June 4, 2025
The real reason prompt engineering is dying and what comes next
Decidr
AI in business
For the past two years, prompt engineering has been one of the buzziest skills in tech. As large language models (LLMs) like GPT-4, Claude and Gemini exploded into the mainstream, an entire cottage industry sprang up around crafting the perfect phrase to elicit the right response. Careers were launched. Courses sold out. “Prompt whisperers” became a thing.
But in 2025, something is shifting and fast. The need for manual prompt engineering is quietly fading. Not because prompts are irrelevant, but because the way we interact with AI is fundamentally evolving.
Why prompt engineering thrived… briefly
Prompt engineering surged because it solved an early limitation: how to communicate effectively with LLMs that had no memory, no grounding and no internal goals. Users needed clever workarounds to get consistent outputs. Whether writing content, debugging code or summarising data.
From few-shot examples (a machine learning framework in which an AI model learns to make accurate predictions by training on a very small number of labeled examples) and rigid templates to anthropomorphising AI with “You are a helpful assistant…” instructions, it was all just scaffolding. Workarounds to guide static models without true context or agency.
But the world is moving on
Today, AI is increasingly embedded into workflows, products and systems, not perched inside a chatbot waiting for a perfectly-worded command. Three shifts are driving the decline of prompt engineering:
Multi-modal interfaces
Models like GPT-4o and Gemini 1.5 can now process combinations of voice, video, images, screen input and text. You don’t need to type a prompt when you can just point, show or speak. AI is moving beyond language towards interaction.
Agentic systems
From memory-enabled OpenAI agents to autonomous tools like Cognosys, Hypercycle and Decidr, AI is becoming less reactive and more proactive. These agents don’t just respond — they plan, reason and act. Tell your assistant to “set up a re-engagement campaign” and it’ll handle the copy, segmentation and scheduling autonomously. No prompt engineering required.
Invisible orchestration
Behind the scenes, LLMs are being integrated directly into apps and APIs. In these environments, prompts are generated by software, not users. You don’t tell Notion AI how to behave. You just click “Summarise” and the system handles the context invisibly.
The real reason it’s fading
Prompt engineering isn’t dying because it failed. It’s fading because it succeeded, as a transitional skill. Now, it feels clunky. Manual tinkering with phrasing or format doesn’t scale. As models become more adaptive, we expect them to understand us, not the other way around.
It’s the same story we’ve seen before. From command lines to GUIs, from hand-coded HTML to drag-and-drop builders. Prompt engineering was never the destination. It was the on-boarding.
What comes next
In this next phase, the value shifts to:
Context - systems that remember who you are, what you’ve done, and what you need.
Orchestration - platforms that route tasks intelligently across tools, models and data.
Autonomy - agents that initiate, adapt and improve continuously.
We’ll still shape and guide AI, but increasingly through goals, outcomes and feedback loops, not finely tuned instructions.
That’s where Decidr comes in…
We’re building an operating system for decision intelligence. Where AI doesn’t just react, but collaborates. Our platform blends orchestration, autonomy and context into a single ecosystem that works the way humans do i.e. by setting goals, adapting to feedback and making smart decisions over time.
The skill of the future isn’t prompting. It’s system thinking. Goal setting. AI reasoning.
The age of the prompt is ending. The age of intent is just beginning.
