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Glossary

Every hard term the posts define, in one place: 494 terms, each with one plain definition and the posts where it appears. In a post, the same definitions open when you hover over or tap a term with a dotted underline.

494 terms

#

.NET

Microsoft's software platform for building applications, most often in the C# language.

Used in: Forward deployed engineering, Part 6: Agent frameworks compared

16-bit

A number format that uses 16 bits, or two bytes, per value: smaller than the usual 32-bit format, at the cost of some precision.

Used in: Prerequisite 3: How a model works: tokens, context, settings and what we never ask it to do

403 Forbidden

The HTTP status code for Forbidden: the server knows who you are, but that identity is not allowed to do this.

Used in: Forward deployed engineering, Part 8: Debugging in the field

429 Too Many Requests

An HTTP status code meaning too many requests: the caller hit a rate limit or quota and should wait before retrying.

Used in: Part 15: What breaks in production: answers, loops, cost and model changes

A

Access Connector for Azure Databricks

An Azure resource that holds a managed identity, an Azure-run identity with no stored secret, which Databricks uses to reach Azure storage.

Used in: Part 2: Identity and access, IAM, service accounts, single sign-on and automation

access token

A short-lived digital pass, issued after someone signs in, that a program shows to a service to prove it may act for that person.

Used in: Connectors, MCP and plugins explained: who builds the link, where the data lives, and can a custom MCP server stay private?, Part 1: What an agent really is, and the system we will build

adversarial inputs

Inputs crafted on purpose to trick a model into a wrong or harmful output, often looking normal to a person.

Used in: Prerequisite 5: Compliance for AI systems: what an architect needs to know

after-model callback

A function ADK runs straight after each model response, which can inspect the response and replace it before anything else sees it.

Used in: Part 6.5: Multi-agent topologies beyond a router

Agent Identity

A Google Cloud feature that gives each deployed agent its own cryptographic identity, based on the SPIFFE standard, so it can be granted roles and audited separately.

Official docsUsed in: Forward deployed engineering, Part 10: Talking to executives and proving the outcome, Part 16: What breaks in production: identity, agents, safety and rollout

Agent Registry

Google Cloud's central catalogue for registering, discovering and governing agents, MCP servers, tools and endpoints, which Agent Gateway can check calls against.

Official docsUsed in: Connectors, MCP and plugins explained: who builds the link, where the data lives, and can a custom MCP server stay private?, Part 16: What breaks in production: identity, agents, safety and rollout

Agentic AI Foundation

A Linux Foundation body that hosts open agent standards, such as MCP, under neutral, multi-vendor governance.

Official docsUsed in: Plugins vs agents: what changed in August 2026

agents-cli

Google's command-line tool for creating, running, testing and deploying ADK agent projects from templates.

Used in: Prerequisite: The Python you need to read agent code

AI Office

The body inside the European Commission that supervises general-purpose AI models and coordinates how the AI Act is applied across the EU.

Used in: Your chatbot now has to say it's a chatbot

AI Omnibus

The Digital Omnibus on AI: an EU package of targeted amendments to the AI Act, proposed by the Commission in November 2025, which among other changes postpones the high-risk deadlines.

Official docsUsed in: Prerequisite 5: Compliance for AI systems: what an architect needs to know

Allowlist

A list of the only accounts, projects, destinations or actions that are permitted; anything not on it is refused.

Used in: Forward deployed engineering, Part 4: Data readiness and RAG from zero, Plugins vs agents: what changed in August 2026, Part 1.75: Agent frameworks, and where ADK fits

Amazon S3

Amazon Simple Storage Service, the object storage service on AWS, the counterpart of Cloud Storage.

Used in: Prerequisite 1: What a lakehouse is: storage, table formats and Spark

Apache 2.0

A permissive open-source licence that allows commercial use, changes and redistribution, as long as you keep the licence and copyright notices.

Used in: Part 13: Choosing and running models for agents

Apache Hive

Open source software that lets people query files in distributed storage with SQL, and whose metastore many engines use as a table catalogue.

Used in: Prerequisite 1: What a lakehouse is: storage, table formats and Spark

Apache Spark

An open source engine that splits large data processing jobs across many machines in a cluster working in parallel.

Official docsUsed in: Part 5: Storage, Cloud Storage and how Unity Catalog uses it, Prerequisite 2: What a cloud is, and what Google Cloud is

API key

A secret string an app sends with each request to a paid service so the service knows whose account to use and bill.

Used in: Practice Time: an app that listens to a child read

Apigee

Google Cloud's API management platform, which sits in front of APIs to handle security, rate limits, analytics and routing.

Official docsUsed in: Part 12: Giving it to users, Part 12.5: Front doors and runtimes: Gemini Enterprise, the alternatives, and agents that run anywhere

App Check

A Firebase service that checks requests really come from your genuine app or site, so others cannot use your backend resources or quota.

Official docsUsed in: Your chatbot now has to say it's a chatbot

Application Load Balancer

Google Cloud's load balancer for HTTP and HTTPS traffic, which can terminate TLS and route each request by its host name or path.

Used in: Part 12: Giving it to users

ARIMA

AutoRegressive Integrated Moving Average: a classic statistical method that forecasts a series from its own recent values and its recent forecast errors.

Used in: Prerequisite 2.5: Traditional AI and generative AI: from regression and trees to neural networks

attribute mappings

Rules that copy details from the external identity provider's sign-in token, such as user ID or group, into the attributes Google Cloud uses for access decisions.

Used in: Forward deployed engineering, Part 3: Designing inside someone else's estate

attribution graph

A map, built by Anthropic's circuit tracing method, of which internal features passed information to which others on one prompt, tracing how an input becomes an output.

Official docsUsed in: Research papers, myth by myth, Part 4: 'Hallucinations are random glitches', Research papers, myth by myth, Part 5: 'A model's chain of thought shows how it really reached the answer'

auto-regressive

Generating a sequence one piece at a time, feeding each new piece back in as input before producing the next.

Used in: Research papers, myth by myth, Part 1: 'An AI reads one word at a time, like we do'

autocorrelation

When a value is similar to the values just before it in time, as this week's orders usually are to last week's.

Used in: Prerequisite 2.5: Traditional AI and generative AI: from regression and trees to neural networks

Autoscaling

Automatically adding or removing computing capacity, such as cluster workers, as demand rises and falls, usually between a minimum and maximum that you set.

Used in: Part 9: Commercials, quotas and operations, Learning Cloud through GCP — Part 3: Where do I compute on cloud ?

Availability Zone

AWS's name for one or more isolated data centres inside a Region, with separate power and networking, much like a Google Cloud zone.

Used in: Prerequisite 2: What a cloud is, and what Google Cloud is

AWS Glue

AWS's managed data integration service, whose Glue Data Catalog records tables, their schemas and where their files sit in Amazon S3.

Used in: Prerequisite 1: What a lakehouse is: storage, table formats and Spark

B

B-tree

A sorted, branching structure that lets a database find a value in a few steps instead of scanning every row.

Used in: Prerequisite 1: What a lakehouse is: storage, table formats and Spark

backfill

A one-off run that processes past periods of data, for example to fill a gap or apply a corrected rule to history.

Used in: Part 9: Commercials, quotas and operations

baremetal

A physical server used directly, with no hypervisor or virtual machine layer between the hardware and the operating system.

Used in: Learning Cloud through GCP — Part 3: Where do I compute on cloud ?

base model

A model straight out of pretraining, before any tuning to follow instructions or chat; it simply continues the text it is given.

Used in: Research papers, myth by myth, Part 4: 'Hallucinations are random glitches'

base64

A way of writing any binary data using only 64 printable characters, so it can travel safely inside text such as a web form.

Used in: Prerequisite 3: Identity and security foundations

batch inference

Running a model over many stored records in one go, rather than answering live requests one at a time.

Used in: Part 8: Better together, BigQuery, Gemini and Google Cloud services

batch job

Work submitted to run in the background over many inputs at once, rather than answering one request at a time while someone waits.

Used in: Part 10: Proving it works, evals that gate releases

bearer token

An access token that grants access to whoever presents it, like a ticket, so it must be kept secret and short-lived.

Used in: How I built this website for free: system design, Astro, Firebase, OIDC federation and browser-native reader tools, Part 12: Giving it to users

benchmark

A fixed public test set, such as MMLU or GPQA, used to score and compare models on the same questions.

Used in: Research papers, myth by myth, Part 4: 'Hallucinations are random glitches'

BIG-Bench

A collaborative benchmark of over 200 varied tasks, from arithmetic to translation puzzles, contributed by many researchers to probe the abilities of language models.

Official docsUsed in: Research papers, myth by myth, Part 6: 'Bigger models get smarter in sudden, unpredictable leaps'

BigQuery Agent Analytics

An ADK plugin that streams agent events, such as prompts, tool calls and responses, into a BigQuery table for analysis.

Used in: Part 9: Guardrails that cannot be talked around

Bigtable

Google Cloud's managed wide-column NoSQL database, built for very large tables and fast reads and writes of single rows by key.

Used in: Part 13.75: Preparing data for agents: structured and unstructured, Part 17: Designing an agent system from scratch: a framework and five real-world scenarios

binaries

Compiled program files that a computer can run directly, as opposed to the human-readable source code they were built from.

Used in: Learning Cloud through GCP — Part 3: Where do I compute on cloud ?

biometric data

Personal data from measuring a person's physical or behavioural features, such as their face, fingerprints or voice, that can identify or categorise them.

Used in: Your chatbot now has to say it's a chatbot

BLEU

A translation score from 0 to 100 that measures how many word sequences in the machine's output also appear in human reference translations; higher is better.

Used in: Research papers, myth by myth, Part 1: 'An AI reads one word at a time, like we do'

broadcast address

The last address in a range, traditionally used to send one message to every device on that subnet at once.

Used in: Part 3: Networking: VPC, Cloud NAT, Private Google Access and Private Service Connect

browser console

The browser's developer tool where anyone can type and run JavaScript against the page they have open.

Used in: CV Builder: write your CV once, export it ten ways

C

calibrated

A model is calibrated when its scores match reality: of all the cases it scores about 0.7, about 70% turn out to be positive.

Used in: Prerequisite 2.5: Traditional AI and generative AI: from regression and trees to neural networks, Research papers, myth by myth, Part 4: 'Hallucinations are random glitches'

callback

A function ADK runs automatically at a fixed point in a turn, such as just before a tool call, which can inspect or block that step.

Used in: Part 4: Skills, teaching an agent how, Part 8: Memory, what an agent should remember

canary

A release that sends a small share of real traffic to the new version first, and widens it only if nothing goes wrong.

Used in: Part 17: Designing an agent system from scratch: a framework and five real-world scenarios, Prerequisite 2.75: MLOps and LLMOps: keeping models and agents right after launch

catalog

In Unity Catalog, the top level container of data, holding schemas, which in turn hold tables and views.

Used in: Prerequisite 2: The business terms and the data behind the agents

certificate authority (CA)

An organisation or service that signs certificates; a device accepts a certificate only if it was signed by an authority on that device's trusted list.

Used in: Connectors, MCP and plugins explained: who builds the link, where the data lives, and can a custom MCP server stay private?, Part 12: Giving it to users

change data feed

A Delta table option that records row-level inserts, updates and deletes between versions, so downstream jobs can process only what changed.

Used in: Part 8: Better together, BigQuery, Gemini and Google Cloud services

checkpoint

A Parquet file Delta Lake writes now and then to summarise the table's log so far, so readers need not replay every JSON commit.

Used in: Part 6: Governance and security

chunking

Splitting long documents into smaller passages so each one can be indexed and retrieved on its own.

Used in: Forward deployed engineering, from the basics

circuit breaker

A switch in code that stops calling a failing service for a while after repeated errors, then lets a few trial calls through to test recovery.

Used in: Part 15: What breaks in production: answers, loops, cost and model changes

classic compute plane

Where classic Databricks clusters run, as virtual machines inside your own Google Cloud project and network.

Used in: Part 2: Identity and access, IAM, service accounts, single sign-on and automation

classifier

A model that sorts an input into categories, such as harmful or harmless, usually by giving a score and comparing it with a cutoff.

Used in: Research papers, myth by myth, Part 11: 'You cannot stop jailbreaks without making the model useless'

CLI

Command-line interface: a program you control by typing commands in a terminal rather than clicking in a window.

Used in: Forward deployed engineering, Part 7: Prototype in days, production in weeks

Cloud Firestore

Google's managed document database, part of Firebase, which can push changes to connected apps in real time.

Used in: Rally Point: badminton rules you can see, and a scorer an umpire can trust

Cloud Interconnect

A dedicated private physical link between an on-premises data centre and Google's network.

Used in: Part 4: Serverless networking and egress

Cloud KMS

Google Cloud Key Management Service: it stores encryption keys and controls which identities may use them to encrypt or decrypt data.

Official docsUsed in: Part 2: Identity and access, IAM, service accounts, single sign-on and automation

Cloud Logging

Google Cloud's managed service that collects, stores and lets you search log lines from your applications.

Official docsUsed in: Part 12: Giving it to users, Part 3: Letting an agent touch data safely, Part 9: Guardrails that cannot be talked around

Cloud Scheduler

Google Cloud's managed cron service, which sends a message or calls a URL on a fixed schedule.

Used in: Long-running agents explained: what changes when an agent keeps working after you close the tab

Cloud Storage

Google Cloud's object storage service; files are kept in containers called buckets.

Used in: Part 8: Memory, what an agent should remember

cold start

The delay while a stopped service or machine starts up before it can answer its first request.

Used in: Forward deployed engineering, Part 5: Enterprise integrations, APIs, connectors and identity

Committed-use

Committed-use discount: a lower price in exchange for committing to a minimum spend or usage, usually for one or three years.

Used in: Part 13.5: What does an agent cost to own? Pricing across the architecture choices

Compaction

Shortening a long conversation history, typically by replacing older turns with a short model-written summary, so each model call sends fewer tokens.

Used in: Part 1.5: The harness, the loop and the context, Part 15: What breaks in production: answers, loops, cost and model changes, Part 2.5: Inside ToolContext, the object every tool receives

Compute Engine

Google Cloud's service for creating and running virtual machines.

Used in: from the basics

concurrency control

How a database keeps data correct when many users read and change the same records at the same moment.

Used in: Learning Cloud through GCP — Part 4: Where do I store my data on Cloud ?

conditional edge

A link in a graph whose destination is chosen while the program runs, by a function that looks at the current state.

Used in: Forward deployed engineering, Part 6: Agent frameworks compared

container runtime

The software on a machine that actually starts, runs and stops containers from their images, such as Docker or containerd.

Used in: Learning Cloud through GCP — Part 3: Where do I compute on cloud ?

Context caching

Reusing the already processed opening part of a model request when later requests start with the same text, such as fixed instructions, which cuts cost and latency.

Official docsUsed in: Part 1.9: How agents connect: MCP, A2A and UTCP, Prerequisite 3: How a model works: tokens, context, settings and what we never ask it to do

Context-Aware Access

A Google Cloud control that allows or refuses a request based on conditions about it, such as the device, network or certificate it comes from.

Official docsUsed in: Part 7: Who is asking? Identity for agents

CopilotKit

An open-source framework for building in-app AI assistant interfaces, which created and maintains the AG-UI protocol.

Used in: Part 12.75: How agents show more than text: A2UI, AG-UI and MCP Apps

CORS

Cross-Origin Resource Sharing: the browser rules that decide whether a page on one domain may read responses from a server on another domain.

Used in: How I built this website for free: system design, Astro, Firebase, OIDC federation and browser-native reader tools

COTS

Commercial off-the-shelf: ready-made software bought from a vendor rather than built in-house.

Used in: Learning Cloud through GCP — Part 4: Where do I store my data on Cloud ?

covariate shift

A change in the distribution of a model's inputs while the relationship between inputs and the answer stays the same.

Used in: Prerequisite 2.75: MLOps and LLMOps: keeping models and agents right after launch

CPM

Cost per mille: advertising spend for every thousand impressions, so spend divided by impressions, times 1,000.

Used in: Part 3.5: Letting an agent write and run code safely

CrewAI

An open-source Python framework for building teams of AI agents that each play a defined role.

Used in: Forward deployed engineering, Part 1: What a forward deployed engineer actually does

cron

The classic Unix scheduler, and its compact five-field notation for times such as every day at 02:00.

Used in: Long-running agents explained: what changes when an agent keeps working after you close the tab

cross-entropy loss

A score of how surprised a language model is by the real next token in unseen text, averaged over many tokens; lower means better predictions.

Used in: Research papers, myth by myth, Part 6: 'Bigger models get smarter in sudden, unpredictable leaps'

cross-layer transcoder

A readable stand-in network trained to imitate a model's MLP layers using sparse features, where each feature reads from one layer and writes to all later ones.

Official docsUsed in: Research papers, myth by myth, Part 2: 'It only predicts the next word'

cryptographic provenance

A digitally signed record attached to a file, as in the C2PA standard, showing where the content came from and how it was edited.

Used in: Your chatbot now has to say it's a chatbot

CSAT (customer satisfaction score)

Customer satisfaction score: the share of customers who rate an interaction as good in a short survey sent straight after it.

Used in: Part 17: Designing an agent system from scratch: a framework and five real-world scenarios

CSV

Comma-separated values: a plain text file where each line is a row and commas separate the columns.

Used in: Part 2.5: Inside ToolContext, the object every tool receives

custom-mode

A custom-mode VPC network starts with no subnets; you create each subnet and choose its region and IP range yourself.

Used in: Prerequisite 2: What a cloud is, and what Google Cloud is

customer-managed VPC

A network you create and control in your own Google Cloud project, which Databricks then uses for a workspace's classic clusters.

Used in: Part 4: Serverless networking and egress

D

Data pipeline

A chain of automated, often scheduled, steps that copies data out of its sources, cleans and reshapes it, and loads it where it will be used.

Used in: Learning Cloud through GCP — Part 4: Where do I store my data on Cloud ?, Part 1: What an agent really is, and the system we will build

data poisoning

An attack that slips misleading or malicious examples into training data so the resulting model behaves wrongly.

Used in: Prerequisite 5: Compliance for AI systems: what an architect needs to know

Databricks Runtime

The versioned bundle of Apache Spark and libraries that runs on Databricks compute; each version number is a release of it.

Used in: Prerequisite 2: The business terms and the data behind the agents

Databricks service principal

A Databricks identity for an automated tool, job or program rather than a person, with its own permissions and credentials.

Official docsUsed in: Part 7: The platform on Google Cloud, runtime, Photon, SQL, Lakeflow and AI, Part 8: Better together, BigQuery, Gemini and Google Cloud services

DataFrames

A pandas table held in memory, with named columns and rows, that Python code can filter, sum and plot.

Used in: Part 3.5: Letting an agent write and run code safely

dbt Cloud

The hosted service for dbt, a tool that builds, tests and documents data transformations written in SQL.

Used in: Part 3: Networking: VPC, Cloud NAT, Private Google Access and Private Service Connect

DBU (Databricks Unit)

Databricks Unit: the normalised unit of processing Databricks measures and bills by; each product consumes DBUs at its own rate, and you pay a price per DBU.

Official docsUsed in: from the basics, Part 7: The platform on Google Cloud, runtime, Photon, SQL, Lakeflow and AI, Part 13.5: What does an agent cost to own? Pricing across the architecture choices

DDOS

Distributed denial of service: an attack where many machines flood a service with traffic at once so genuine users cannot reach it.

Used in: Learning Cloud through GCP — Part 5: How do I connect to my cloud ?

decoder

The half of a translation model that writes the output one token at a time, looking at what it has written so far and at the encoder's vectors.

Used in: Research papers, myth by myth, Part 1: 'An AI reads one word at a time, like we do'

default gateway

The address a machine sends traffic to when the destination lies outside its own subnet.

Used in: Part 3: Networking: VPC, Cloud NAT, Private Google Access and Private Service Connect

Delta Lake

An open table format that adds a transaction log to Parquet files in cloud storage, giving reliable updates, deletes and version history.

Official docsUsed in: Part 7: The platform on Google Cloud, runtime, Photon, SQL, Lakeflow and AI, Prerequisite 2: What a cloud is, and what Google Cloud is

Delta table

A table stored as Parquet data files plus a transaction log in object storage, using the open Delta Lake format.

Used in: Part 5: Storage, Cloud Storage and how Unity Catalog uses it

deprecation warning

A notice from an API that a feature still works for now but is being retired and will stop working later.

Used in: Prerequisite 3: How a model works: tokens, context, settings and what we never ask it to do

differential privacy

A mathematical guarantee that a published statistic changes very little whether or not any one person's data is included, usually achieved by adding carefully sized random noise.

Used in: Research papers, myth by myth, Part 12: 'Nobody really knows how people use AI, and it is mostly replacing jobs'

distributed system

A system whose data and work are spread across many machines that coordinate over a network.

Used in: Learning Cloud through GCP — Part 4: Where do I store my data on Cloud ?

DML and DDL

Data manipulation language (INSERT, UPDATE, DELETE) changes the rows in tables; data definition language (CREATE, ALTER, DROP) changes the tables themselves.

Used in: Prerequisite 1: What a lakehouse is: storage, table formats and Spark

DNS

The Domain Name System, which turns names such as a web address into the IP addresses that machines actually connect to.

Used in: Part 1: Foundations, how Databricks is built on Google Cloud

DNS peering

A Cloud DNS setting that answers lookups for chosen domain names using another VPC network's DNS settings, so private names resolve to private addresses.

Official docsUsed in: Connectors, MCP and plugins explained: who builds the link, where the data lives, and can a custom MCP server stay private?

Docker container

A packaged app with its own files and libraries that runs as an isolated process, but still shares the host machine's operating system kernel.

Used in: Part 3.5: Letting an agent write and run code safely

Docstring

The text written just below a Python function's first line that says what it does, its arguments and what it returns; ADK shows it to the model.

Used in: Part 2: Your first agent: one job, narrow tools, Part 4: Skills, teaching an agent how

Document AI

Google Cloud's service for extracting text, layout, tables and fields from documents such as scanned PDFs, forms and invoices.

Official docsUsed in: Forward deployed engineering, Part 4: Data readiness and RAG from zero, Part 13.75: Preparing data for agents: structured and unstructured

DOM

Document Object Model: the browser's live, in-memory tree of every element on the page, which JavaScript reads and changes.

Used in: How I built this website for free: system design, Astro, Firebase, OIDC federation and browser-native reader tools

dot product

Multiply two vectors number by number and add up the results; the bigger the total, the more the two vectors point the same way.

Used in: Research papers, myth by myth, Part 1: 'An AI reads one word at a time, like we do'

DPoP (Demonstrating Proof of Possession)

Demonstrating Proof of Possession: an OAuth extension in which the client signs each request with its own private key, so a stolen token is useless without that key.

Official docsUsed in: Part 12: Giving it to users

Drift

A gradual change over time in the data a model or system sees, or in its behaviour, so patterns it learned or was tested on stop matching.

Used in: Prerequisite 2.5: Traditional AI and generative AI: from regression and trees to neural networks, Prerequisite 5: Compliance for AI systems: what an architect needs to know

E

eager execution

Running each operation immediately as the code reaches it, which is easy to debug, instead of first compiling the whole program into one optimised graph.

Used in: GPUs, TPUs and why AI is slow where it is: compute, memory bandwidth, the KV cache and the software in between

early stopping

Stopping training once the score on held-back data stops improving, so the model does not keep memorising the training rows.

Used in: Prerequisite 2.5: Traditional AI and generative AI: from regression and trees to neural networks

encoder

The half of a translation model that reads the whole input sentence and turns it into vectors.

Used in: Research papers, myth by myth, Part 1: 'An AI reads one word at a time, like we do'

Environment variable

A named setting a running program reads from its operating system, often used to pass secrets such as API keys or paths without writing them into code.

Used in: Forward deployed engineering, Part 9: LLM-native performance, latency, tokens and cost, Part 3.5: Letting an agent write and run code safely

Envoy

An open-source network proxy, now a Cloud Native Computing Foundation project, that many gateways and load balancers are built on to route, secure and observe traffic.

Official docsUsed in: Part 12: Giving it to users

ERP

Enterprise resource planning: the core business system that runs orders, stock, finance and purchasing, such as SAP or Oracle.

Used in: Forward deployed engineering, Part 5: Enterprise integrations, APIs, connectors and identity, Part 17: Designing an agent system from scratch: a framework and five real-world scenarios

EU Member States

The 27 countries of the European Union, whose governments must approve EU laws and amendments alongside the European Parliament.

Used in: Your chatbot now has to say it's a chatbot

European Commission

The European Commission: the EU's executive body, which proposes laws and publishes guidance on how they should be applied.

Used in: Your chatbot now has to say it's a chatbot

Eval gate

An automated check that runs a fixed set of test questions and blocks a change from release if the scores fall below an agreed bar.

Used in: Forward deployed engineering, Part 9: LLM-native performance, latency, tokens and cost, Part 11.5: Fallbacks and budgets, Prerequisite 0: Before you build: what to have ready

event-driven

Built so that steps start in response to events, such as a message arriving or a previous step finishing, rather than following one fixed script.

Used in: Forward deployed engineering, Part 6: Agent frameworks compared

exact match

A scoring rule that gives full marks only if the model's output matches the reference answer character for character, and zero otherwise, with no partial credit.

Used in: Research papers, myth by myth, Part 6: 'Bigger models get smarter in sudden, unpredictable leaps'

exception

An error a Python program raises when something goes wrong; if nothing catches it, the running code stops.

Used in: Part 2: Your first agent: one job, narrow tools

exfiltrate

To copy data out of a system without permission, for example by sending it to a server the attacker controls.

Used in: Part 12.9: Long-running agents: work that carries on after the tab closes

External location

A Unity Catalog object that pairs a cloud storage path with a storage credential, so access to files under that path can be granted and audited.

Official docsUsed in: Part 10: Migration to Google Cloud, Part 4: Serverless networking and egress, Part 6: Governance and security

F

f-string

A Python string written with an f prefix that inserts variable values directly into the text, which is unsafe for building SQL from user input.

Used in: Forward deployed engineering, Part 7: Prototype in days, production in weeks

failover

Switching automatically to a backup, such as another model, provider or server, when the first one fails or is unavailable.

Used in: Part 1.75: Agent frameworks, and where ADK fits

faithful (chain of thought)

Describes a chain of thought that accurately reflects the factors that actually produced the model's answer, including any shortcut or hint it relied on.

Used in: Research papers, myth by myth, Part 5: 'A model's chain of thought shows how it really reached the answer'

FastAPI

A popular open-source Python framework for building web APIs quickly, with request checking based on Python type hints.

Used in: Part 12.5: Front doors and runtimes: Gemini Enterprise, the alternatives, and agents that run anywhere

FCA

Financial Conduct Authority: the UK regulator for financial services firms and the promotions they publish.

Used in: Part 6.5: Multi-agent topologies beyond a router

federating

Querying data where it already lives, from another system, instead of copying it into one place first.

Used in: Forward deployed engineering, Part 1: What a forward deployed engineer actually does

few-shot prompting

Showing a model a few worked examples inside the prompt so it copies the pattern, with no change to the model's weights.

Used in: Research papers, myth by myth, Part 5: 'A model's chain of thought shows how it really reached the answer'

FIPS 140

A US government standard for testing and certifying that the modules performing encryption do it correctly and securely.

Used in: Part 6: Governance and security

Firebase

Google's platform for building web and mobile apps, providing hosting, sign-in and databases as managed services.

Official docsUsed in: Rally Point: badminton rules you can see, and a scorer an umpire can trust, Your chatbot now has to say it's a chatbot

firewall rule

A rule on a VPC network that allows or blocks traffic to or from virtual machines, by address range, port and protocol.

Used in: Part 9: Commercials, quotas and operations

FLOPs

Floating point operations: individual multiplications or additions on decimal numbers. Training compute is counted as the total number of them, often written like 5.76 x 10^23.

Used in: Research papers, myth by myth, Part 6: 'Bigger models get smarter in sudden, unpredictable leaps'

FOIA

Freedom of Information Act: the US law that lets the public request records held by federal agencies.

Used in: Part 11.75: What Gemini Enterprise is: one work agent, connectors, skills, plugins and sandboxes

foreign catalog

A Unity Catalog catalog that mirrors the databases and tables of an external system, so Databricks users can query them by name.

Used in: Part 8: Better together, BigQuery, Gemini and Google Cloud services

frontend

The part of an application the user sees and interacts with, such as a web page or mobile app.

Used in: Part 12.75: How agents show more than text: A2UI, AG-UI and MCP Apps

G

garbage collection

A runtime feature that automatically frees memory a program is no longer using.

Used in: Learning Cloud through GCP — Part 2: How can I consume Cloud ?

gcloud

The Google Cloud command line tool, used to create, inspect and manage resources from a terminal or script.

Used in: Part 1: Foundations, how Databricks is built on Google Cloud

GDPR

General Data Protection Regulation: the EU law on how organisations collect, use, store and protect personal data.

Official docsUsed in: Prerequisite 4: Security words for agents: prompt injection and the rest

Gemini Enterprise Agent Platform

Gemini Enterprise Agent Platform: Google Cloud's unified platform for building, deploying, governing and optimising AI agents and models, the evolution of Vertex AI.

Official docsUsed in: Forward deployed engineering, Part 9: LLM-native performance, latency, tokens and cost, Part 2.5: Inside ToolContext, the object every tool receives

Gemini Flash

Gemini Flash: the faster, cheaper family of Gemini models, suited to simple, high-volume steps.

Official docsUsed in: Part 10: Proving it works, evals that gate releases, Part 5: The router, let code choose the path

Gemma 2

Google's family of open models, with published weights, released in 2024 in 2B, 9B and 27B parameter sizes.

Official docsUsed in: Research papers, myth by myth, Part 3: 'Nobody can see inside a model'

Genie

Databricks' natural language experience that lets business users ask questions of governed data and answers them by generating SQL over Unity Catalog tables.

Official docsUsed in: Forward deployed engineering, Part 5: Enterprise integrations, APIs, connectors and identity, Part 13.75: Preparing data for agents: structured and unstructured

Git

A version control system that records every change to a set of files, who made it and when, so changes can be reviewed and undone.

Used in: Part 9: Commercials, quotas and operations

GitHub Actions

GitHub's built-in service for running automated workflows, such as tests and deployments, whenever code changes.

Used in: Prerequisite 3: Identity and security foundations

Google Gen AI Python SDK

Google's Gen AI software development kit for Python: a library of ready-made functions for calling Gemini from code.

Official docsUsed in: Prerequisite 3: How a model works: tokens, context, settings and what we never ask it to do

GPQA

A benchmark of very hard, graduate level multiple choice science questions written by experts and designed to be hard to answer even with a web search.

Official docsUsed in: Research papers, myth by myth, Part 5: 'A model's chain of thought shows how it really reached the answer'

GPU

Graphics processing units: chips with thousands of small cores that do many simple calculations at the same time, which is why they suit training AI models.

Used in: Research papers, myth by myth, Part 1: 'An AI reads one word at a time, like we do'

grants

Permissions given to a user or group on an object, such as the right to read one table.

Used in: Part 3: Letting an agent touch data safely, Prerequisite 2: The business terms and the data behind the agents

graph workflow

An agent built as a graph: each node is a step or an agent, and each edge says which step runs after which.

Used in: Forward deployed engineering, Part 8: Debugging in the field

gRPC

An open-source framework, created at Google, for one program to call functions in another over the network using compact binary messages.

Official docsUsed in: Part 12: Giving it to users

GSM8K

A public test set of about 8,500 grade school maths word problems, each needing a few steps of arithmetic, widely used to measure reasoning over several steps in language models.

Official docsUsed in: Research papers, myth by myth, Part 5: 'A model's chain of thought shows how it really reached the answer'

gVisor

An open-source Google sandbox that sits between a container and the host operating system, intercepting system calls so the code cannot touch the real kernel directly.

Used in: Part 3.5: Letting an agent write and run code safely

H

Hadoop

An older open-source framework for storing and processing very large datasets across a cluster of ordinary servers.

Used in: Part 10: Migration to Google Cloud

hallucinates

Produces something that sounds plausible but is false or not supported by its input, stated as confidently as a fact.

Used in: Part 4: Skills, teaching an agent how, Research papers, myth by myth, Part 4: 'Hallucinations are random glitches'

hard-coded

Written directly into the code as a fixed value, so it does not change unless someone edits the code.

Used in: Prerequisite 2: The business terms and the data behind the agents

harness

The code around a model that runs it: it builds each prompt, calls the model, runs the tools it asks for and decides when to stop.

Used in: Part 1.25: The complete architecture, one picture for the whole series

headers

Named fields sent with a network request, separate from its body, often used to carry credentials and other details about the call.

Used in: Part 1.5: The harness, the loop and the context, Prerequisite 3: How a model works: tokens, context, settings and what we never ask it to do

held-out eval set

Test questions kept apart from everything used to build or tune the system, so the score reflects how it handles questions it has not seen.

Used in: Forward deployed engineering, Part 10: Talking to executives and proving the outcome, Research papers, myth by myth, Part 8: 'Human feedback teaches a model the truth'

HIPAA

The US Health Insurance Portability and Accountability Act, which sets rules for protecting patients' health information.

Used in: Part 9: Commercials, quotas and operations

Hive metastore

The older table catalogue, from Apache Hive, that each Databricks workspace kept for itself before Unity Catalog moved governance to the account level.

Used in: Part 1: Foundations, how Databricks is built on Google Cloud, Part 5: Storage, Cloud Storage and how Unity Catalog uses it

horizontal scalability

Growing capacity by adding more machines, rather than buying one bigger machine.

Used in: Learning Cloud through GCP — Part 4: Where do I store my data on Cloud ?

HTTP

Hypertext Transfer Protocol: the request and response language browsers and web servers use; HTTPS is the same protocol wrapped in encryption.

Used in: Learning Cloud through GCP — Part 5: How do I connect to my cloud ?

hypervisor

The software layer that splits one physical server into several virtual machines and keeps each one isolated from the others.

Used in: GPUs, TPUs and why AI is slow where it is: compute, memory bandwidth, the KV cache and the software in between, Learning Cloud through GCP — Part 3: Where do I compute on cloud ?

I

IAM allow policy

A Google Cloud rule set attached to a resource that lists which identities hold which IAM roles on it, and so what they may do.

Official docsUsed in: Part 1.25: The complete architecture, one picture for the whole series, Part 6: Agents talking to agents

IAM role

A named set of Google Cloud permissions that you grant to a person, group, service account or agent on a resource.

Official docsUsed in: from the basics

ICT

Information and communications technology: the computers, networks, software and services an organisation runs on.

Used in: Prerequisite 5: Compliance for AI systems: what an architect needs to know

identity provider

The system that signs people in and knows which groups they belong to, such as Microsoft Entra ID, Okta or Google Identity.

Used in: Forward deployed engineering, from the basics, Part 11.75: What Gemini Enterprise is: one work agent, connectors, skills, plugins and sandboxes

IETF

The Internet Engineering Task Force, the open standards body that develops core internet protocols such as HTTP and TLS.

Used in: Prerequisite 3: Identity and security foundations

implicit caching

Automatic reuse of a prompt's repeated opening text that the platform has seen recently, billed at a lower rate without you setting anything up.

Used in: GPUs, TPUs and why AI is slow where it is: compute, memory bandwidth, the KV cache and the software in between, Part 13: Choosing and running models for agents

in-context learning

A model picking up a pattern or task from examples inside the prompt itself, with no change to its weights.

Official docsUsed in: Research papers, myth by myth, Part 1: 'An AI reads one word at a time, like we do'

indemnification

A promise in a contract to cover the other party's legal costs and damages if a specific kind of claim is made against them.

Used in: Prerequisite 5: Compliance for AI systems: what an architect needs to know

ingress rules

VPC Service Controls rules that allow specific identities or networks outside a perimeter to reach the protected services inside it.

Used in: Forward deployed engineering, Part 3: Designing inside someone else's estate

init script

A shell script that a Databricks cluster runs on every node as it starts, for example to install software or set configuration.

Used in: Part 1: Foundations, how Databricks is built on Google Cloud

inpainting

Editing only a chosen area of an image, such as the background, while the rest of the picture, such as the product, stays as it was.

Used in: Part 17: Designing an agent system from scratch: a framework and five real-world scenarios

input schema

A machine-readable description of the arguments a tool accepts, with each field's name and type, so the model knows how to call it.

Used in: Part 11.75: What Gemini Enterprise is: one work agent, connectors, skills, plugins and sandboxes

instance profiles

An AWS wrapper around an IAM role that lets programs on a virtual machine use that role's permissions without any stored keys.

Used in: Part 2: Identity and access, IAM, service accounts, single sign-on and automation

Interactions API

A Gemini API interface for calling models and agents, such as the Deep Research agent; long tasks can run in the background while the caller polls for the result.

Official docsUsed in: Part 17: Designing an agent system from scratch: a framework and five real-world scenarios

internal load balancer

A Google Cloud load balancer with a private IP address that spreads traffic from inside your network across the machines behind it.

Used in: Part 3: Networking: VPC, Cloud NAT, Private Google Access and Private Service Connect

interpretability

Research that looks inside a model's internal numbers and pathways, such as features and circuits, to explain how it actually computes an answer.

Used in: Research papers, myth by myth, Part 3: 'Nobody can see inside a model', Research papers, myth by myth, Part 5: 'A model's chain of thought shows how it really reached the answer'

invocation

In ADK, everything that happens to answer one user message, from receiving it to the final reply.

Used in: Part 11.5: Fallbacks and budgets

IPv4

Internet Protocol version 4: the original internet addressing scheme, written as four numbers from 0 to 255 separated by dots, with about 4.3 billion possible addresses.

Used in: Learning Cloud through GCP — Part 5: How do I connect to my cloud ?

IPv6

Internet Protocol version 6: the newer addressing scheme with vastly more addresses than IPv4, written as eight groups of hexadecimal digits separated by colons.

Used in: Learning Cloud through GCP — Part 5: How do I connect to my cloud ?

ISO 8601

The international standard way to write dates and times, such as 2026-10-20T14:05:00Z, so there is no doubt about format or time zone.

Used in: Forward deployed engineering, Part 8: Debugging in the field

ISP

Internet service provider: the company, such as BT or Virgin Media, that connects your home or office to the internet.

Used in: Learning Cloud through GCP — Part 5: How do I connect to my cloud ?

J

JDBC and ODBC

Standard database driver interfaces, JDBC for Java and ODBC for most other languages, that BI tools and programs use to connect to a database and run SQL.

Used in: Part 3: Networking: VPC, Cloud NAT, Private Google Access and Private Service Connect, Part 4: Serverless networking and egress, Part 6: Governance and security

Jensen-Shannon divergence

A number between 0 and 1 for how different two distributions are; 0 means identical. Model Monitoring uses it to compare live feature values with a baseline.

Used in: Prerequisite 2.75: MLOps and LLMOps: keeping models and agents right after launch

join keys

The columns used to match rows in one table with rows in another, such as brand, region and week.

Used in: Part 4: Skills, teaching an agent how

JSON Pointer

A short path string, standardised in RFC 6901, that picks one value out of a JSON document, such as /results/0/title.

Official docsUsed in: Connectors, MCP and plugins explained: who builds the link, where the data lives, and can a custom MCP server stay private?

JSON-RPC

A lightweight protocol for asking another program to run a named method, with the request and the reply both written as JSON.

Used in: Let people ask your lakehouse questions: wiring Gemini Enterprise to Databricks Genie, Part 6: Agents talking to agents

JWT (JSON Web Token)

JSON Web Token: a compact, signed set of claims, such as who the user is and when access expires, that anyone holding it can read and the receiver can verify.

Official docsUsed in: Part 11: Deploy, observe and pay for it, Part 7: Who is asking? Identity for agents, Prerequisite 4: Security words for agents: prompt injection and the rest

K

k-means

A clustering method that places a chosen number of centre points, assigns each item to its nearest centre, then moves each centre to the middle of its group and repeats.

Used in: Research papers, myth by myth, Part 12: 'Nobody really knows how people use AI, and it is mostly replacing jobs'

key-value

Data stored as pairs of a name and its value, such as currency set to EUR, looked up by the name.

Used in: Part 8: Memory, what an agent should remember

knowledge graphs

Databases that store facts as entities and the relationships between them, such as retailer, has contract, contract version, so software can follow the links.

Used in: Forward deployed engineering, Part 4: Data readiness and RAG from zero

KPI

Key performance indicator: a headline number a business tracks to judge how something is doing, such as total spend.

Used in: Part 12.75: How agents show more than text: A2UI, AG-UI and MCP Apps

Kubernetes cluster

A group of machines managed by Kubernetes, open-source software that starts, restarts and scales containers across them.

Used in: Part 12.5: Front doors and runtimes: Gemini Enterprise, the alternatives, and agents that run anywhere

Kubernetes Job

A Kubernetes task that starts one or more containers, runs them until the work finishes, then stops.

Used in: Part 3.5: Letting an agent write and run code safely

L

L-infinity distance

For categories, the largest difference between the share of any one category in the two datasets, for example 30% of homes rural in training and 55% now gives 0.25.

Used in: Prerequisite 2.75: MLOps and LLMOps: keeping models and agents right after launch

Lakeflow

Databricks' family of data engineering tools for ingesting data, building data pipelines and orchestrating jobs.

Official docsUsed in: from the basics

lakehouse

A data platform that keeps tables as open files in low-cost object storage, then adds warehouse features such as transactions, governance and fast SQL.

Used in: from the basics, Part 5: Storage, Cloud Storage and how Unity Catalog uses it

Lakehouse Federation

A Databricks feature that gives governed, read-only access to tables in outside systems, such as BigQuery, through Unity Catalog foreign catalogs, without copying the data.

Official docsUsed in: Part 2: Identity and access, IAM, service accounts, single sign-on and automation, Part 6: Governance and security

landing-zone

A landing zone is the pre-built foundation of a cloud estate: hierarchy, networks, policies and access set up before workloads move in.

Used in: Prerequisite 2: What a cloud is, and what Google Cloud is

LangGraph

An open-source framework from the LangChain team for building agents as graphs of steps with shared state.

Used in: Forward deployed engineering, Part 1: What a forward deployed engineer actually does

LangSmith

LangChain's commercial platform for tracing, evaluating and deploying agents built with LangChain and LangGraph.

Used in: Forward deployed engineering, Part 6: Agent frameworks compared

leased line

A private, dedicated connection rented from a telecoms provider between two sites, offering steady bandwidth that is not shared with public internet traffic.

Used in: Learning Cloud through GCP — Part 1: What is Cloud ?

lineage

A record of where data came from and which tables, jobs, notebooks and dashboards it flows into.

Used in: Part 1: Foundations, how Databricks is built on Google Cloud, Part 8: Better together, BigQuery, Gemini and Google Cloud services

lint

An automatic check that reads source code without running it and flags style problems and likely mistakes.

Used in: Part 1.25: The complete architecture, one picture for the whole series

LiteLLM

An open-source Python library that offers one interface for calling models from many providers, such as OpenAI, Anthropic or a vLLM server.

Used in: Part 13: Choosing and running models for agents, Part 17: Designing an agent system from scratch: a framework and five real-world scenarios

local SSD

A solid state drive physically attached to the machine, much faster than network storage, whose data is lost when the machine is stopped.

Used in: Prerequisite 1: What a lakehouse is: storage, table formats and Spark

logistic regression

A simple model that multiplies each input by a learned weight, adds them up and squashes the total into a probability between 0 and 1.

Used in: Prerequisite 2.5: Traditional AI and generative AI: from regression and trees to neural networks

Looker

Google Cloud's business intelligence platform for dashboards and reports built on one shared, governed definition of the business metrics.

Used in: Part 7: The platform on Google Cloud, runtime, Photon, SQL, Lakeflow and AI

M

managed identity

An Azure identity for a resource or program whose credentials Azure creates and rotates itself, so no secret is stored in code.

Used in: Part 10: Migration to Google Cloud

managed tables

Unity Catalog tables whose files Databricks stores and looks after in governed storage, and deletes when the table is dropped.

Used in: Part 10: Migration to Google Cloud

Markdown

A simple plain-text format that uses symbols such as # for headings and * for lists, readable as it is and easy to turn into a web page.

Used in: Plugins vs agents: what changed in August 2026

market surveillance authority

The national regulator in each EU country that checks products on the market comply with the law and can demand evidence or withdrawals.

Used in: Prerequisite 5: Compliance for AI systems: what an architect needs to know

Medallion architecture

A common way to organise lakehouse tables in stages: raw data lands in bronze, is cleaned in silver and is shaped into business-ready tables in gold.

Official docsUsed in: Part 6: Governance and security, Part 8: Better together, BigQuery, Gemini and Google Cloud services

Metadata

Data that describes other data, such as who created a file and when, kept alongside the content rather than in it.

Used in: Part 1.25: The complete architecture, one picture for the whole series, Part 12.75: How agents show more than text: A2UI, AG-UI and MCP Apps, Your chatbot now has to say it's a chatbot

metadata server

A service built into every Compute Engine virtual machine that answers local requests for instance details and short-lived access tokens for its service account.

Used in: Prerequisite 2: What a cloud is, and what Google Cloud is, Prerequisite 3: Identity and security foundations

Metastore

A catalogue of table metadata; in Unity Catalog, the top-level container for a region that holds catalogs, schemas, tables and their permissions, which workspaces attach to.

Official docsUsed in: from the basics, Part 2: Identity and access, IAM, service accounts, single sign-on and automation, Prerequisite 2: What a cloud is, and what Google Cloud is

Metric views

Unity Catalog objects that store a business metric's agreed formula and dimensions once, so every query and tool uses the same definition.

Official docsUsed in: Prerequisite 0: Before you build: what to have ready

metrics

The rule used to turn a model's answers into a score, such as exact match, partial credit per token, or a score based on probabilities.

Used in: Research papers, myth by myth, Part 6: 'Bigger models get smarter in sudden, unpredictable leaps'

Microsoft Entra ID

Microsoft's cloud identity service, formerly Azure Active Directory, which signs employees in and manages their accounts and groups.

Official docsUsed in: Forward deployed engineering, Part 3: Designing inside someone else's estate

Middleware

Software that sits between applications and the operating system or other systems, such as a web server or message broker, providing shared services.

Used in: Learning Cloud through GCP — Part 4: Where do I store my data on Cloud ?, Learning Cloud through GCP — Part 5: How do I connect to my cloud ?

MIT licence

A short, permissive open-source licence: anyone may use, copy, change and sell the code, as long as they keep the copyright notice.

Used in: Three of my apps are now open source

MLflow

An open-source platform, created by Databricks, for tracking machine learning and AI experiments, tracing agents, evaluating quality and managing models.

Official docsUsed in: Part 1.75: Agent frameworks, and where ADK fits

MLP layer

Multi-layer perceptron: the part of each Transformer layer that transforms each token on its own after attention has mixed in information from other tokens.

Used in: Research papers, myth by myth, Part 2: 'It only predicts the next word', Research papers, myth by myth, Part 3: 'Nobody can see inside a model'

MMLU

Massive Multitask Language Understanding: a benchmark of multiple choice questions across 57 subjects, from law to physics, used to compare language models' knowledge and reasoning.

Official docsUsed in: Research papers, myth by myth, Part 5: 'A model's chain of thought shows how it really reached the answer', Research papers, myth by myth, Part 6: 'Bigger models get smarter in sudden, unpredictable leaps'

model alias

A model name, such as one ending in latest, that the provider can point at a newer model without you changing any code.

Used in: Part 15: What breaks in production: answers, loops, cost and model changes

Model card

A document a model provider publishes describing what a model is for, how it was trained and evaluated, its known limits and safety testing.

Used in: Prerequisite 3: How a model works: tokens, context, settings and what we never ask it to do, Prerequisite 4: Security words for agents: prompt injection and the rest

Model Garden

Google Cloud's catalogue of Google, partner and open models, from which you can call managed APIs or deploy open models to your own endpoints.

Official docsUsed in: Part 13: Choosing and running models for agents

Model Serving

Databricks' managed service for deploying, governing and querying machine learning and generative AI models behind REST API endpoints, for real-time and batch use.

Official docsUsed in: Part 4: Serverless networking and egress

model-agnostic

Able to work with models from different providers, not only the one it was designed around.

Used in: Forward deployed engineering, Part 6: Agent frameworks compared

N

Network peering

Joining two private networks, such as two VPC networks, so their internal IP addresses can reach each other directly without crossing the internet.

Official docsUsed in: Part 3: Networking: VPC, Cloud NAT, Private Google Access and Private Service Connect, Prerequisite 2: What a cloud is, and what Google Cloud is

network tab

The part of the browser's developer tools that lists every request a page makes and shows the data each one returns.

Used in: CV Builder: write your CV once, export it ten ways

network tag

A label on a VM that firewall rules and routes can target, so a rule applies only to machines carrying that tag.

Used in: Part 3: Networking: VPC, Cloud NAT, Private Google Access and Private Service Connect

next hop

Where a route sends matching traffic next, such as an internet gateway, a VM or a VPN tunnel.

Used in: Part 3: Networking: VPC, Cloud NAT, Private Google Access and Private Service Connect

Notebook

An interactive document, such as a Jupyter or Databricks notebook, that mixes runnable code cells with their results and notes, used to explore data and build jobs.

Used in: Prerequisite 1: What a lakehouse is: storage, table formats and Spark, Forward deployed engineering, Part 6: Agent frameworks compared, Part 3: Letting an agent touch data safely

O

O*NET

The Occupational Information Network: a US Department of Labor database describing around 20,000 work tasks and the occupations that perform them.

Official docsUsed in: Research papers, myth by myth, Part 12: 'Nobody really knows how people use AI, and it is mostly replacing jobs'

observability

Being able to see what a running system did and why, from the traces, logs and metrics it records.

Used in: Part 1.5: The harness, the loop and the context

on-call rota

The schedule of who is responsible, at any hour, for responding when a production system raises an alert.

Used in: Forward deployed engineering, Part 7: Prototype in days, production in weeks

On-premises

Running in a company's own buildings or data centres, on hardware it owns and operates, rather than in a public cloud.

Used in: Part 3: Networking: VPC, Cloud NAT, Private Google Access and Private Service Connect, Learning Cloud through GCP — Part 3: Where do I compute on cloud ?

ontologies

Formal, agreed definitions of the types of things in a domain and how they relate, which give a knowledge graph its vocabulary and rules.

Used in: Forward deployed engineering, Part 4: Data readiness and RAG from zero

OpenAPI

A standard, machine-readable way to describe a REST API: its paths, parameters and request and response formats, so tools can call it.

Used in: Part 1.9: How agents connect: MCP, A2A and UTCP, Part 6: Agents talking to agents

OpenSharing

Databricks' open protocol, formerly called Delta Sharing, for sharing live tables and other assets with other organisations and platforms without copying the data.

Official docsUsed in: Part 5: Storage, Cloud Storage and how Unity Catalog uses it, Part 6: Governance and security

OpenTelemetry

An open-source standard and toolkit for producing traces, metrics and logs in one format that many monitoring tools can read.

Official docsUsed in: Part 1.75: Agent frameworks, and where ADK fits, Part 17: Designing an agent system from scratch: a framework and five real-world scenarios

orchestration

Software that automatically starts, stops, scales and places workloads on servers according to demand.

Used in: Learning Cloud through GCP — Part 2: How can I consume Cloud ?

Orchestrator

A coordinating program or agent that splits work into tasks, triggers each one in the right order on the right system or agent, and combines the results.

Used in: Part 9: Commercials, quotas and operations, Part 12.5: Front doors and runtimes: Gemini Enterprise, the alternatives, and agents that run anywhere

over-refusal

When a model or safety filter declines a harmless request because it wrongly looks risky, such as refusing a question about mustard because mustard gas exists.

Used in: Research papers, myth by myth, Part 11: 'You cannot stop jailbreaks without making the model useless'

P

pandas

A popular Python library for loading, reshaping and summarising tables of data.

Used in: Part 12.9: Long-running agents: work that carries on after the tab closes

Parquet

An open file format that stores data column by column, compressed, so analytical queries read only the columns they need.

Used in: Part 10: Migration to Google Cloud, Part 5: Storage, Cloud Storage and how Unity Catalog uses it, Part 7: The platform on Google Cloud, runtime, Photon, SQL, Lakeflow and AI

PCI-DSS

The Payment Card Industry Data Security Standard, which any company that stores, processes or transmits card data must meet.

Used in: Part 9: Commercials, quotas and operations, Part 17: Designing an agent system from scratch: a framework and five real-world scenarios

PECR

The Privacy and Electronic Communications Regulations: the UK rules on electronic marketing such as emails and texts, and on cookies, which sit alongside UK GDPR.

Official docsUsed in: Part 17: Designing an agent system from scratch: a framework and five real-world scenarios

PEP 604

The Python Enhancement Proposal that lets you write a union of types with a vertical bar, such as str | None, supported from Python 3.10.

Official docsUsed in: Part 2.5: Inside ToolContext, the object every tool receives

persistent disk

Network-attached block storage for Compute Engine, whose data lives independently of the virtual machine it is attached to.

Used in: Part 9: Commercials, quotas and operations

Photon

The Databricks native vectorised query engine, written in C++, which runs SQL and DataFrame work faster than standard Spark.

Official docsUsed in: Prerequisite 1: What a lakehouse is: storage, table formats and Spark

PKCE

Proof Key for Code Exchange: an OAuth add-on in which the app proves it started the sign-in, designed for apps that cannot keep a secret.

Official docsUsed in: Forward deployed engineering, Part 5: Enterprise integrations, APIs, connectors and identity

post-training

The training stages after pretraining, such as tuning on example answers and reinforcement learning, that turn a base model into a helpful assistant.

Used in: Research papers, myth by myth, Part 4: 'Hallucinations are random glitches'

power law

A relationship where one quantity changes as a fixed power of another, so it appears as a straight line when both are plotted on logarithmic scales.

Used in: Research papers, myth by myth, Part 6: 'Bigger models get smarter in sudden, unpredictable leaps', Research papers, myth by myth, Part 7: 'More context is always better'

PPO

Proximal Policy Optimization: a reinforcement learning algorithm that improves a model in small, limited steps so each update cannot change its behaviour too much at once.

Official docsUsed in: Research papers, myth by myth, Part 8: 'Human feedback teaches a model the truth'

Predictive optimisation

A Databricks service that automatically runs table maintenance, such as compaction and VACUUM, on Unity Catalog managed tables.

Official docsUsed in: Part 9: Commercials, quotas and operations

preference model

A model trained on people's choices between pairs of answers, which then gives any new answer a score for how much people would prefer it.

Used in: Research papers, myth by myth, Part 11: 'You cannot stop jailbreaks without making the model useless'

pretraining

The first and largest training stage, where a model learns to predict the next token across a huge collection of text.

Used in: Research papers, myth by myth, Part 4: 'Hallucinations are random glitches'

private key

The secret half of a cryptographic key pair, kept only by its owner and used to prove identity or sign data.

Used in: Long-running agents explained: what changes when an agent keeps working after you close the tab

Pro

Gemini Pro: the larger, more capable family of Gemini models, slower and dearer than Flash, used where reasoning quality matters most.

Used in: Part 5: The router, let code choose the path

probe

A small, cheap classifier that reads a model's internal activations, the numbers inside it while it processes text, to spot a pattern such as harmful intent.

Used in: Research papers, myth by myth, Part 11: 'You cannot stop jailbreaks without making the model useless'

Protocol Buffers

Google's language-neutral format for describing structured data in a schema file and serialising it compactly between programs.

Used in: Part 1.9: How agents connect: MCP, A2A and UTCP

proxy

A server that forwards requests on behalf of other machines, often used as the single controlled exit point to the internet.

Used in: Forward deployed engineering, Part 3: Designing inside someone else's estate

public key cryptography

Encryption that uses a pair of keys: a private key kept secret to sign or decrypt, and a public key anyone can use to verify or encrypt.

Used in: Learning Cloud through GCP — Part 5: How do I connect to my cloud ?

Pull request

A proposed change to a code repository that others review and automated checks test before it is merged into the main branch.

Used in: Part 10: Proving it works, evals that gate releases, Part 11: Deploy, observe and pay for it

pure functions

Functions whose output depends only on their inputs and which change nothing outside themselves, so the same input always gives the same result and testing is easy.

Used in: Three of my apps are now open source

push notifications

Messages a server sends to a client's own web address when something changes, so the client does not have to keep asking.

Used in: Part 6: Agents talking to agents

Pydantic

A Python library that defines data shapes as classes with typed fields and checks that incoming data matches them.

Used in: Part 10: Proving it works, evals that gate releases, Part 11.5: Fallbacks and budgets

PyPI

The Python Package Index, the public repository from which Python libraries are usually installed with pip.

Used in: Part 1: Foundations, how Databricks is built on Google Cloud

pytest

A widely used open-source Python testing framework: it finds functions named test_ and reports which pass and which fail.

Used in: Part 10: Proving it works, evals that gate releases

Q

Quantised (4-bit)

Stored with fewer bits per number, for example 4 instead of 16, which saves memory and speeds up a model at the cost of a little precision.

Used in: GPUs, TPUs and why AI is slow where it is: compute, memory bandwidth, the KV cache and the software in between, Part 14: Knowledge: RAG, long context, fine-tuning and the infrastructure behind them

quota

The amount of use, such as model calls per minute or per day, that a project is allowed before further requests are refused or billed.

Used in: CV Builder: write your CV once, export it ten ways

R

RAG Engine

A managed service in Gemini Enterprise Agent Platform that imports, chunks, embeds and indexes documents, then retrieves relevant passages so a model can ground its answers.

Official docsUsed in: Part 13: Choosing and running models for agents, Part 13.75: Preparing data for agents: structured and unstructured

ReAct

An agent pattern that loops: the model reasons about what to do, calls a tool, reads the result, and repeats until it can answer.

Used in: Forward deployed engineering, from the basics

React

A popular JavaScript library for building web interfaces out of reusable components.

Used in: Practice Time: an app that listens to a child read

Reasoning model

A model that works through a problem in internal reasoning steps before giving its final answer, trading extra time and tokens for better answers on hard questions.

Used in: Forward deployed engineering, Part 9: LLM-native performance, latency, tokens and cost, Part 6: Agents talking to agents, Research papers, myth by myth, Part 5: 'A model's chain of thought shows how it really reached the answer'

refactor

Restructuring existing code to tidy or improve it without meaning to change what it does.

Used in: Part 3: Letting an agent touch data safely

refresh token

A longer-lived token the app keeps so it can get a fresh access token later without asking the user to sign in again.

Used in: Part 12: Giving it to users

region

A specific geographic area, such as London or Iowa, where a cloud provider runs a cluster of data centres you can choose to place resources in.

Used in: Learning Cloud through GCP — Part 1: What is Cloud ?

Regular expression

A compact text pattern, such as one matching any email address or run of digits, that code uses to find, check or replace text.

Used in: Meal Tracker: log a meal by taking a photo, Part 6.5: Multi-agent topologies beyond a router

rejection sampling

Generating several candidate answers and returning only the one a scoring model rates best; in this paper, the best of 16 by a harmlessness score.

Used in: Research papers, myth by myth, Part 11: 'You cannot stop jailbreaks without making the model useless'

release candidate

A version believed to be ready for final release, published so people can test it before it is declared stable.

Used in: Part 12.75: How agents show more than text: A2UI, AG-UI and MCP Apps

release pipeline

The automated sequence of build, test and deploy steps that takes a code change from the repository to production.

Used in: Part 10: Proving it works, evals that gate releases

ReLU

A simple function used inside neural networks that passes positive numbers through unchanged and turns negative numbers into zero.

Used in: Research papers, myth by myth, Part 3: 'Nobody can see inside a model'

reorder points

The stock level for a product at which a new order should be placed, set so the delivery arrives before the shelf runs empty.

Used in: Long-running agents explained: what changes when an agent keeps working after you close the tab

reservations

A Compute Engine reservation holds VM capacity of a chosen machine type in one zone, so it is guaranteed to be there when you need it.

Used in: Part 1: Foundations, how Databricks is built on Google Cloud

residual stream

The running vector each token carries from layer to layer in a Transformer; every layer reads from it and adds its own result back.

Official docsUsed in: Research papers, myth by myth, Part 1: 'An AI reads one word at a time, like we do', Research papers, myth by myth, Part 3: 'Nobody can see inside a model'

resolvers

DNS resolvers are the servers that look up names on a device's behalf and return the matching IP addresses.

Used in: Part 3: Networking: VPC, Cloud NAT, Private Google Access and Private Service Connect

Resumability

An ADK app setting that saves a run's progress, so a run that is interrupted or paused for approval can continue later from the same point.

Used in: Part 1.5: The harness, the loop and the context, Part 15: What breaks in production: answers, loops, cost and model changes, Part 9: Guardrails that cannot be talked around

retrieval

Searching a document store for the passages most relevant to a question, so they can be handed to the model with the question.

Used in: Part 13.75: Preparing data for agents: structured and unstructured

reward hacking

When a model trained with rewards finds a loophole that earns the reward without doing the intended task, such as gaming a grader instead of answering correctly.

Used in: Research papers, myth by myth, Part 5: 'A model's chain of thought shows how it really reached the answer'

RLHF

Reinforcement learning from human feedback: people compare pairs of answers, a model learns their preferences, and the assistant is trained to give answers that model scores highly.

Official docsUsed in: Research papers, myth by myth, Part 11: 'You cannot stop jailbreaks without making the model useless', Research papers, myth by myth, Part 4: 'Hallucinations are random glitches', Research papers, myth by myth, Part 9: 'If it passed safety training, the bad behaviour is gone'

ROC-AUC

A score up to 1 for how well a classifier ranks positive cases above negative ones across every possible cutoff; 0.5 is no better than chance.

Used in: Prerequisite 2.75: MLOps and LLMOps: keeping models and agents right after launch

Row filters and column masks

Unity Catalog rules applied at query time: row filters hide rows a user may not see, and column masks hide or blank column values, depending on who runs the query.

Official docsUsed in: Part 7: The platform on Google Cloud, runtime, Photon, SQL, Lakeflow and AI, Part 8: Better together, BigQuery, Gemini and Google Cloud services

runbook

A written step-by-step guide that tells the on-call person what to check and do when a known problem happens.

Used in: Prerequisite 0: Before you build: what to have ready

Runner

The ADK object that runs an agent: it takes the user's message, drives the model and tool calls, and saves events to the session.

Used in: Part 2.5: Inside ToolContext, the object every tool receives

S

S&OP (sales and operations planning)

Sales and operations planning: the regular business process that balances demand forecasts against supply, production and stock plans.

Used in: Part 11.5: Fallbacks and budgets, Prerequisite 4: Security words for agents: prompt injection and the rest

SaaS

Software as a service: software the vendor runs and maintains for you, used over the internet on a subscription.

Used in: Part 9: Commercials, quotas and operations

SAML

Security Assertion Markup Language: an older single sign-on standard in which the identity provider sends the application a signed XML statement about the user.

Used in: Forward deployed engineering, from the basics

sandboxes

Isolated environments where untrusted code can run without being able to reach or harm the rest of the system.

Used in: Part 3: Letting an agent touch data safely

SASE (Secure Access Service Edge)

Secure Access Service Edge: a cloud service between employees and the internet that combines network access with security checks such as web filtering and data loss prevention.

Used in: Part 17: Designing an agent system from scratch: a framework and five real-world scenarios, Prerequisite 4: Security words for agents: prompt injection and the rest

scaffold

The starter project that agents-cli generates, with sample agent, test, eval and deployment files you then replace or extend.

Used in: Part 10: Proving it works, evals that gate releases

scale down to zero

Shut down every running copy of a service when no requests arrive, so you pay nothing while it is idle and it starts again on the next request.

Used in: Learning Cloud through GCP — Part 3: Where do I compute on cloud ?

schema

In Unity Catalog, a named folder inside a catalog that groups related tables and views.

Used in: Prerequisite 2: The business terms and the data behind the agents

schemas

The description of a table's structure: its column names, their data types and how the columns are arranged.

Used in: Part 2: Your first agent: one job, narrow tools

SCIM

SCIM: System for Cross-domain Identity Management, a standard protocol an identity provider uses to create, update and remove users and groups in another system automatically.

Official docsUsed in: Part 8: Better together, BigQuery, Gemini and Google Cloud services, Forward deployed engineering, from the basics

scratchpad

A private space where a model writes out its step-by-step reasoning before answering; researchers read it to see why the model acted as it did.

Used in: Research papers, myth by myth, Part 9: 'If it passed safety training, the bad behaviour is gone'

Secret Manager

Google Cloud's service for storing passwords, API keys and other secrets, with access controlled by IAM.

Official docsUsed in: Part 8: Better together, BigQuery, Gemini and Google Cloud services

self-signed certificate

A TLS certificate signed with its own key instead of by a certificate authority, so clients trust it only if they are told to explicitly.

Used in: Connectors, MCP and plugins explained: who builds the link, where the data lives, and can a custom MCP server stay private?

Semantic Kernel

Microsoft's open-source SDK for adding AI models, plugins and planning to C#, Python and Java applications.

Used in: Forward deployed engineering, Part 6: Agent frameworks compared

semantic layer

A shared set of business definitions, such as metric formulas and column meanings, that sits between raw tables and the people or tools querying them.

Used in: Prerequisite 0: Before you build: what to have ready

service control policy

An AWS Organizations policy that caps the permissions available in accounts below it, whatever their own IAM grants say.

Used in: Part 1: Foundations, how Databricks is built on Google Cloud

service worker

A script the browser runs in the background for a website, which can cache its files so the site works offline.

Used in: Rally Point: badminton rules you can see, and a scorer an umpire can trust, Three of my apps are now open source

SFTP

SSH File Transfer Protocol, a common way to copy files securely to and from a server.

Used in: Part 4: Serverless networking and egress

Shadow mode

Running a new version on copies of real traffic alongside the current one, logging its answers for comparison while users still get the current version's answers.

Used in: Part 11: Deploy, observe and pay for it, Part 13: Choosing and running models for agents, Prerequisite 2.75: MLOps and LLMOps: keeping models and agents right after launch

Shared VPC

A Google Cloud setup where one host project owns a network and other projects run their machines in its subnets.

Official docsUsed in: Part 2: Identity and access, IAM, service accounts, single sign-on and automation, Part 4: Serverless networking and egress

SharePoint

Microsoft's platform for team sites and document libraries, widely used inside companies to store and share files.

Used in: Forward deployed engineering, Part 4: Data readiness and RAG from zero

Shuffle

The step where a distributed engine such as Spark moves rows between machines so rows sharing a key end up together, for a join or grouping.

Used in: Part 1: Foundations, how Databricks is built on Google Cloud, Part 7: The platform on Google Cloud, runtime, Photon, SQL, Lakeflow and AI

side effects

Changes a step makes outside itself, such as starting a job or writing to a database, beyond just returning a result.

Used in: Part 8: Memory, what an agent should remember

signed URLs

Web addresses carrying a time-limited signature that grants temporary access to one Cloud Storage object without any other credentials.

Used in: Part 3: Networking: VPC, Cloud NAT, Private Google Access and Private Service Connect

SKUs

Stock keeping units: the unique codes a retailer gives each distinct product variant, such as one boot model in one size.

Used in: Long-running agents explained: what changes when an agent keeps working after you close the tab, Part 17: Designing an agent system from scratch: a framework and five real-world scenarios

SLA

Service level agreement: a provider's written commitment to a level of service, such as uptime, often with credits if it is missed.

Used in: Learning Cloud through GCP — Part 2: How can I consume Cloud ?

softmax

A function that turns a list of scores into positive weights that add up to 1, giving the largest share to the highest score.

Used in: Research papers, myth by myth, Part 1: 'An AI reads one word at a time, like we do'

source ports

Numbered slots on an IP address that keep outbound connections apart; each connection a VM opens through Cloud NAT uses one.

Used in: Part 9: Commercials, quotas and operations

split loads

Shipping one order in several smaller deliveries instead of one full truck, which costs more per unit.

Used in: Prerequisite 2: The business terms and the data behind the agents

SQL

Structured Query Language: the standard language for asking a database for data, for example to select spend for one brand.

Used in: Part 1: What an agent really is, and the system we will build, Part 4: Skills, teaching an agent how, Part 9: Guardrails that cannot be talked around

SQL injection

A security hole where text typed into an app is run as part of a database query, letting an attacker read or change data they should not reach.

Official docsUsed in: Research papers, myth by myth, Part 9: 'If it passed safety training, the bad behaviour is gone'

SQLite

A small database engine that keeps a whole database in one ordinary file, with no separate server to run.

Used in: Part 1: What an agent really is, and the system we will build

SRAM

Very fast memory built into the chip itself, far smaller than HBM, used to keep the data the chip needs right now close to the maths.

Used in: GPUs, TPUs and why AI is slow where it is: compute, memory bandwidth, the KV cache and the software in between

SRE

Site reliability engineering: Google's discipline of running production systems with software engineering methods, described in its public SRE books.

Used in: Forward deployed engineering, Part 7: Prototype in days, production in weeks

StableHLO

An open, portable format for describing machine learning computations, used to hand a model from a framework such as PyTorch or JAX to a compiler such as XLA.

Official docsUsed in: GPUs, TPUs and why AI is slow where it is: compute, memory bandwidth, the KV cache and the software in between

staged rollout

Releasing a change to a small group of users first and widening it step by step, so problems are caught before everyone is affected.

Used in: Forward deployed engineering, Part 7: Prototype in days, production in weeks

staging

A copy of the system set up like production but not used by real users, where changes are tried before release.

Used in: Part 11: Deploy, observe and pay for it

Standard PayGo

Standard pay as you go: paying per token with no reserved capacity, so your requests share Google's capacity with other customers.

Official docsUsed in: Part 15: What breaks in production: answers, loops, cost and model changes

stateless

Describes a service that keeps no memory of earlier requests itself, storing any data elsewhere, so any copy of it can handle any request.

Used in: Learning Cloud through GCP — Part 3: Where do I compute on cloud ?

static site

A website made of pre-built files served as they are, with no server-side program creating pages for each visitor.

Used in: Your chatbot now has to say it's a chatbot

stdout and stderr

Standard output and standard error: the two text streams every program writes to by default, for normal output and for error messages.

Used in: Part 11: Deploy, observe and pay for it

stockouts

Times when a product has run out at a store or warehouse, so customers cannot buy it.

Used in: Forward deployed engineering, Part 2: Discovery, from a business problem to something you can build

Storage credential

A Unity Catalog object that wraps a cloud identity, such as a Google service account or an AWS IAM role, which Databricks uses to reach a storage bucket.

Official docsUsed in: Part 10: Migration to Google Cloud, Part 4: Serverless networking and egress, Part 6: Governance and security

Streamable HTTP

The current MCP transport, in which the client sends requests over ordinary HTTP and the server can stream its replies back on the same connection.

Used in: Connectors, MCP and plugins explained: who builds the link, where the data lives, and can a custom MCP server stay private?, Plugins vs agents: what changed in August 2026

sub-processors

Other companies a processor hires to help handle the customer's personal data, such as a data centre or support provider.

Used in: Prerequisite 5: Compliance for AI systems: what an architect needs to know

Subnet

A range of IP addresses carved out of a network, usually written in CIDR notation; for example, a /28 range holds 16 addresses.

Used in: Forward deployed engineering, Part 3: Designing inside someone else's estate

synchronous

Done while the caller waits for the result, as opposed to submitted now and collected later.

Used in: Forward deployed engineering, Part 9: LLM-native performance, latency, tokens and cost

synthetic data

Training examples generated by a model or program instead of collected from real people, used when real examples are rare, sensitive or costly.

Used in: Research papers, myth by myth, Part 11: 'You cannot stop jailbreaks without making the model useless'

SynthID

Google's technology for adding an invisible watermark to AI-generated content, such as images, that software can later detect.

Used in: Part 17: Designing an agent system from scratch: a framework and five real-world scenarios

T

tau-bench

A 2024 benchmark from Sierra that tests agents on realistic multi-turn customer service tasks with tools, simulated users and policy rules.

Official docsUsed in: Part 10: Proving it works, evals that gate releases

TCP

Transmission Control Protocol: the internet protocol that delivers data reliably and in order, resending anything lost along the way.

Used in: Learning Cloud through GCP — Part 5: How do I connect to my cloud ?

telemetry

Data a running system sends out about itself, such as traces, logs and metrics, so people can see what it did.

Used in: Part 1.25: The complete architecture, one picture for the whole series, Part 17: Designing an agent system from scratch: a framework and five real-world scenarios

temperature

A setting that sharpens or flattens a model's probabilities over possible next tokens; a higher value spreads probability more evenly across options.

Used in: Research papers, myth by myth, Part 4: 'Hallucinations are random glitches'

thinking tokens

Tokens a reasoning model spends working through a problem before it answers; they are billed as output although the user never sees them.

Used in: Part 15: What breaks in production: answers, loops, cost and model changes, Research papers, myth by myth, Part 5: 'A model's chain of thought shows how it really reached the answer'

three-legged OAuth

An OAuth flow with three parties, the user, the app and the provider, in which the user signs in and approves what the app may do.

Used in: Part 12: Giving it to users, Part 12.9: Long-running agents: work that carries on after the tab closes

time travel

A Delta Lake feature that lets you query or restore an earlier version of a table, using its transaction log.

Used in: Part 5: Storage, Cloud Storage and how Unity Catalog uses it

TLS certificate

A digital certificate that proves a server's identity and lets clients set up an encrypted HTTPS connection to it.

Used in: Plugins vs agents: what changed in August 2026

Token (credential)

A short-lived digital credential a program presents with each request to prove who it is and what it may access, like a temporary pass.

Used in: Forward deployed engineering, Part 8: Debugging in the field, Part 8: Memory, what an agent should remember, Prerequisite 0: Before you build: what to have ready

topologies

The shapes in which agents are wired together, such as one after another, in a loop, or side by side.

Used in: Part 2.5: Inside ToolContext, the object every tool receives

TPUs

Tensor Processing Units: Google's custom chips designed to train and run machine learning models quickly.

Used in: Part 13: Choosing and running models for agents, Research papers, myth by myth, Part 1: 'An AI reads one word at a time, like we do'

Trace

A record of every step one request went through, such as each model call and tool call, with timings, used to see where time and errors went.

Used in: Forward deployed engineering, Part 7: Prototype in days, production in weeks, Part 5: The router, let code choose the path, Prerequisite 5: Compliance for AI systems: what an architect needs to know

tracing

Recording each step of a request, such as model calls and tool calls, with timings, so you can see what happened and where it slowed or failed.

Used in: Forward deployed engineering, Part 1: What a forward deployed engineer actually does

trajectories

The ordered sequence of steps an agent took to reach an answer, such as which tools it called, with which arguments.

Used in: Part 1.5: The harness, the loop and the context

transit hub

A central network that other networks connect to, so traffic between them passes through one managed place.

Used in: Part 3: Networking: VPC, Cloud NAT, Private Google Access and Private Service Connect

Trino

An open source distributed SQL engine that queries data where it sits, across many sources, without loading it first.

Used in: Prerequisite 1: What a lakehouse is: storage, table formats and Spark

trust store

The list of certificate authorities a device or program trusts; a certificate signed by anyone else makes the connection fail or shows a warning.

Used in: Part 12: Giving it to users

try/catch

A programming construct that runs some code and, if it throws an error, jumps to a recovery block instead of crashing.

Used in: Meal Tracker: log a meal by taking a photo

tuple

A fixed, ordered group of values in Python, written in round brackets, such as (a, b).

Used in: Part 5: The router, let code choose the path

U

UDP

User Datagram Protocol: a lightweight internet protocol that sends data without checking delivery, used where speed matters more than completeness, such as video calls and DNS lookups.

Used in: Learning Cloud through GCP — Part 5: How do I connect to my cloud ?

Unix time

A count of seconds since midnight UTC on 1 January 1970, the usual way computers store timestamps.

Used in: Prerequisite 3: Identity and security foundations

UTCP

Universal Tool Calling Protocol: an open specification for describing how to call an existing tool or API directly, without a wrapper server in between.

Official docsUsed in: Part 13.5: What does an agent cost to own? Pricing across the architecture choices, Part 6: Agents talking to agents

UUID

Universally unique identifier: a long random ID, such as one stored in a browser, that can single out one device across visits.

Used in: How I built this website for free: system design, Astro, Firebase, OIDC federation and browser-native reader tools

V

vanishing gradient problem

When training a deep or recurrent network, the corrections reaching early layers shrink towards zero, so those layers barely learn.

Used in: Prerequisite 2.5: Traditional AI and generative AI: from regression and trees to neural networks

variance

How much a set of numbers spreads out; explaining 65% of it means the rebuilt numbers capture 65% of how the real numbers vary from token to token.

Used in: Research papers, myth by myth, Part 3: 'Nobody can see inside a model'

vCPU (virtual CPU)

Virtual CPU: one share of a physical processor, on Compute Engine usually one hardware thread, that clouds use to size, bill and set quota for machines.

Used in: Part 1: Foundations, how Databricks is built on Google Cloud, Part 13.5: What does an agent cost to own? Pricing across the architecture choices

vector

An ordered list of numbers, such as an embedding, that can be treated as a point in space so distances can be compared.

Used in: Prerequisite 3: How a model works: tokens, context, settings and what we never ask it to do

vector databases

Databases that store embeddings, lists of numbers representing meaning, and find the items closest in meaning to a query.

Used in: Forward deployed engineering, Part 1: What a forward deployed engineer actually does

version control

A system such as Git that records every change to files, who made it and when, so any earlier version can be restored.

Used in: Part 4: Skills, teaching an agent how

versioned

Given a version label, such as v1 or v2, so old and new definitions can be told apart and changed deliberately.

Used in: Prerequisite 2: The business terms and the data behind the agents

Vertex AI

Google Cloud's machine learning and generative AI platform for building, tuning and serving models such as Gemini; its services now form part of Gemini Enterprise Agent Platform.

Official docsUsed in: Part 1: What an agent really is, and the system we will build, Part 1.25: The complete architecture, one picture for the whole series

view

A saved query that looks like a table: reading it runs the query over the underlying tables, without storing a separate copy.

Used in: Prerequisite 2: The business terms and the data behind the agents

virtual environment

An isolated folder of Python packages for one project, so its library versions do not clash with other projects on the same machine.

Used in: Forward deployed engineering, Part 6: Agent frameworks compared

vLLM

A popular open-source server for running large language models efficiently on GPUs, TPUs and other accelerators, with an OpenAI-compatible API.

Used in: Part 13: Choosing and running models for agents

VM (virtual machine)

Virtual machine: a software computer, with its own operating system, CPU, memory and disk, that runs on a share of a physical server.

Used in: Learning Cloud through GCP — Part 4: Where do I store my data on Cloud ?, Learning Cloud through GCP — Part 5: How do I connect to my cloud ?

VPC network

Virtual Private Cloud: a private, isolated network inside Google Cloud; one VPC network is global, spanning every region, with each subnet in a single region.

Official docsUsed in: Connectors, MCP and plugins explained: who builds the link, where the data lives, and can a custom MCP server stay private?, from the basics, Part 13: Choosing and running models for agents

VPN

Virtual private network: an encrypted tunnel over the public internet that links a laptop or an office to a private network as if it were directly connected.

Used in: Learning Cloud through GCP — Part 1: What is Cloud ?, Part 6.5: Multi-agent topologies beyond a router, Starting a writing habit, in public

VS Code

Visual Studio Code: Microsoft's free, widely used code editor, which hosts AI coding assistants such as GitHub Copilot.

Used in: Plugins vs agents: what changed in August 2026

W

watermark

In stream processing, a moving time threshold that sets how late an event may arrive and still be handled, so older state can be dropped.

Used in: Part 8: Better together, BigQuery, Gemini and Google Cloud services

watermarking

Hiding a signal inside generated content, such as a pattern in an image's pixels, that software can later detect to show the content was AI-generated.

Used in: Your chatbot now has to say it's a chatbot

webhook

A web address that one system calls automatically to tell another that something has happened, such as a new order, so it can act on it.

Used in: How I built this website for free: system design, Astro, Firebase, OIDC federation and browser-native reader tools, Long-running agents explained: what changes when an agent keeps working after you close the tab

WebSockets

A web protocol that keeps a two-way connection open, so the browser and server can both send messages at any time.

Used in: Part 12.75: How agents show more than text: A2UI, AG-UI and MCP Apps, Part 17: Designing an agent system from scratch: a framework and five real-world scenarios

worker nodes

The machines in a Kubernetes cluster that actually run your containers, under instructions from the control plane.

Used in: Learning Cloud through GCP — Part 3: Where do I compute on cloud ?

Workforce Identity Pool

A Google Cloud group of staff identities that sign in through an outside identity provider, such as Microsoft Entra ID or Okta, instead of Google accounts.

Official docsUsed in: Part 12: Giving it to users

X

XML

Based on XML, a text format that marks up data with nested, named tags, widely used in documents and older web standards.

Used in: Prerequisite 3: Identity and security foundations

Y

YAML

A plain text format for configuration files that uses indentation to show structure, readable by people and programs.

Used in: Part 9: Commercials, quotas and operations

Z

Zero Data Retention

An OpenAI arrangement, for approved customers, under which API inputs and outputs are not stored after the request is processed.

Used in: Part 1.75: Agent frameworks, and where ADK fits

zero-shot

Using a pretrained model on a new task or dataset with no extra training on it.

Used in: Prerequisite 2.5: Traditional AI and generative AI: from regression and trees to neural networks

zones

Separate data centre locations within one cloud region, each with independent power and networking, so a failure in one does not take down the others.

Used in: Learning Cloud through GCP — Part 4: Where do I store my data on Cloud ?