Understanding No-Code Solutions Realities

When no-code started spreading, people thought the big unlock was getting access to development—being able to build websites, apps, integrations, and automations without needing an engineer. But pretty quickly, they realized that wasn’t actually the biggest problem. The real challenge was whether the idea itself was any good. No-code wasn’t just about building—it was about figuring things out faster. It let people test, iterate, and fail quickly without wasting time and money. More at-bats meant better ideas. Now the same thing is happening with AI in the enterprise. People think they just need an agent, an internal dashboard, or an AI-powered workflow. But once they start building, they run into the same core issue: Do they actually understand the problem well enough? Is this the right solution? And honestly, I’m excited for this shift. AI and no-code are removing the old excuses—“We can’t get dev resources” or “It’s locked behind expensive SaaS.” Ops teams—RevOps, SalesOps, MarketingOps, and beyond—are finally getting the power to build what they need. But once that barrier is gone, they’re going to run into all the other hard stuff. They’ll have to sit with problems longer, talk to internal stakeholders, validate ideas, define processes, map workflows, and align on what the future state should be. Before, they avoided that because committing to the work without guaranteed dev resources felt risky. Now? If they put in the work, there’s almost always a way to make it happen—with no-code, with AI, or both. And that’s a future worth being excited about.

No-code AI agents streamline the automation process with visual builders and drag-and-drop components, enabling rapid iteration through pre-built triggers, conditions, and AI blocks without touching code. Coded AI agents offer deeper control over data flows, memory management, and tool orchestration, allowing developers to define goals, customize model selection, and deploy modular APIs with frameworks like LangChain and FastAPI. While no-code tools are ideal for quickly validating ideas, coded frameworks are essential when building scalable agents that require fine-grained prompt engineering, multi-step workflows, and persistent context. Choosing the right approach depends on your skillset, use case, and speed to execution. Let’s break it down step-by-step : 🔹No-Code AI Agent Workflow Best for fast prototyping and non-tech users – Tools: Make, Zapier, n8n, Pipedream – Drag & drop interface – Add triggers, conditions, and AI blocks – Test and publish in minutes – Minimal learning curve 🔸Coded AI Agent Workflow Ideal for developers building complex, scalable agents – Tools: LangChain, Autogen, FastAPI, LlamaIndex – Define goals, write prompts, add memory – Full control over models, tools, and logic – Deploy as robust APIs – Requires programming knowledge 🔹When to Use What? – Choose No-Code when speed > complexity – Choose Coded when flexibility > ease – Hybrid is also possible - start no-code, scale with code Follow for more agent workflows, no-code blueprints, and real-world automation examples designed to help you build smarter. #genai #agenticai

I was talking with Jason Fried about no-code tools because I had an idea for an app. For the uninitiated: No-code lets someone like me, zero coding experience, build an app with almost any functionality in just a few days. Which is incredible. I can make the app do everthing I want it to do. And also… the problem. Fried’s point? Just because you can build something, doesn’t mean you should. It’s tempting to over-engineer. To keep adding features “just in case.” To solve every possible edge case upfront. But every feature you add? That’s something you have to support, maintain, and explain. Solve the problem simpler. Fewer screens. Less buttons. It reminds my of something Guy Kawasaki once said: “You can design a car with a windshield wiper that automatically adjusts to 85 different speeds. Most people just need 5.” Simple solves the problem. Simple is easier to build. And simple is a lot easier to live with. Today the hard part isn’t making something. It’s knowing when to stop.

Last month, our Devsinc business analyst, accomplished something that would have seemed impossible five years ago. In just two weeks, she built a complete inventory management system for our client's warehouse operations – without writing a single line of code. The client had been quoted six months and $150,000 by traditional developers. Fatima delivered it in 72 hours using our low-code platform, and it works flawlessly. That moment crystallized a truth I've been witnessing: we're experiencing the assembly line revolution of software development. Henry Ford didn't just speed up car manufacturing; he democratized automobile ownership by making production accessible and efficient. Today's no-code/low-code movement is doing exactly that for software development. The numbers tell an extraordinary story: by 2025, 70% of new applications will use no-code or low-code technologies – a dramatic leap from less than 25% in 2020. The market itself is exploding from $28.11 billion in 2024 to an expected $35.86 billion in 2025, representing a staggering 27.6% growth rate. What excites me most is the human transformation happening inside organizations. Citizen developers – domain experts who build solutions using visual, drag-and-drop tools – will outnumber professional developers by 4 to 1 by 2025. This isn't about replacing developers; it's about unleashing creativity at unprecedented scale. When our HR manager can build a recruitment tracking app, our finance team can automate expense reporting, and our project managers can create custom dashboards, we're not just saving time – we're enabling innovation at the speed of thought. For my fellow CTOs and CIOs: the economics are undeniable. Organizations using low-code platforms report 40% reduction in development costs and can deploy applications 5-10 times faster than traditional methods. The average company avoids hiring two IT developers through low-code adoption, creating $4.4 million in increased business value over three years. With 80% of technology products now being built by non-tech professionals, this isn't a trend – it's the new reality. To the brilliant IT graduates joining our industry: embrace this revolution. Your role isn't diminishing; it's evolving. You'll become solution architects, platform engineers, and innovation enablers. The demand for complex, enterprise-grade applications will always require your expertise, while no-code handles the routine, repetitive work that has historically consumed your time. The assembly line didn't eliminate craftsmen – it freed them to create masterpieces. No-code/low-code is doing the same for software development, democratizing creation while elevating the art of complex problem-solving.

The conversation around vibe coding is broken. 𝗩𝗶𝗯𝗲 𝗰𝗼𝗱𝗶𝗻𝗴 𝗶𝘀 𝘁𝗵𝗲 𝗻𝗲𝘄 𝗘𝘅𝗰𝗲𝗹 𝗳𝗶𝗹𝗲. In the early 2000s I did a lot of work consulting for major corporations. Most of that work ended up being creating web applications to replace Excel files created by non-coders. These corporations would spend millions of dollars on software implementations from companies like Oracle, but individual departments would struggle with bugs, incorrect business rules, and poor usability. To actually do their work someone would create a big Excel file that acted as a shim for the expensive software, letting them get the real work done. We would then come in and analyze that Excel file, reverse-engineering the business rules and the underlying problems it solved, and producing a small intranet web application that solved the same problems (and skirted around the big system's problems). I see those same kind of non-coders today saying that they're "vibe coding" apps. But this doesn't mean developers are being replaced. It's all about context. 𝗘𝘅𝗰𝗲𝗹 𝗙𝗶𝗹𝗲 𝗔𝗽𝗽𝘀  Many of these vibe coded apps are providing the same service as an Excel file. It lets non-coders carry out an aspect of the job that existing software isn't helping them do. Does it mean they aren't hiring consultants to write these for them? Sure, but it also means they will need maintenance and fixes in the future. Unlike an Excel formula, the non-coder will have a harder time validating that the code is correct. Someday, a skilled developer may have to take the reins. Though, if the app isn't very complex, it may last for a long time. I've seen massive Excel files that ran a large department's core processes for 𝘺𝘦𝘢𝘳𝘴. That's ok! Because not all apps can be vibe coded. 𝗣𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝗔𝗽𝗽𝘀 As app requirements get more complex and the number of users (and the visibility of the app's flaws) increases, inevitably well-engineered software must be built. Security, performance, maintainability, and verified business rule implementations fall outside the realm of non-coder experience. You can only get so far on LLM vibes. 𝗧𝗵𝗲 𝗖𝗼𝗻𝘃𝗲𝗿𝘀𝗮𝘁𝗶𝗼𝗻 The conversation around vibe coding, thus, is broken. In 𝘴𝘰𝘮𝘦 𝘤𝘰𝘯𝘵𝘦𝘹𝘵𝘴, vibe coding is enabling the non-coder to do their work, and makes them feel like they don't need to go back and forth with developers about bugs any more. In 𝘮𝘰𝘴𝘵 𝘰𝘵𝘩𝘦𝘳 𝘤𝘰𝘯𝘵𝘦𝘹𝘵𝘴 of software engineering and application development, experienced software developers understand that vibe coding is at best foolish, and at worst dangerous. The problem is we tend to discuss the topic from our own perspective, our own context, as if it was the only context to exist. So I recommend you step outside the hype and your own bubble. 𝗩𝗶𝗯𝗲 𝗰𝗼𝗱𝗶𝗻𝗴 𝗺𝗮𝘆 𝗯𝗲 𝘁𝗵𝗲 𝗻𝗲𝘄 𝗘𝘅𝗰𝗲𝗹 𝗳𝗶𝗹𝗲, 𝗯𝘂𝘁 𝗘𝘅𝗰𝗲𝗹 𝗳𝗶𝗹𝗲𝘀 𝗻𝗲𝘃𝗲𝗿 𝗿𝗲𝗽𝗹𝗮𝗰𝗲𝗱 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿𝘀. Neither will LLMs.

Superpath doesn't exist without no-code, and but it's straining under the weight of it these days. I've got 90 Zaps processing around 8,000 tasks each month. It's amazing how much happens when all this works properly. Writers get paid, Superpath gets paid, customers get notified, Airtable bases get updated, etc. But I also find myself troubleshooting these Zaps constantly. And the more sophisticated the workflows get (and the more I rely on them), the more errors happen, and the more time I have to spend troubleshooting. There are a few big challenges with no-code these days: One is that the automations run in the background. For example, if I change a status in Airtable, it triggers a Zap. It's invisible, but I'm mostly able to remember this kind of thing so I don't accidentally trigger something I don't mean to. All this remembering clogs my brain and I still end up triggering stuff by accident anyway. Another is that I've automated so many things that I forget they are even there. For example, when someone posts a freelance gig in our Slack channel, we ask them to fill out a form so we can standardize the data, then that posts in Slack, and then we send some follow-up emails to see how it went. It's complicated considering that it's only marginally better than just letting people post directly in the channel. When this automation has issues, I have to wonder if it's even worth my time to fix it. Lately, the entire business feels duct-taped together by Zapier. What used to feel amazing—a one-person business scaling via automation!—now feels like a very disconnected experience both for me and our members/customers. I haven't decided yet what to do about this. In some cases, we should evolve from no-code to code. In others, we should probably just eliminate unnecessary workflows. And still in others, this is just the small cost of automating work that would be far too painful to do manually. I absolutely love Zapier—maybe even too much. But I've got a case of no-code fatigue and I'm curious if others feel this too.

Is the promise of low-code/no-code platforms too good to be true? While they may be suitable for simple applications or prototypes, low-code and no-code platforms often fall short when it comes to building complex, scalable software that meets the unique needs of a growing business. Here’s what you need to consider: 𝗦𝗰𝗮𝗹𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗖𝗼𝗻𝗰𝗲𝗿𝗻𝘀: Initial developments are swift, but as complexity grows, these platforms might struggle to keep up. 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗥𝗶𝘀𝗸𝘀: With convenience comes risk. The more we depend on third-party platforms, the more we expose ourselves to potential breaches. 𝗟𝗶𝗺𝗶𝘁𝗲𝗱 𝗖𝘂𝘀𝘁𝗼𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻: What you gain in speed, you often lose in flexibility. Custom needs can become a tall order! 𝗢𝘃𝗲𝗿𝗿𝗲𝗹𝗶𝗮𝗻𝗰𝗲 𝗼𝗻 𝗩𝗲𝗻𝗱𝗼𝗿𝘀: Tied to the tools your vendor supports, what happens when they can no longer support your project? 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗗𝗲𝗯𝘁 𝗔𝗰𝗰𝘂𝗺𝘂𝗹𝗮𝘁𝗶𝗼𝗻: Quick fixes can lead to long-term headaches. Are you building a castle on sand? On a recent episode of my podcast I interviewed Nick Farrish about his experience using Oodo for his company. Hidden costs and scalability issues ultimately led Kudu to build its own custom software. Thinking of using no-code/low-code? Read the full story on the Startup Hustle Newsletter: https://lnkd.in/g7ErCQ46

Just describe what you want and AI will build it No, not really. This is very much overhyped right now Real engineers know this No-code AI builders are great until you actually have to go to production We’re in the middle of an AI coding gold rush Sure—it looks magical Until you try integrating Stripe Or handling user auth AI can generate a boilerplate It can speed up iteration But shipping something scalable and production-ready still requires real engineering Most people underestimate that Ask the AI to regenerate the same piece of code 15 times till it gets it right if you'd like, but do you really want to debug that later? You can’t build serious applications if you don’t know how systems connect It’s why most AI-built apps today hit a ceiling Databases, APIs, edge cases, and error handling still matter We’re not at “text to app” just yet We’re at “AI teammate" who helps you ship code faster—if you know where you’re going These AI tools in the hands of a software engineer is a major productivity boost for sure. However, when used incorrectly.... They can introduce a lot of bugs into the code base if you don't know how to instruct it properly So yes, AI will change how we build. I strongly believe we'll get to that true, no-code application world in the future, but right now we have to be realistic with expectations. #nocode #engineering #saas #aibuilders

Yes, you can use no-code to build your product. But should you? No-code tools are growing rapidly, and yes, they're powerful. I've seen founders use them to validate MVPs, build quick prototypes, and test ideas without massive upfront investment. But while it is a "faster" way to start, is it worth the effort? Because no matter how smart the AI or no-code tool is, you're fundamentally bound by its design. Every customization becomes a workaround, every integration a compromise, and every scaling attempt feels like forcing a square peg into a round hole. And sometimes, it takes just as much effort to work around these limitations as it would to build it right with engineers from the start. Now, don't get me wrong—I’ve found no-code incredibly useful for operations, workflow automation, and internal tools. But for building actual products that need to scale? That's where you need real engineering expertise. Just look at the data: Despite the rise of AI and no-code, devs are still making over 5.2 billion contributions to 518 million projects on GitHub in 2024 alone. This just shows that expertise is still essential—AI and no-code won't replace the problem-solving and technical depth that engineers bring. 💭 Which of these tools have you tried? Did you hit the same walls I mentioned? Or have you found better use cases? #nocode #technology #startups #engineering 

The biggest weakness of no-code software right now (IMO) is the lack of support for database-driven business logic. For complex business logic, a user-input in your frontend of choice is often passed into the database, validated against or modified by numerous formula fields, and then outputted back to the user. In Airtable, I've had to use automations with multiple steps, like 'Find,' to ensure business logic is processed correctly. But the problem is two-sided. Most frontends lack support for that kind of querying and function capacity. To fix that, I build out fields in Airtable on top of which conditions can be built in Noloco, for example. But now the problem is that I'm layering numerous nested condition groups direclty into the UI components, making the business logic harder to manage across my stack. (BTW, Noloco is my favorite modular app builder and is highly flexible. But the point here is that no-code databases and app builders generally lack support for true queries and functions) And so instead of functions in traditional software development, builders in tools like Airtable are left bootstrapping their frontend business logic requirements with overly-complex formula fields, lookups, and rollups that (1) crowd the schema, and (2) lack the same performance as a true query or set of functions. SmartSuite partially lessens the friction with support for dot-notation formulas that can look through tables and into their fields. Glide Tables also offers a query column, which really helps: stitching together user-inputs on the frontend with logic in the backend is much more seamless than in other tools. Yet even there, the querying, filtration, and logical requirements are "baked" directly into the query column, which is an attribute of the database rather than a separate layer in the development stack (functions in Xano, for example). So if one of the goals of no-code is to lower the barrier to development, then it's high time these modular platforms step their game up with functions and queries so that people aren't left bootstrapping a solution together or resorting to the heavier-weight tools like Xano and Supabase to get the job done. Not every no-code data tool needs this kind of functionality since many of them aren't geared toward use as application backends. But for those that are, it's a necessity. #nocode #software #development #tech