advance Was the Same Move

One workflow, 150,000 tokens down to 2,000. A subagent that burns fifty thousand tokens and returns fifteen hundred. A hundred installed skills that cost two thousand tokens until one is needed. Four separate advances, four separ…

agents context-engineering mcp tool-use ∑ ◫
Platforms & Practice 25 min

The Controls That Make It Worse: Colliders, Mediators and Why Adjusting for Everything Is Wrong

Open surgery beat percutaneous nephrolithotomy on small kidney stones, 93% to 87%. It beat it on large stones too, 73% to 69%. Pooled across both, it lost, 78% to 83%. The arithmetic is correct in all three statements, and no amo…

causal-inference statistics confounding dags ∑ ◫
Reasoning & Evaluation 24 min

The Curse of Dimensionality: Why Distances Stop Meaning Anything, and Why Learning Works Anyway

Scatter 1,000 random points in a 1,000-dimensional cube and the farthest one from a query is only about 12% farther away than the nearest. By that arithmetic nearest-neighbour search should be meaningless, and yet every vector da…

supervised-classical learning-theory embeddings vector-search ∑ ◫
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1020 concepts, 11,135 flashcards and 124 long-form pieces on AI, NLP, deep learning, LLMs and agentic systems. Free, no sign-up, no paywall.

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