Changelog

We made the browser one of the tools every agent starts with, like running code or reading files. Until now, an agent had to load the browser guide before it could open a browser at all. Most runs did, but a scheduled workflow with a saved browser would sometimes skip that step, decide it had no browser, and stop without opening a page, even though the browser and its saved logins were fine. That failure is gone: a workflow that follows a script now goes straight to opening the browser.

Opening another member's private specialist used to retry for about seven seconds, then show a raw "not found" error. Detail pages now tell the difference between something you can't open and something that doesn't exist, and they say so right away.

Many automations hinge on a judgment call: which team should get this ticket, is this lead a good fit, does this email need a reply. The new decision service answers questions like these with a probability for every possible answer, so your workflow can act only when it's confident enough. Like every built-in service, it needs no API key of your own and bills to your workspace.

Meta released Muse Wonder on October 12, and it's in General Input the same day. You can also connect a Muse Code subscription through Token Tunnel, alongside Claude, ChatGPT, Gemini, and Grok, and run Muse models on the plan you already pay for. Read about Meta's earlier open-source Muse release.

The dashboard and the iPhone app held the same lists (specialists, Home, Activity, conversations, resource cards, pins, badges) in about a dozen separate caches, and every send, stop, read, and live event had to remember to update each one. When one was missed, a specialist looked idle while it worked, or a finished run still looked busy. Both apps now draw every list from one sync engine per workspace, kept in step by a server change feed.

Workflows and apps can now turn recordings into text with a built-in transcription service: meeting recordings, voicemails, interviews, podcast episodes, or any audio or video file. Like every built-in service, it needs no account of your own and bills to your workspace.

When the Agent Firewall blocked a request, the agent used to be able to say only "ask the workspace owner," which left people guessing. Every firewall refusal now explains itself: which firewall stopped the action, where it can be allowed, and who is allowed to change it.

When someone published a new version of an app you had open, the dashboard unmounted it for every build, failed builds included, and the iPhone app could run old screens against new server code for up to a minute. Viewers refreshing at once could also restart the app's server in parallel and disrupt each other. We rebuilt the session model under apps.

When a conversation outgrows its model's context, a summarizer writes a checkpoint and the conversation continues from there. In production, the default utility model could spend its whole output budget on hidden reasoning and stop before the summary was complete. Compaction then failed the run, and every later message in that conversation failed the same way. Compaction now always lands a checkpoint, and never writes a partial one.

Sign-in cards and AI connection sign-ins hand you a live browser so you can log in to a site yourself. On a phone, text sent into that page was typed key by key, which was slow and failed past 1,024 characters. The phone is now a trackpad over a zoomable page, and every live browser, on any screen, is framed in the same browser controls.

Anthropic released Claude Haiku 5.5 on October 7, and it reached General Input on October 8. It replaces Haiku 4.5 everywhere, and it's the first Haiku to be a default agent model rather than opt-in, so specialists can run on it. It appears in the model picker, the hosted API catalog, and the Subscription group when you connect a Claude plan through Token Tunnel. See the models page.

Every conversation gives its specialist a persistent work folder in its sandbox. Until now, a cold sandbox fetched that folder's contents before the agent could act, so the bigger the workspace, the longer the wait. As of October 8, the work folder is a real filesystem, built on open-source JuiceFS, that restores only names and metadata when the sandbox starts and fetches each file's data the first time something reads it.

Starting a conversation used to mean choosing a specialist first. Now you start with the work. New task, in the sidebar, the Home menu, and the specialist list, opens the full chat composer. When you send, General Input ranks the specialists you can access and asks where the task should go: pick the recommended specialist, another one, or a new specialist that's created, named, and described from your message and starts on the task right away. The same flow ships on iPhone.

You shouldn't have to repeat yourself to every specialist. Since October 8, a specialist can check what you've been discussing elsewhere: if you worked out a plan with your Chief of Staff on Monday, the specialist that carries it out on Tuesday can read that conversation instead of asking you again.

Workspace owners ask Analytics two questions: what are we spending credits on, and who is spending them? The old page spread the answers across four tabs. We rebuilt it as a single spend view measured in credits, with runtime and run counts beside spend, since spend alone doesn't measure productivity. An Overview and a Logs tab replace the old Members, Executions, Security, and Usage tabs.

The iPhone app now opens on what it already has. Chat lists and recent conversations live on the device, a notification fetches its conversation as it arrives, and coming back reads only the messages you missed. Tapping a reply notification opens on the reply, even in airplane mode.

Connecting an integration from the dashboard, or from a connect card in chat, now reports what actually happened. The server records how every connect attempt ended, and the dashboard waits for that answer instead of inferring it from the sign-in popup.

Every new workspace now starts with 4,800 credits, worth $30, instead of 800 credits ($5). That's exactly one Pro seat's monthly allowance, so it amounts to a free first month of one Pro seat: enough to connect your tools, build your first specialists, and run real workflows before paying anything. See what a seat includes on the pricing page.

We reworked how the browser agent acts on pages and how long browsing runs hold their context, and we built a harness that scores browser changes on a public benchmark. The changes target three failure modes: forms left half-filled, observations that go stale after navigation, and long runs that lose their prompt cache.

Sending a message, starting a conversation, stopping a run, and reading a reply now update the sidebar, conversation lists, and Home immediately on the dashboard and in the iPhone app, instead of waiting for a round trip to the server. On mobile, a message you send keeps trying for up to a day, through dead zones, backgrounding, and relaunches, and a retry never creates a second copy.

A hosted Token Tunnel account (a Claude, ChatGPT, Gemini, or Grok subscription you signed in to through General Input) used to serve only its owner. You can now share each account with specific workspaces. Every active member of a workspace you add can use that subscription in chats and workflows, on the same plan limits, and you can remove a workspace at any time.

Every conversation with a specialist has a workspace: the files it keeps between turns. We used to save that folder as a single archive, so every cold start downloaded, unpacked, and later re-uploaded the whole thing. That scaled badly: one design conversation with 175 files and 260 MB of images saw its sandbox start climb from 2 to 15 seconds to more than 200 before it failed outright. Workspaces are now stored the way Git stores a repository, as content-addressed objects plus a manifest, synced incrementally.

Image-heavy conversations could go wrong four separate ways. Pasted phone photos could replace or corrupt each other, a large folder hit a fixed attachment cap, a request with many big images was rejected outright, and a request over a size limit ended the run. Between September 26 and 30 we fixed each one where it happened.

You can now sign up, sign in, and accept invitations to a workspace with your Apple ID, alongside Google. Existing members can link Apple to their account, or unlink it, from account settings. The iPhone app uses the same browser sign-in and device approval it already had.

General Input is on iPhone. The native app, open to everyone through a public TestFlight beta linked from the mobile page, puts your specialists in your pocket: chat with them, answer their questions, approve paused runs, and check on your workflows from anywhere.

General Input now runs on specialists. A specialist is an AI worker that owns one job in your business, such as weekly reporting or lead follow-up. You describe the outcome in your own words, it asks what it needs to know, and it builds and runs the skills, workflows, and apps the job takes. Projects became specialists and kept everything they held. Read why we made the change.

You can now delete your own General Input account, from the dashboard or the iPhone app, without contacting support. Before anything is removed, you see every workspace you belong to and everything you own in each one, and you decide what happens to it.

The Business plan used to require at least five seats, so a team of two paid for five. That minimum is gone. Choose a seat count starting from one, and each seat adds its credits to the workspace's monthly allowance plus a spot for one member. See plans on the pricing page.

With specialists, the geni CLI and the MCP server picked up a long list of operations that used to need the dashboard. Agents inside General Input got the same operations as tools, so an outside coding agent, the CLI, and a specialist all work through one set of actions. The developer docs were audited against the deployed tools and every /v1 route in the same release. See the developer page.

Notices used to sit behind a bell, apart from the conversations and runs they were about. They're now rows in the Home inbox: unread ones appear in Unread on the dashboard and in Activity on the iPhone app, next to conversations and paused runs, and every notice is kept in History. Alongside the move, the iPhone app gained push notifications, and workflows learned to tell you when a live run fails or stops to ask you something.

Signing an agent into a website used to run through a guided flow where an agent checked and steered each sign-in. It was slow and brittle, so we replaced it with something plainer. On the Browser page (in beta), your saved browser is a computer with a power button: switch it on, browse and sign in to anything the way you would on your own machine, and switch it off. Agents, workflows, the CLI, and the MCP server reuse whatever you signed in to.

We audited what would break if usage grew tenfold, sized each fix from measured numbers, and lifted three limits that were already slowing busy workspaces down. The result is steadier performance at the moments workspaces are busiest, like the top of the hour when many schedules fire at once.

When a query against your PostgreSQL, MySQL, or SQL Server database failed, agents used to get a generic "Database query failed" with no detail. That hid real SQL mistakes, like a misspelled column or a missing join, from the agents that could have fixed them. Now the agent sees the database's own message and corrects the query itself.

Running agents on your own AI subscription used to mean keeping General Input Desktop open on a computer that stayed online. The hosted Token Tunnel runs that connection in our cloud instead. In Settings, under AI connections, sign in to Claude, ChatGPT, Gemini, or Grok once, and those models appear in the model picker in every workspace where you're an active member. New members can connect a subscription during onboarding, and the iPhone app has the same page.

We moved the catalog to the newest generation of each frontier model family, and saved selections followed on their own: a workflow, app, or specialist that names a retired model now runs on its successor, so nothing had to be re-saved. Subscription models through Token Tunnel follow the same upgrades. Compare everything on the models page.

When a run used a model served from your own computer through Token Tunnel and that computer slept or lost its network, the run could wait 90 seconds to 4 minutes before failing. Fallback then tried every other model on the same unreachable machine before reaching a cloud model. In a typical week, about 96% of device disconnects were only caught by a server ping, mostly computers that fell asleep with the tunnel still marked connected.

GPT-6 Astra and Claude Fable 5.1 are now hosted models: any workspace can run them on General Input's provider keys without connecting a subscription. Until now both were reachable only through Token Tunnel. Compare them on the models page.

Every resource in a workspace can now change hands, and deactivating a member can no longer strand what they built. An owner can give a workflow, app, skill, project, credential, database, store, or browser to any active member. When someone leaves, an admin moves everything they own to a successor, or deletes it, in the same step as the deactivation.

Three gaps at the edges of a run are closed. A run that exists in the database is always handed to a worker, a redelivered schedule or webhook can no longer execute twice, and stopping a run no longer throws away the text the agent was in the middle of writing.

Agents produce and read a lot of files: reports, spreadsheets, screenshots, recordings. Opening one now fills the screen with the file itself, on a black backdrop with just a close button and a download button, on the dashboard and in the iPhone app alike.

A security review of the request surface, and of how runs reach credentials, shipped as a set of protections. None of them change how a workflow is written; they narrow what a request or a run can reach.

The dashboard is rebuilt around what you come back to. The new Home became the dashboard for every workspace in early September: one feed of your work, your pins in the sidebar, and every workflow, app, and skill in a single Resources grid, so you no longer need to remember which list page something is on. (Projects here are what we now call specialists.)

Two chats editing the same workflow could silently revert each other: a conversation holding a draft from days earlier could publish it and wipe out changes another chat had made since. Every publish from an agent, the geni CLI, or an MCP client is now conditional on the version its working copy was taken from. A stale copy is refused with instructions to re-read and merge, never applied.

Model routing now lives in one engine, and a model can be served by more than one route. Every chat model in the catalog has its native provider plus routes through Vercel AI Gateway and OpenRouter. When a provider is overloaded, a run first moves the same model to its next untried route, and only then falls back to a different model, so a provider incident doesn't have to change which model is doing your work.

The public /v1 API now has two kinds of key with separate, explicit scopes, and every route checks exactly one. A personal key acts as you and manages your workflows, skills, memory, projects, and triggers. A platform API key, now available to every workspace, acts for the workspace: it can search the integration catalog, hand out credential tokens, and call hosted services, but can never start a run or touch members' resources. That split lets you give an outside agent, such as Claude Code, Codex, or your own, exactly the access it needs. See the developer page.

Any code or agent workflow can now carry an optional filter.ts: a cheap, deterministic check that decides whether a run happens at all, and on what input. A busy webhook or poll trigger no longer wakes an agent for every event. A code check costs roughly a tenth of a cent; an agent run costs 40 to 250 times that before it does any work, so on a noisy trigger the filter decides most of the bill.

Agents call your integrations from our documentation of each API, so a wrong field name or a retired endpoint becomes a failed run. We now check that documentation against the live APIs. Each service gets a test suite whose probes encode what our docs claim, and a daily run replays them. The finding we care about is a faithful probe failing because the API disagrees with the docs.

Workspaces can now define their own team roles, such as Sales Rep, Recruiter, or Finance, and give each member one or more of them. Apps use those roles to decide what each person sees and can do, so one app can serve a whole team with the right view for each person.

Projects shipped to every workspace. Projects, which have since become specialists, give a goal that takes several pieces one home: a skill holding the procedure, a workflow running it on a schedule, an app where someone reads the output, and the reference files behind all three. Start a chat inside a project and everything it builds lands there. Read the Projects announcement.

The knowledge base is now Memory, one name across the product: a Memory page in the dashboard, and workspace and personal memory available to every agent. The bigger change is that it no longer depends on someone typing facts into it. A memory agent runs daily for each memory, reads what happened since its last run, and revises it: confirming what still holds, changing what changed, adding what's new, and removing what's now wrong.

Workflows, apps, and templates declare the integrations they need as credential slots. Databases and browsers now go through the same slots: the picker lists your databases and browsers beside your integration credentials, and publishing refuses a slot nobody filled. The result is that a workflow states up front every resource it touches, and the platform holds it to that list.

Auto picks the model for each request. It now considers the models you've connected through Token Tunnel and prefers them: when a suitable one is online, Auto runs there, on the subscription you already pay for, instead of on a hosted model billed in credits. A Default to local models switch in the Auto menu controls it; it's on by default once you have a connected model.

Since August 19, every member gets a weekly digest of what happened in their workspace: how much work their workflows and agents did, and how they compare with the rest of the team. It arrives on Wednesdays, covers the previous Monday through Sunday, and comes once for each workspace you belong to.

For work that has no API (a supplier portal, an internal tool, a retailer's product page), agents can now open a real hosted browser. Every member has a browser that keeps per-site logins: sign in to a site once, and later runs open already signed in. When a run lands on a sign-in page, it pauses, you sign in through a live view in the chat, and the run picks up with the result. Agents never ask for a password and never type one.

Connect once from Settings, then MCP, and Claude, ChatGPT, Claude Code, Codex CLI, or any other MCP client can work in your General Input workspace. The connector isn't a read-only window or a short list of popular actions: it mounts the full toolset our own agent uses, so the model in your AI tool can call any operation across your connected integrations, build and edit workflows, apps, and skills, run them, and read their traces. Read the MCP announcement.

We replaced the flat self-serve plans with one per-seat Business plan in two tiers. Pro is $30 per seat per month and funds 4,800 credits per seat. Max is $100 per seat per month and funds 16,000 credits per seat. Both started at 5 seats and go up to 50; larger teams go through Enterprise. The free tier is unchanged. See the pricing page for current plans.

Apps can now declare background agents that someone using the app launches from a button: a Research button on each row of a lead table, a Draft reply button on each support ticket. An app agent is not a reduced version of a workflow agent. It follows the same agent workflow spec, runs in its own sandbox, and gets the same run history, streaming, approval steps, and billing. Ask for one in the chat panel next to your app, the same way you'd ask for a new chart. Read the launch post.

You no longer have to wait for an agent to finish before you correct it. Send a message while a run is in flight and it shows up as a dimmed Queued bubble. At the agent's next step, the message is added to the conversation and the agent responds to it in the same run. Changed your mind? Undo on the bubble, or Escape in the composer, takes it back and returns the text and attachments to the composer. Queuing works in chat and while building workflows, apps, and skills.

New members now get a Getting Started checklist in the dashboard sidebar. It walks through six first steps: connect an integration, chat with the agent, install Token Tunnel, build a workflow, build an app, and build a skill. Each step opens a short explanation with a button that takes you straight to the right page.

Owners can now delete a workspace from Settings. Confirm by typing the workspace's name, and it becomes invisible and inert immediately: members lose access, and nothing in it runs again. Its data is then removed permanently, not just hidden.

The new Analytics page shows who in a workspace is using AI and for what. It replaces the separate executions, usage, and security audit pages with one view, and adds a Members section that ranks every active member by what they built and ran.

Two hosted models landed at the end of July. Compare them on the models page.

July reworked how apps run and how people move through them. Actions respond faster because they hit a server that's already up, app code can behave differently for different members, and any page inside an app can be linked to directly. See how apps fit into agents inside your apps.

Token Tunnel is available to every workspace. Install General Input Desktop, sign in to the AI subscriptions you already have (Claude, ChatGPT, Gemini, or Grok), and those models appear in General Input as your own. Chats and agent workflows run on them without an API key, usage isn't billed per token, and your provider logins live only on your computer. Learn more about running local and personal models.

Long agent runs used to look broken at exactly the wrong moments: a laptop waking from sleep, a train going through a tunnel, a flaky office network. The chat stream is rebuilt so reconnecting is clean. Your run keeps working on our servers the whole time, and the chat catches up exactly where it left off.

Most requests don't need the most expensive model, and some need nothing less. Auto now makes that call per run. It sits at the top of the model picker with three tiers (Fast, Balanced, and Max), and new members start on Auto everywhere. Members who already chose a default keep it.

Our integration count went from 275+ at the start of July to 500+ on July 17. Each integration ships with operation-level API documentation agents search, a setup guide, a credential check on connect, and poll triggers wherever the service has a real new-items stream. Browse the full integrations catalog.

You can now move a workflow, app, or skill between workspaces as a file. Export downloads the resource's live bundle as a .zip; import validates it, shows a preview, and creates the resource. Credentials never travel in the file, so an imported workflow arrives ready for you to connect your own accounts.

An agent run can take many minutes, and occasionally one of our servers restarts in the middle of it, for example during a deploy. Until July 15, the resumed run could repeat a step it had already taken. Now every tool call with side effects is recorded in a journal before it runs and again when it finishes, so a resumed run picks up exactly where it left off.

Describing a workflow out loud is faster than typing it, but raw transcripts are full of false starts. Every prompt box in the dashboard now has a mic button: words appear as you speak, and when you stop, a cleanup pass turns the ramble into the prompt you meant and puts it in the box. It never submits for you. Read why talking to agents is faster than typing.

Workflows and apps do work; skills teach agents how to do it. A skill is a SKILL.md instruction bundle in the open Agent Skills format: your email conventions, a report layout, a triage procedure, plus any scripts and templates that go with it. Skills now sit beside workflows and apps with their own page, every agent in the workspace can load them, and because the format is portable, a skill written here works in other Agent Skills hosts and the reverse. See why we favor small agents over mega-skills.

Agent runs resend the same long prefix on every step: instructions, tool definitions, and the conversation so far. Most of it comes back from the provider's prompt cache at a fraction of the input price. Every model in the catalog now carries four rates (input, output, cache read, cache write), and each call is priced on what the provider actually served.

On June 30 we moved our managed Claude models to Anthropic's own API and upgraded them in the same step. Claude Sonnet 4.6 became Claude Sonnet 5, Claude Opus 4.6 became Claude Opus 4.8, and Haiku 4.5 stayed as it was. Sonnet 5 is now the default model for chat and for building workflows and apps, and the agents in our built-in templates use it too. See all models on the models page.

OAuth scopes and API keys are coarse. Connecting Google Sheets grants edit and delete on every spreadsheet, and an agent holding that credential inherits all of it. Agent Firewall moves the unit of control down to the operation: on any connection you can block whole categories (every write, every read) or individual operations, and admins can set standing rules across the workspace. Agents keep the access their job needs and lose the actions you never want them to take. Read why scopes are the wrong unit of control.

Notifications used to go out by email only. A workspace admin can now connect Slack, and each member chooses, per notification type, whether it arrives by email, as a Slack DM from the workspace's bot, or both. That covers auto-disabled workflows, failed triggers, low balance, balance refills, revoked credentials, and workflows, credentials, or databases shared with you.

Apps used to build on our API servers. An agent edit could trigger duplicate builds, concurrent builds were silently dropped, publishing cleared the running app until the next good build, and a crashed build could leave an app stuck on "building." We rebuilt the pipeline in two steps.

Over June we loosened what a workflow needs before it can run. It can take files as input, its settings can be optional, and so can its connections, so one workflow can serve people with different tool stacks and a missing nice-to-have no longer blocks a run.

The geni CLI can now author code workflows, agent workflows, and apps end to end. Local files are the draft: your coding agent edits them with its own tools, geni resource validate checks them without saving, geni resource publish makes them live, and geni workflow test runs the published version in the cloud. It's the same build loop the in-product agent follows, backed by the same server-side checks. See the developer page.

We ran four agents: one for chat, one that built workflows, one that built apps, and one for database questions. Each had its own prompt, tools, and run lifecycle, so a fix to one often missed the others. They're now a single agent, and what changes between surfaces is the subject it's pinned to (home, a workflow, or an app), which decides its instructions, preloaded skills, and tools.

As workspaces filled up, finding something meant remembering which page it lived on. Global search, added June 11, puts one search box in the dashboard header that looks across the whole workspace at once.

We rebuilt workspace and personal context into a memory system. Each workspace and each member now has a distilled summary of at most 200 words covering identity and working style: who you are, how you write, and the standing instructions you've given. Every agent run loads that summary, so agents know the essentials on every run without reading your whole knowledge base each time.

Until now, an API outside our catalog meant filing a request and waiting. You can now add it yourself: in Integrations, choose New, then Custom Integration, and describe the API or drop in its docs. An agent drafts a private integration for your workspace, and once published it works everywhere a built-in integration does. Agents call it in chat, and workflows and apps declare it as a connection.

Workflows run in the background, but some work needs a screen. Apps, available to every workspace since June 2, are single-purpose internal tools an agent builds for you: a dashboard over your CRM, a quick lookup across two systems, a one-click action your team runs every day. Describe what you need, and the app builder writes it, tests it against your real accounts, and publishes it to your workspace.

Long runs used to stop for reasons that had nothing to do with the work. Code workflows were capped at 5 minutes and chat and scheduled runs at 10, a deploy could stop a worker mid-run, and a sandbox provider having a bad hour meant failed runs. Over May we lined all of those up.

Choosing a model is two decisions: which model, and how hard it should think. The model picker now shows both, along with what each option costs, and five new models arrived during May. Compare them on the models page.

Until now, a new workspace waited on a waitlist or a sales conversation before it could run anything. Sign-up is now self-serve: pick a plan during onboarding and start building. Everyone still on the waitlist was approved when self-serve went live. Current plans are on the pricing page.

General Input is now CASA Tier 2 verified. CASA (Cloud Application Security Assessment) is the App Defense Alliance's review, and Google requires it before an app can use restricted scopes such as reading and modifying Gmail or full Google Drive access. To prepare, we ran the platform through the same dynamic and static scans the assessment uses and fixed what they found across the API, the dashboard, and our edge.

Two weeks after sharing launched, a workflow can be shared with Editor access. Editors can change instructions, triggers, credentials, settings, and agent configuration, and can ask the agent to make changes. Once more than one person can edit the same workflow, collisions become possible, so this release also makes concurrent editing safe.

An agent's files used to last only as long as one sandbox. Close the conversation, or follow up on a finished run, and its scratch files, downloaded data, and half-written scripts were gone. Now every conversation and every execution has a persistent work folder, and agents run code the way an engineer does: with bash.

More than 100 services gained connection support in May, taking the catalog past 240 integrations: data tools (Snowflake, Segment, Mixpanel, Amplitude), work apps (Pipedrive, ClickUp, Zoom, Xero), web data (Firecrawl, Tavily, Bright Data), voice (ElevenLabs, Deepgram), enrichment, and media monitoring. Over the same month, the trigger library grew from about 60 triggers on 20 services to 344 on 52, so more workflows can start from the event itself instead of a schedule that checks for it. Browse them in the integrations catalog.

geni is a command-line tool that gives an AI coding agent on your machine access to the integrations you've connected in General Input. Ask Claude Code to post in a Slack channel or pull last week's Stripe charges, and it finds the right credential, reads the operation's docs, and makes the call, without ever seeing the token. Install it from npm as @general-input/cli and see the developer page.

Until now, a workflow and every credential behind it belonged to the one member who built it. You can now share both the way you share a document: pick members or give the whole workspace access, then choose what they can do. The person who connected Salesforce can hand a workflow to the team, and the team runs it without their own admin login. Read the announcement.

Poll triggers check a service on a schedule and start a run for each new item. When polling broke, we used to disable the whole workflow after three consecutive failures, whatever the cause, so a provider outage could switch off an automation its other triggers were still feeding. As of April 30, a failing trigger pauses only itself.

Knowing what to automate first is often the hardest part. The prompt library, launched April 30, collects ready-made starting points by use case and by integration. Pick one and the builder starts from that prompt, so the first draft of a workflow is a click away instead of a blank page. The same library is public at generalinput.com/prompts.

Some steps shouldn't run unattended: sending a draft to a customer, choosing which leads to contact, filling in a detail only you know. Agent workflows can now stop and ask. The run parks with a Paused status, the question appears on your hub and on the execution's page, and once you answer, the agent picks up exactly where it stopped.

Agents now carry what they know about you from one conversation to the next. Context holds two sets of files: workspace context every member shares, and personal context only you can see. On April 25 we made filling it in the first thing a new workspace does.

Billing now shows credits instead of dollars. The rate is fixed at 160 credits per dollar, so $25 buys 4,000 credits, and refills come in packs of 1,000, 2,000, 4,000, and 10,000. Every execution and agent run shows its cost as a receipt. See current plans on the pricing page.

Ask an agent for a deliverable and you used to get Markdown or a hand-built HTML file. Agents now have skills: packaged instructions plus the tools to produce a specific kind of output, shared across chat, the workflow builder, and agent workflow runs.

Connecting tools was the slowest step before a first workflow could run. Dozens of providers now connect in one click: pick the service, approve the provider's own consent screen, and you're done, with no app to register and no token to paste. That covers the Microsoft suite (Outlook, Teams, OneDrive, SharePoint, Excel), the Google suite (Gmail, Drive, Calendar, Sheets, Docs), HubSpot, Salesforce, Airtable, Box, Dropbox, GitHub, Linear, QuickBooks, Shopify, and Stripe. Read the release post.

Workspaces now decide which AI models their agents use. A new Models page in settings lists every managed model by provider and lets admins turn each one on or off. Teams that already run an approved model in their own cloud can add it as a custom model, which is the bring-your-own-model path for regulated or cost-sensitive teams. See the current lineup on the models page.

Until April, every workflow was TypeScript that ran the same steps each time. That suits moving data between apps, and breaks down on work that needs judgment: deciding which stories in a feed matter, triaging a reply, drafting a response. Workflows now come in two types. Code workflows work as before. Agent workflows hand each run to an AI agent that follows a written procedure, and you can switch a workflow between the types.

Six more services can now start a workflow on their own events, which closes loops like booking, to CRM, to meeting notes without anyone copying data by hand. A Cal.com booking can create a lead in your CRM, and the Granola note from that call can update the record afterward.

Until now, each account belonged to exactly one workspace, so accepting a second invitation failed. As of March 29, one login can be a member of any number of workspaces. That matters most for consultants and agencies who build automations for several organizations, and for anyone who wants a test workspace next to their team's.

At launch, every OAuth integration required a workspace admin to register an app with the provider and paste in its credentials. That's still right for teams that want tokens issued to an app they own, but it's a lot of setup for one connection. As of March 26, General Input can supply the OAuth app itself, so members connect in one click on the provider's own consent screen, starting with QuickBooks.

Workflows often need to remember things: which leads were already processed, when the last run happened, a running list someone wants to query later. Keeping that state used to mean wiring up a spreadsheet or an outside database. Every workspace can now create its own databases, and the Databases page is in the sidebar for all members.

Until March 25, when the workflow builder or the chat agent needed a service, it loaded that service's complete API reference into its context, however few endpoints the task used. A large reference crowded out the conversation and made mistakes more likely. We split every integration's documentation into individual operations, one per endpoint, plus one shared section per service covering authentication, pagination, and error handling.

Ask the chat agent for a report, a slide deck, or a one-page graphic, and it now designs the file the way a web designer would: as HTML and CSS, exported through headless Chrome inside its sandbox. That gives every file a real layout engine, with grids, web fonts, proper text wrapping, and inline SVG charts, instead of hand-placed coordinates.

You can now work with the agent where your team already talks. It answers direct messages in Microsoft Teams, can be @mentioned in Slack channels to start a thread, and sends and receives files in Slack, Teams, and Telegram. From any of them it can search, run, and build workflows.

Your own databases are now connections like any other integration. Connect PostgreSQL, MySQL, or SQL Server, and agents can answer questions from your data in chat or use it inside scheduled workflows. When you have more than one, type @ and the connection's name to point the agent at exactly the right one.

General Input is live in public beta. You describe a job in plain English, and an AI agent turns it into a workflow: a real program that runs on a schedule or in response to events, presented as a document you can read and edit rather than a flowchart of nodes. Read the launch announcement.

You should be able to answer "what touched my Gmail account, and why?" without reading code. Since February 26, every time the platform decrypts one of your credentials it writes a record, and the Integrations page has an Access logs tab that lists them all.

A workflow is only useful if it runs at the right moment. By February 26 there were three ways to start one, and they are still the three trigger types today: a webhook, a schedule, or a poll that watches one of your apps for new items. The first polling providers covered new emails in Gmail, new rows in Google Sheets, Google Calendar events, Stripe charges and subscriptions, new subreddit posts, and RSS feeds.

Most automations need an AI model, a search engine, or a way to read web pages, and none of that should require signing up with another vendor first. Since February, workflows can use built-in platform services the moment they declare them, and all usage is paid from one prepaid credit balance you top up by card.

Most automation tools can only do what their prebuilt connectors expose. In General Input, an integration is two things: a way to connect your account (OAuth or an API key) and a curated API reference the agent reads before writing code against that service. That means the agent can use almost anything the service's API supports. By February 19, more than 90 services were documented and close to 60 could be connected, including Google Workspace, Microsoft 365, Slack, GitHub, Notion, Stripe, and Zendesk.

In General Input you don't write workflows; an AI agent does. By February 10 the agent could ask you structured questions mid-build, write the workflow, test it in the same sandbox production uses, and repair a failed run starting from its actual error.

We started General Input on January 24 with one thesis: instead of hand-maintaining hundreds of connectors that fall behind API changes, ship identity, triggers, and execution, and let an AI agent write the integration code each workflow needs. By January 29, every workflow was a real program running in its own fresh, isolated cloud sandbox.