The Speed of Obsolescence: What we learn when the 'new' becomes 'old' in months
The Speed of Obsolescence: What we learn when the "new" becomes "old" in months
Originally published on TechSambad Substack
It has been a big week for us at TechSambad—we have officially incorporated as an OPC firm. Our focus remains clear: building Agentic Solutions to empower students and working professionals. (You can see the full roadmap at techsambad.com).
But as I sat down to reflect on the week, I kept coming back to a point made by Ethan Mollick: how quickly "cutting-edge" solutions can become redundant.
In the world of AI, "redundant" does not mean "bad"—it means the technology is maturing so fast that the "hard way" of doing things is being replaced by the "easy way." Looking back at my own journey over the last few months, I can see three specific areas where the landscape has shifted radically.
1. The Transition from "Building" to "Integrating"
There is a massive distinction between a "Builder" and a "Harness." Earlier this year, I took great pride in learning OpenAI Agent Builder. It was a great entry point — a drag-and-drop interface to build workflows. Microsoft had a similar offering with Copilot Agent Builder.
But here is where it gets interesting: these "Builder" models are becoming redundant. They are being replaced by what I call Harnesses — tools like OpenClaw, Claude Code, Hermes, and Codex.
While the Builders gave us a playground, the Harnesses give us power. They allow us to "summon" and "spawn" agents, and because they lean into natural language, they make the complexity of programming agents much more accessible. Most importantly, their ability to extend into collaboration platforms like Slack, WhatsApp, and Telegram — making them accessible on mobile devices — turned them into the "Agentic platform killers." We are moving away from simple "builders" and toward robust "harnesses" that actually live where the work happens.
2. The End of the "Infrastructure Grind"
Then there was my time with OpenClaw. For a non-techie, the learning curve was steep. I was running it on my laptop, grappling with local infrastructure, and navigating the complexities of CLI-based systems. It was a massive undertaking to get my agents into production.
But look at what happened in just a few months: with the rise of Claude Code, and the moves by Grok (GrokBot) and Meta, the "tedious" part of the setup is vanishing. We are moving toward a world where a functional agent can be deployed via text prompts or integrated into WhatsApp in a few clicks. The "hustle" of the backend is being automated.
3. From "Prompt Engineering" to "Looping & Graphs"
This is the most critical shift. We are moving away from the "art" of crafting the perfect prompt. While defining the boundary conditions and goals still requires expertise, the act of "polishing" a prompt is no longer the primary task.
We are moving toward Loops and Graphs. We give the agent a goal, and the agent iterates — it crafts its own prompts, tries, fails, and adjusts until the goal is met. The human becomes the architect of the goal; the AI becomes the architect of the execution.
The Bottom Line
We are living in an era where what we learn today might be the "standard" of tomorrow. As the White Rabbit in Alice in Wonderland says, we are often "running to stay in the same place."
In this fast-moving landscape, the only way to stay ahead is to stop focusing on the "tools" that will be obsolete in six months, and start focusing on the "logic" that stays relevant.
If you are looking to navigate these complexities and build durable Agentic Solutions, let us talk.
Views are my own and made in personal capacity. SAP is not responsible for any content.