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The field notes archive.

2026.05.11 PAYMENTS

Pricing an API when the customer is an agent.

When the buyer is an autonomous agent paying per call, human pricing breaks. Seats, signup-gated free tiers, and annual commitments stop making sense for a machine that reads the price and comparison-shops every call.

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2026.05.13 AGENTS

Deterministic replay: debugging agents that will not reproduce.

An agent run is non-deterministic — sampling, tool responses, and timing all vary — so a bug seen once may never recur. Deterministic replay records every non-deterministic input so the run can be replayed exactly.

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2026.05.15 VOICE

Cascaded or end-to-end: a 2026 voice-architecture trade study.

A 2026 voice agent forks at the first design decision — STT→LLM→TTS cascade, or a single speech-to-speech model. End-to-end wins on latency and naturalness; the cascade wins on everything you debug, audit, and control. Here is the trade study.

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2026.05.16 ZKML

opML or zkML: a decision tree for verifiable inference.

Two ways to make an off-chain model output trustworthy on-chain. zkML is cryptographic, expensive, and small-model-only. opML is optimistic, cheap, and runs Llama-2-scale models today. Choosing by stakes, model size, and latency.

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2026.05.16 STANDARDS

MCP in production: the four gaps nobody demos.

MCP won the tool-integration standard. But "works in a demo" and "works in production" are different claims — and four gaps bite at scale: sticky sessions, server fan-out, governance, and what happens when a session drops mid-task.

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2026.05.16 EVAL

Faithfulness is not groundedness. And "accuracy" is not a RAG metric.

Teams say their RAG is 'accurate' and mean different things. Faithfulness is whether the answer is true; groundedness is whether every claim traces to a source. They fail differently — and a deploy depends on measuring both.

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2026.05.16 ZKML

The first proven LLM: what DeepProve changes for zkML.

DeepProve, from Lagrange, produced the first zero-knowledge proof of a full LLM inference — GPT-2. It moves "prove a transformer" from impossible to merely expensive. What that unlocks, and what is still years away.

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2026.05.16 TRAINING

Proving the work: verification in decentralized training.

Decentralized pretraining now reaches into the tens of billions of parameters — but you still cannot cryptographically prove the GPUs did the work they claim. How production networks check untrusted workers, and why ZK-proven training is years out.

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2026.05.16 EVAL

Stop OCR-ing your PDFs: retrieve on the page, not the transcript.

Most document RAG OCRs a PDF, rebuilds the layout, and chunks the text — losing every table, chart, and column it touches. ColPali-class visual retrieval embeds the page image directly. When that wins, when it doesn't.

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2026.05.16 SECURITY

Auditing an agent that holds a wallet.

Agents now sign transactions. The attack surface — a prompt injection that ends in a signed transfer — is new, and almost no security auditor covers it. What an agent security audit actually checks.

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2026.05.16 PAYMENTS

Spend rails for agents shipped. The safety layer didn't.

x402, ERC-8004, and AP2 gave agents the rails to hold and spend money. The controls that stop a prompt-injected agent from draining a wallet — spend ceilings, treasury isolation, circuit breakers — did not ship with them.

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2026.05.16 AGENTS

Your APM cannot see your agent failing.

Request traces and dashboards were built for request/response services. The ways an agent fails — a tool returning 200 with garbage, a truncated context, a looping planner — trip none of them. What agent-native observability has to capture.

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