Agents on the job.Every day, for real.
How we answer GDPR data-subject requests before the deadline
Our Machine agent checks each GDPR access or deletion request, finds the person's data across our product database, builds the report well within the SLA and hands it to legal before anything is sent.
How we keep our docs matching what the code does
Once a day a Machine agent reads every commit merged since its last pass, finds the doc pages those changes made wrong, rewrites them and sends you one pull request to review.
How we test every pull request without lifting a finger
Our Machine QA agent works with GitHub and our test environment. For each pull request it checks out the branch, runs the tests, tries the change for real, and posts what it found.
How we run day-to-day operations from a Slack thread
One agent you can call from Slack, with narrow access to our database, Stripe, Linear and GitHub. Describe the job in a thread and it carries it out across every tool involved.
How we turn NDAs around in minutes instead of days
Every 15 minutes our Machine agent picks up new NDAs, marks up anything that strays from our standard positions, and drafts a note for counsel. It never signs and never sends. Counsel does both.
How we run customer support with an AI agent
Our support agent on Machine plugs into Plain, our code and Stripe. It sorts and answers incoming threads on its own, and pauses for a person whenever something sensitive comes up.
How we answer HR policy questions on autopilot
Every 15 minutes our Machine agent reads the HR inbox, answers only from our Notion policy library as a Gmail draft for HR to send, and passes anything sensitive to HR in Slack.
How we help new customers reach activation
A daily agent on Machine checks every new account's onboarding progress in Postgres, writes a nudge email when one gets stuck, and gives the account's CSM the full story in Slack.
How we write the first draft of every incident postmortem
Once an incident is resolved, a Machine agent reads the incident channel, lines the timeline up with deploys and log spikes, and opens a postmortem draft as a doc PR for the team to review and edit.
How we keep interview loops on schedule
Each day our Machine agent picks up candidates who are ready to book in Greenhouse, checks the panel's Google Calendars, and drafts the time proposal and invites for a coordinator to approve.
How we write first drafts of RFP responses
Our RFP agent picks up each new request, breaks it into questions, answers them in a fresh Google Doc from our vetted library and product docs, and marks anything uncertain for a person to handle.
How we do first-pass contract review
Drop a contract into a Drive folder and an agent reads it, flags any clause that breaks our playbook, posts a summary for legal and drafts redlines a lawyer must approve.
How we get new vendors through onboarding
Every day an agent checks new vendor requests in Gmail for a W-9, a banking form and a signed contract, logs each vendor in a Google Sheets register and flags gaps in Slack. It never approves or sets up payment.
How we keep watch over our ad performance
Our ads agent reads Google Ads and Meta Ads each day, spots pacing problems, CPA and ROAS drift and weak ads or keywords, and posts ranked fixes to Slack. It never edits budgets, campaigns or ads.
How we find candidates for our open roles
Each day our sourcing agent on Machine searches LinkedIn for people who fit an open role, skips anyone already in Greenhouse, and writes a tailored email that the recruiter reviews and sends.
How we sort through reported phishing emails
Every 15 minutes, a Machine agent opens newly reported emails, checks headers, links and attachments for warning signs, and posts a verdict with a suggested action to Slack. A person makes the final call.
How we process vendor invoices the moment they arrive
Every 15 minutes our payables agent pulls new invoices from Gmail, reads them, checks them against POs and the ledger in Google Sheets, and sends them to Slack for approval. It never pays anything.
How we catch compliance drift
Each day an agent checks our cloud setup against policy, flags public buckets, missing tags and roles with too much access, and suggests every fix as a change a person approves.
How we handle offboarding when someone leaves
A Machine agent checks Okta for new leavers, cuts their access in Okta, Google Workspace, Drive and GitHub and frees their licenses. Ownership transfers wait for approval; accounts are never deleted.
How we run the month-end close
Each month our Machine finance agent works the close checklist, ties Stripe revenue to the Google Sheets ledger, flags odd numbers and missing docs, and posts open items to Slack. A person closes the books.
How we stay one step ahead of contract renewals
Every day, a Machine agent finds accounts 90, 60 and 30 days from renewal, builds a packet on usage and value, drafts the outreach, and flags any at risk so the account owner can review.
How we turn NPS responses into clear themes
Once a week our Machine agent reads new NPS and CSAT answers from a Google Sheet, sorts the comments into themes with sentiment and detractor drivers, and posts the score trend and real quotes to Slack.
How we put together first-draft QBR decks for key accounts
Each week, a Machine agent reads Postgres and HubSpot for every account with a QBR coming up and builds a draft Google Slides deck plus a Google Docs briefing for the CSM to edit and present.
How we build our roadmap from what users tell us
On a set schedule an agent collects feedback from support, public reviews and a Slack channel, sorts it into themes with real quotes and counts, and keeps a single Linear issue current for each theme.
How we get the weekly metrics report written for us
Our reporting agent is hooked up to our Postgres database and Slack. Each Monday it pulls the numbers, writes the weekly report with notes on what changed, and posts it to the team channel.
How we figure out why we win and lose deals
Once a week our win-loss agent reads every HubSpot deal closed won or lost since its last run, then posts the patterns to Slack by segment, competitor, price and the stage where deals died.
How we keep an eye on competitors
Every day an agent reads competitor websites, changelogs and pricing pages, compares them with yesterday's copy, and drops a short note in Slack about anything that moved.
How we win back subscription payments that fail
Every hour, an agent walks each failed Stripe invoice up a four-step ladder of retry and reminders, keeps the revenue team posted in Slack, and goes quiet the second the customer pays.
How we keep track of who's talking about our brand
Each day an agent scans news, social sites and forums for fresh mentions of our brand, sorts them by sentiment, and posts the important or negative ones to Slack with a draft reply for a person to review.
How we run truly personal outbound
Our agent on Machine works with the CRM, enrichment and email. It researches every lead, writes a sequence that is actually personal, logs it to the CRM, and waits for a person to approve sends under a daily cap.
How we stop deals from going quiet
A daily Machine agent combs HubSpot for deals gone silent, blank next steps, stuck stages and late tasks, pings the rep who owns each one in Slack, and sends the worst cases up to their manager.
How we write release notes straight from merged PRs
Our Machine release-notes agent works from GitHub. Each time we ship, it reads what merged since the previous release, sorts it by area, writes the notes and opens a changelog PR.
How we turn the pipeline into a forecast every week
Each week our agent reads HubSpot's open deals, weights them into a forecast against quota by stage, rep and segment, names the deals slipping out of the quarter, and posts it to Slack. It only reads.
How we monitor our data pipelines and warehouse health
Every hour an agent on Machine checks how fresh our warehouse tables are, whether row counts look normal and whether schemas shifted, then alerts Slack and drafts a GitHub issue. It never changes data.
How we spot accounts that might churn
Each day an agent scores every account on early churn warnings from product usage, support and billing, then posts a ranked list to Slack with the reason and a suggested next step for each.
How we turn our content calendar into social post drafts
Each day our agent checks the Notion content calendar, writes posts suited to each platform for what is coming up, and parks them in Slack with their dates until a person approves and publishes.
How we keep our content from going stale
Once a week an agent on Machine spots blog and marketing pages that are slipping in Search Console, freshens their copy, numbers and internal links, and opens a pull request for review.
How we get each inbound lead to the right rep
Every 15 minutes, our Machine agent scores fresh HubSpot leads, gives each one an owner by territory, segment or round-robin, pings that rep in Slack, and passes anything unclear to a person.
How we close the books on expenses each month
Once a month a Machine agent checks Stripe and the bank feed against our invoices, records the result in Google Sheets and posts a summary. Anything it cannot match goes to a person.
How we catch wasted SaaS spend
Once a week our agent lines up card and bank charges with our subscription register and points out duplicate tools, idle seats, price rises and shadow IT. It suggests fixes and never cancels anything.
How we get security questionnaires drafted fast
Our agent breaks each incoming security questionnaire into questions, answers them in the vendor's own format from our vetted knowledge base, and marks anything uncertain for a person.
How we write help articles from tickets we've already solved
Once a week an agent groups our resolved Plain tickets, spots the questions that keep coming back with no help article, drafts the biggest gaps from the real fixes, and opens one PR for a person to review.
How we handle access requests
Someone asks for access in Slack and an agent checks the policy, looks up their role and drafts the smallest grant that fits. A person approves every grant, and each one is logged.
How we catch cloud cost spikes long before the bill arrives
Our cost agent reads AWS Cost Explorer each day, learns normal spend for every service and account, flags anything that breaks pattern with its likely cause, and alerts Slack. It never touches a resource or budget.
How we turn each meeting into notes and action items
Our meeting agent on Machine works from Google Calendar, the call transcript and Linear. When a call wraps, it writes tidy notes and files each action item as a Linear ticket for the person who owns it.
How we keep our production error backlog tidy
Every hour a Machine agent sorts new and spiking Sentry errors, checks GitHub for existing issues, drafts issues for the worst ones and posts to Slack. It never resolves, ignores or assigns.
How we get urgent support tickets to the right team
Every 15 minutes a Machine agent checks Plain for SLA breaches, VIP accounts and severe tickets, routes each one, links a Linear issue when engineers are needed and posts to Slack. It never closes tickets.
How we give every applicant a fair first read
Each new application wakes an agent that checks the resume against the role's written rubric, quotes its evidence, and suggests interview times for strong fits. A person decides every case.
How we get back to every inbound lead
An agent on Machine works with HubSpot, email and Google Calendar. It looks into each new lead, writes a personal follow-up with a suggested call time, and waits for a person to approve the send.
How we stop code review from getting stuck
A Machine agent spots pull requests that are overdue for review, have gone quiet, or still owe answers to requested changes, then pings the author or reviewer in Slack with what's holding them up.
How we get new hires set up
When HR adds a new hire, a Machine agent prepares their Google account, groups, Slack channels and a first-week checklist in Linear. Anything that grants access waits for a person to approve.
How we clear out old feature flags
Each week a Machine agent finds feature flags that are fully rolled out or long dead, deletes them along with the code they guard, and opens a PR. A person merges; live rollouts are left alone.
How we keep a shared inbox sorted with an AI agent
An agent on Machine reads our shared Gmail inbox with a help doc and Linear to hand. It labels each email, drafts a reply or files a task, and waits for a person before a customer sees anything.
How we write the first draft of our monthly investor update
Once a month an agent on Machine reads Postgres, Stripe and last month's update, gathers our key metrics, checks them against last month and plan, and drafts the update in our format for a founder.
How we triage on-call alerts before anyone gets paged
Our triage agent on Machine reads Sentry, our logs and GitHub. It puts together a first diagnosis for every alert, and only wakes a person when it can't settle the alert or the severity is high.
How we handle the follow-up after every sales call
The moment a call wraps, our agent writes the recap, updates the HubSpot deal and logs next steps in Linear. The recap email then waits for the rep to read and send it.
How we catch flaky tests and put them in quarantine
Our Machine agent reads GitHub CI history daily, ranks each test by how often it flips on unchanged code, then opens a quarantine PR and a tracking issue for a person to review.
How we keep our CRM clean
Each night an agent merges duplicate HubSpot contacts, fills in blank fields from enrichment data, flags deals that went cold and posts a tidy-up report. Big bulk edits wait for a person.
How we follow up on invoices that are past due
Our receivables agent on Machine works with Stripe, email and the accounting ledger. It spots late invoices, sends the right reminder, records each contact and reconciles payments as they arrive.
How we stop our dependencies falling behind
Once a week a Machine agent bumps our packages, installs them clean in a private sandbox and runs every test. You only get a pull request when the whole suite is green.
How we keep the office kitchen stocked
Anyone can ask for snacks with a Slack shortcut. Once a week an agent rounds up the requests, puts together an order, and posts it for the office manager to approve before a penny is spent.
How we run our standup as a Slack post
Each weekday an agent reads what everyone did in Linear and GitHub, nudges anyone whose day left no trace, and posts a short team standup to Slack. It never writes to either tool.
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