In April 2026, OpenAI announced workspace agents in ChatGPT, a research preview for its Business, Enterprise and education plans (Techstrong.ai, April 2026). The reaction in the agent ecosystem was predictable: half the market assumed the category was over, the other half assumed nothing had changed. Both reactions are wrong. What changed is real, but it does not collapse the category; it sharpens the line between platforms and features.

This piece is the category map. It starts with plain ChatGPT, the chat assistant most people actually compare Gravity with, then covers Workspace Agents: what they are, how they compare to a focused agent platform, what each costs, when each is the right buy, and why the platform-versus-feature distinction matters more than any single feature.

Gravity vs plain ChatGPT

Most people who type "Gravity vs ChatGPT" mean the ChatGPT they already use, not an enterprise feature. The short version: ChatGPT is a chat assistant and Gravity is an agent that runs a job. In ChatGPT you open a window, ask, read the answer, and ask again; you are in the loop on every turn. In Gravity you describe the outcome you want once, and an agent does the work and hands back the result.

ChatGPT is very good at what a conversation is good for: asking questions, drafting and rewriting copy, debugging code with you, brainstorming, and one-off research. It has also grown agent-like features. Its pricing page lists scheduled tasks and custom GPTs on the Plus plan, and the Pro plan adds what OpenAI calls an always-on agent (ChatGPT pricing, read 9 October 2026), so the line between the two is not "ChatGPT cannot run things." The line is where the work lives and who does the setup. In ChatGPT you assemble the steps in a conversation; in Gravity the job is the product. Whether ChatGPT counts as an AI agent at all is its own question, answered in is ChatGPT an AI agent.

When plain ChatGPT is the right choice

Gravity is the better fit when the work should happen without you typing it each time, touches the tools you work in rather than just text, and is something you would rather hand off than supervise. These are not either-or choices. A sensible setup keeps ChatGPT for thinking and drafting and hands the recurring jobs to an agent. A practical way to find those jobs: list the prompts you type into ChatGPT every week, and for each one ask whether you want the answer or the outcome.

The April 2026 launch and what changed

OpenAI announced workspace agents for ChatGPT in April 2026, as a research preview for ChatGPT Business, Enterprise and education plans. A team describes a workflow in plain text, the agent is published inside the organization for others to reuse, and it can run on a schedule or respond to a trigger, work with tools such as Slack, and continue without a person typing. Administrators can require human approval for sensitive actions such as sending messages or changing records. The agents are powered by Codex, OpenAI's code-oriented model, and mark a move away from custom GPTs. The preview was free, with usage-based pricing expected to follow (Techstrong.ai, April 2026).

What changed in the market: the default agent for the "we already use ChatGPT" buyer now ships in the box. What did not change: the depth, focus, and ownership profile of a focused platform are different things, and ChatGPT Workspace Agents does not subsume them.

What ChatGPT Workspace Agents actually does

The product surface is the ChatGPT chat window with an "Agents" mode. From there a user can delegate a task ("review my inbox and draft replies", "build a Q2 forecast in this Google Sheet", "find the customer logos for our case studies"). The agent runs against the user's connected accounts, reports progress in the chat, and produces a deliverable.

Where it is strong

Three places. First, ad hoc delegation: one-off tasks a knowledge worker would otherwise do manually. Second, productivity-suite integration: Google Workspace and Microsoft 365 are already there. Third, the chat surface itself: people who live in ChatGPT have one fewer tab to open.

Where it is shaped by being a feature

The agent inherits ChatGPT's home. Workspace agents can now run on schedules and triggers, so "runs every Tuesday at 9am" is no longer the dividing line it was. What stays true is that you build, find, and review them inside ChatGPT, under ChatGPT's admin model and ChatGPT's plan structure, and their roadmap competes with everything else ChatGPT ships. For a team already living in ChatGPT, that is a feature. For someone who just wants a job handed off, it is a product to adopt first.

What Gravity does differently

Gravity is a platform whose entire roadmap optimises deployed autonomous agents. The agent is the first-class object; the chat surface is incidental. You describe an outcome, the agent deploys, runs on a schedule or trigger, integrates with your tools, monitors itself, and reports results to a dashboard built for agents (not a chat thread).

This is the same "describe outcome, not workflow" thesis that runs across the Gravity blog (see describe outcome, not workflow). The product implication is that every Gravity feature serves the deployed-agent job. Nothing in the roadmap competes for prioritisation with a chat surface, a foundation model release, a coding tool, or any of the other things OpenAI also has to ship.

Platform vs feature: the strategic distinction

The framing that matters. A platform is a product whose roadmap optimises one job. A feature is one capability inside a product optimising a different job. ChatGPT Workspace Agents is a feature inside ChatGPT, which is fundamentally a chat product. Gravity is a platform whose only job is agents. The same noun ("agent") covers different commitments.

Why the distinction is more than semantic

Three concrete consequences. First, roadmap. The platform ships agent features the feature cannot because the feature must also keep the chat product cohesive. Second, support model. The platform's support, docs, and account team are agent-focused; the feature's are ChatGPT-focused. Third, billing. The platform can price around agents; the feature has to roll into the parent product's per-user pricing logic.

For a deeper view of the build-vs-buy framing inside this distinction see build vs buy AI agent and AI agent deployment models.

Capability comparison

DimensionChatGPT Workspace AgentsGravity
Unit of workDelegated task inside a chatDeployed agent
Schedule / triggersSchedules and triggers (research preview)Cron, webhook, event, manual
Pricing modelNeeds a ChatGPT Business, Enterprise or education plan; preview free, usage-based pricing expectedBasic free (one agent); Mini Pilot $15/mo (one automated agent); Auto Pilot $20/mo
IntegrationsSlack and other enterprise suites, via ChatGPT's connectorsTop SaaS native + MCP for long tail
Customisation depthBounded by ChatGPT productFull agent definition and tool registry
Audit & monitoringWithin ChatGPT adminAgent-first dashboard
Vendor concentrationOpenAI-only stackMulti-model routing

Pricing: ChatGPT vs Gravity

The two are priced on different logic, so compare the shape before the number.

Which costs less depends on the job. For asking and drafting, ChatGPT's free plan or an individual plan is the cheaper fit, because that is what it is built for. For a job you want handed off, compare how many people would need a ChatGPT seat against how many agents the job needs on Gravity. A team that is not already on a ChatGPT business plan needs those per-user seats before Workspace Agents are available at all; one person handing off one recurring job can start on Gravity's free plan. If the other option on the table is Anthropic's, we compare Claude and ChatGPT for business teams separately.

The enterprise-vs-team buying motion

Half of this comparison is procurement, not product. ChatGPT Enterprise is a procurement vehicle: a SaaS deal a large company signs once and rolls out. ChatGPT Workspace Agents inherits that vehicle. If your company is already inside an OpenAI master agreement, adding Workspace Agents is friction-free.

A focused agent platform is a different motion. The buyer is typically the person, team, or function with a specific job to hand off, not central IT. Getting started takes a sign-in, not a procurement cycle; the proof-of-value is concrete, and the cost is a small plan rather than a seat rollout. For the broader framing on this see AI agent cost models.

When ChatGPT Workspace Agents is the right call

Three signals.

You are already standardised on ChatGPT Enterprise

The team has ChatGPT Enterprise seats, central IT signed the deal, and you are inside the OpenAI procurement vehicle. Adding Workspace Agents is one toggle. There is no new vendor friction.

The use cases are chat-augmented, not deployed

"Help me draft this email", "summarise this document", "find this customer logo". Ad hoc delegation. The agent does not need to run every day. The chat surface fits.

Procurement values a single vendor

For some companies, fewer vendors equals less compliance overhead. The bundle wins on procurement even if the focused platform would win on capability. This is a legitimate decision.

When Gravity is the right call

Three opposite signals.

The job is deployed, recurring, autonomous

"Greet every new customer", "follow up cold leads weekly", "reconcile invoices Monday". The agent runs without you. Chat-inside-ChatGPT is not the right surface.

You want focused roadmap commitment

You want every product decision to optimise the agent surface. OpenAI's roadmap optimises ChatGPT first; Workspace Agents is part of that. A focused platform makes a different commitment.

You want a small, flat price without a seat rollout

Gravity's plans are flat and small: Free is $0, Mini Pilot is $15 a month for one automated agent, and Auto Pilot is $20 a month. There is no per-user business plan to buy before the first agent runs, which matters when the person with the job is one operator rather than a whole department. See AI agent orchestration and three startups, three shutdowns for the deeper view on why focus matters.

Frequently asked questions

What are ChatGPT Workspace Agents?

Workspace agents are OpenAI's shared agents inside ChatGPT. OpenAI announced them in April 2026 as a research preview for ChatGPT Business, Enterprise and education plans. A team describes a workflow, publishes the agent inside the organization, and the agent can run on a schedule or a trigger, work with tools such as Slack, and ask a person to approve sensitive actions. The preview was free, with usage-based pricing expected to follow.

Is ChatGPT Workspace Agents a competitor to Gravity?

Partially, and only for the buyer who values bundle convenience over focused capability. ChatGPT Workspace Agents are a feature inside a chat product. Gravity is a platform built around deployed long-running agents. Both can complete some of the same tasks, but the buying motion, ownership model, and pricing structure are different categories.

Why would I choose a focused agent platform over ChatGPT Workspace Agents?

Three reasons. First, Workspace Agents live inside ChatGPT, so building, running, and reviewing them happens in a chat product, which suits teams already standardised on it more than someone who just wants a job handed off. Second, OpenAI's roadmap optimises ChatGPT as a whole, not the agent surface alone. Third, price: Workspace Agents sit on top of a per-user ChatGPT Business, Enterprise, or education plan, while Gravity's Free plan is $0 and Mini Pilot is $15 a month.

When is ChatGPT Workspace Agents the right call?

When your team is already standardised on ChatGPT Enterprise, when procurement values a single vendor, when the use cases are mostly chat-augmented ad-hoc tasks rather than deployed daily ops, and when you want zero new vendor friction. The bundle wins on procurement. The focused platform wins on agent depth.

What is the strategic difference between platform and feature?

A platform is a product whose entire roadmap optimises one job. A feature is one capability inside a product optimising a different job. ChatGPT Workspace Agents is a feature inside ChatGPT, which is a chat product. Gravity is a platform whose only job is deployed autonomous agents. The same word covers different commitments.

Can I replace ChatGPT with Gravity?

Usually not, and you do not need to. They do different jobs. Keep ChatGPT for asking questions, drafting, and thinking out loud. Use Gravity for a job you want off your plate: describe it once, and an agent runs it and hands back the result. Keeping both is a sensible default: chat for thinking, an agent for the work you would rather not do by hand.

Is ChatGPT cheaper than Gravity?

For asking questions and drafting, ChatGPT is the cheaper fit: it has a free plan, and its paid plans are priced per person or, for Business and Enterprise, per user. For a job you want handed off, Gravity's Free plan is $0, Mini Pilot is $15 a month for one automated agent, and Auto Pilot is $20 a month. Compare on how many people need access and how often the job runs, not on the headline price.

Three takeaways before you close this tab

Sources