I'll be upfront about where I started on this.
When I first encountered platforms providing "no-code" agent solutions, I was quietly sceptical about their long-term role. The "SaaS is dead" narrative was gaining traction — the argument being that AI makes it straightforward to build your own custom tools on raw APIs, so why pay for a platform someone else controls?
This is making some big assumptions about people and their behaviour…
The API Route Makes Sense — In the Right Context
If you're building something for your own use (and you have great product development skills) the case for raw APIs is solid. You know your requirements. You control your own environment. You can make trade-offs because you're the one living with them.
I've built tools for myself and other projects this way — custom, lightweight, sitting on my own stack. In those contexts, it works well. In fact, this is 80% of my AI-driven development over the last year.
After getting my initial exposure on no-code platforms, I wanted to pursue the self-development API methods — even getting GCP certified as an associate engineer in the process.
Having dived deep into development — having a lot of fun projects and delivering some strong value — I realised that all the development was taking me away from what I really want to be doing and think I have a unique skillset in. Understanding workflows — knowing what the desired outcome is and designing and implementing solutions that work.
When developing custom API-driven solutions, now you're managing server infrastructure, handling permissions and security, thinking about what happens when usage scales, maintaining uptime, and keeping dependencies current — all while trying to analyse the client's actual problem, design a solution that fits their context, and deliver something they can understand and run themselves.
What Changes When the Platform Handles the Plumbing
Building on Autohive, I noticed something early. I was spending almost all of my time on the parts that actually matter: the problem analysis, the architecture decisions, the logic of how an agent should behave.
The things that had absorbed so much time on custom builds — environment setup, credential management, security considerations, scaling questions — were handled at the platform level.
A recent example: a billing and time tracking agent for my own business. It listens to natural language input, creates a calendar event, logs the entry in a spreadsheet, and runs a post-execution audit to verify both systems are in sync before confirming back to me. The part of that process that took time was the design thinking — the architecture, the audit logic, the decision to separate each workflow into a specific triggered action rather than one sprawling agent. The infrastructure wasn't something I had to think about at all.
I could build something similar using Cloud Run with a basic UI. But Autohive removes the overhead entirely — and when a client wants something comparable, I'm building for their problem, not billing them for time diagnosing permissions issues.
A good platform doesn't limit what you can build. It limits what you have to think about. Those are very different things.
The Maintenance Problem With Custom Builds
There's another dimension to this that I think gets underweighted: custom solutions don't just get harder to build — they get harder to maintain.
Every new feature adds complexity. Every complexity introduces new ways for things to break quietly. Security isn't something you set up once; it needs active attention as the environment changes. When something goes wrong, there's no support layer — there's just you.
Platforms compound differently. Each new workflow you add sits inside an environment that's already secured, already monitored. The operational burden doesn't grow at the same rate as the capability. For a client who wants to keep automating more over time — which is exactly what the best clients want — that's a fundamentally better foundation.
Where Custom Builds Still Make Sense
This isn't an argument against custom development. There are situations where it's the right call — highly specific requirements, particular data sovereignty concerns, or cases that fall genuinely outside what a platform can handle. That category exists. It's just smaller than the current narrative implies, and it's getting smaller as platforms mature.
For everything else — which is most automation work — the platform model is where I'm operating now. That includes my own business, not just client work. The scaling advantages compound over time: each new workflow I add sits inside an environment I already understand, already trust, already know how to extend. Building familiarity on a single platform turns out to be its own kind of leverage.
What This Means for How I Work
Autohive has become my default starting point — for client engagements and for my own operations because it keeps me focused on the work that actually creates value: understanding the problem, designing the solution, making sure the change sticks for the people using it.
Disclosure: I've signed up as a referral ambassador with Autohive and want to be upfront about that. I'll be looking to pass any referral commission directly to clients who sign up through me — I want clients to know I'll always recommend the best tool for the job.
Jasper Irvine
Founder, Plain Logic