In the world of software development, we often think in terms of requests and responses. A user clicks a button, a request is sent to a server, the server does something, and it sends a response back. This is a classic stateless interaction. Each request is a self-contained, independent event. For countless applications, from serving web pages to simple API lookups, this model works perfectly.
But what happens when the "something" your server needs to do isn't a single, instantaneous action? What if it's a complex business process that involves multiple steps, calls to third-party APIs, and intentional delays?
Consider a new user signup process:
This isn't a single request-response cycle; it's a long-running process. If you try to run this in a standard stateless environment (like a simple serverless function), you're setting yourself up for failure. A single network hiccup or API timeout can bring the entire workflow to a screeching halt, leaving your user in limbo and your data in an inconsistent state.
This is where the distinction between stateless and stateful execution becomes critically important. For reliable business process automation, you need more than fire-and-forget functions; you need durable, stateful workflows.
A stateless system has no memory of past events. Each time a function runs, it’s a blank slate. While this simplicity is attractive, it creates significant problems for multi-step processes:
Stateless execution forces you to choose between unreliable processes or building and maintaining a complex, bespoke state machine. There’s a better way.
A stateful, or durable, workflow engine fundamentally changes the game. It treats a business process as a single, coherent unit, even if it executes over hours or days.
At its core, a durable execution platform automatically tracks and saves the state of your workflow at every step. Think of it as an automatic "save game" feature for your business logic.
This approach delivers transformative benefits:
This level of enterprise-grade durability might sound complex to implement, but it doesn't have to be. At Workflows.do, we've made durable execution a core, invisible part of the developer experience.
We believe your focus should be on writing clear business logic, not on building plumbing. We call this Business-as-Code. You define complex, multi-step, AI-powered workflows as simple, easy-to-read code, and our platform handles the immense complexity of making them reliable and observable.
Take a look at the user signup process we described earlier, implemented as a Workflows.do agent:
import { AI } from 'workflows.do'
export default AI({
onUserSignup: async ({ ai, api, db, event }) => {
const { name, email, company } = event
// Enrich contact details with lookups from external data sources
const enrichedContact = await api.apollo.search({ name, email, company })
const socialProfiles = await api.peopleDataLabs.findSocialProfiles({ name, email, company })
const githubProfile = socialProfiles.github ? await api.github.profile({ name, email, company, profile: socialProfiles.github }) : undefined
// Using the enriched details, deeply research the company and personal background
const companyProfile = await ai.researchCompany({ company })
const personalProfile = await ai.researchPersonalBackground({ name, email, enrichedContact })
const socialActivity = await ai.researchSocialActivity({ name, email, enrichedContact, socialProfiles })
const githubActivity = githubProfile ? await ai.summarizeGithubActivity({ name, email, enrichedContact, githubProfile }) : undefined
// Schedule a highly personalized email sequence to optimize onboarding
const emailSequence = await ai.personalizeEmailSequence({ name, email, company, personalProfile, socialActivity, companyProfile, githubActivity })
await api.scheduleEmails({ emailSequence })
// Summarize everything, save to the database, and post to Slack
const details = { enrichedContact, socialProfiles, githubProfile, companyProfile, personalProfile, socialActivity, githubActivity, emailSequence }
const summary = await ai.summarizeContent({ length: '3 sentences', name, email, company, ...details })
const { url } = await db.users.create({ name, email, company, summary, ...details })
await api.slack.postMessage({ channel: '#signups', content: { name, email, company, summary, url } })
},
})
This code looks deceptively simple, and that's the point. You write a single, logical function. Under the hood, Workflows.do treats each await as a checkpoint.
If the api.peopleDataLabs.findSocialProfiles call fails, the platform automatically saves the state (including the enrichedContact data from the previous step) and retries the failed API call. You didn't have to write any state management or retry logic—it’s built into the platform. This workflow can now run reliably over minutes, hours, or days, surviving any interruption.
In modern business, automation is no longer optional. But building it on a fragile, stateless foundation is a recipe for operational headaches and failed processes.
By embracing a stateful, durable execution model, you can build automation that is inherently resilient, observable, and powerful. Workflows.do provides this power through a simple, code-first paradigm, allowing you to turn your most complex operational challenges into simple, reliable services.
Ready to build business processes that just work? Discover how Workflows.do can transform your automation strategy.