The weekly strip · 63 issues · page 4 of 6
Building with AI
Hands-on patterns and code for people shipping AI features.
- Issue 50
10 October 2026 · Building with AI · 7 min read
PII and prompts: redaction patterns before the model sees the text
Redact in code before the model call: regex, NER and review, reversible placeholders, what GDPR and India's DPDP Rules imply, and how caching and retention interact.
- PII
- privacy
- redaction
- GDPR
- DPDP
- Issue 49
10 October 2026 · Building with AI · 7 min read
LLM guardrails: input checks, output checks and the ones that fire
Run cheap deterministic checks first, a small model screen second, and log how often each guard fires. A layered design with Haiku 5.5, structured outputs and Noul.
- guardrails
- safety
- validation
- structured outputs
- Claude Haiku 5.5
- Issue 48
10 October 2026 · Building with AI · 7 min read
Prompt versioning and rollback: prompts belong in git now
OpenAI is retiring prompt objects and Anthropic's Playground keeps no history. Version prompts like code, hash them into logs, and roll back without wrecking your cache.
- prompts
- versioning
- CI
- rollback
- prompt caching
- Issue 47
10 October 2026 · Building with AI · 7 min read
Cost observability for LLM apps: log usage per request from day one
Usage fields differ across Claude, OpenAI and Gemini. Normalise them, price each call with a dated rate table, and send cost and cache hits to Datadog per feature.
- observability
- cost
- Datadog
- LLM pricing
- Claude API
- Issue 46
10 October 2026 · Building with AI · 7 min read
Latency budgets for AI features: where the milliseconds go
Split an AI feature's latency into time to first token and decode time, then spend a budget on model tier, caching, output length and parallel calls, with a worksheet.
- latency
- performance
- LLM
- prompt caching
- TypeSafe Jev
- Issue 45
10 October 2026 · Building with AI · 7 min read
Streaming UX for AI answers: what to render before the first token
What users should see in the first second of an AI answer, how to render half-written Markdown without flicker, and how to cancel cleanly. Includes a React example.
- streaming
- UX
- React
- Markdown
- Claude API
- Issue 44
10 October 2026 · Building with AI · 7 min read
Function calling across Claude, GPT-6 and Gemini: one tool, three APIs
One lookup tool defined for Claude, OpenAI and Gemini: where the call comes back, how results go in, what parallel and strict mode look like, and a copyable adapter.
- function calling
- tool use
- multi-provider
- Claude Sonnet 5.5
- GPT-6
- Issue 43
10 October 2026 · Building with AI · 7 min read
Structured output without parsing: JSON schema modes vs System One models
Claude and Gemini schema modes guarantee the shape of a reply; TypeSafe's Jev returns typed answers with probabilities. What each documents, and when to use which.
- structured output
- JSON schema
- TypeSafe Jev
- Claude
- Gemini
- Issue 42
10 October 2026 · Building with AI · 7 min read
Human-in-the-loop by design: confidence thresholds and review queues
Use model confidence to route work to people, then size the queue, set the SLA and feed corrections back into evals. Managed review tools are closing, so build your own.
- human in the loop
- review queues
- confidence
- TypeSafe Jev
- evals
- Issue 41
10 October 2026 · Building with AI · 6 min read
Agentic workflows in enterprise apps: a control loop for production
Plan, act, verify, escalate: budgets, idempotency keys, permission hooks and audit logs for an agent that touches enterprise systems, built on documented SDK features.
- agents
- enterprise
- workflow
- idempotency
- audit logs
- Issue 40
10 October 2026 · Building with AI · 7 min read
Agent tool design: schemas that models call correctly
Naming, descriptions, parameter types and error returns for agent tools, checked against the Claude and Gemini docs, plus the forced tool-call change on Claude 5.5.
- tool use
- function calling
- agents
- Claude
- Gemini
- Issue 39
10 October 2026 · Building with AI · 7 min read
Golden datasets: how to build 200 labelled examples in a week
A day-by-day plan for 200 labelled examples: sampling, labelling guidelines, adjudication, splits and versioning, plus the arithmetic on what 200 can and cannot prove.
- evals
- labelling
- datasets
- golden dataset
- LLM-as-judge