AI Doesn’t Need Better Prompts. It Needs Better Context
Everyone’s talking about prompt engineering like it’s the endgame. It’s not. It’s barely the start.
The real power in AI doesn’t come from better questions; it comes from better context.
If you’ve read folks like Phil Schmid, Adnan Masood, or Jha Vztpc, the message is clear: context engineering is the unlock. Prompting without context is like asking someone to summarize a movie they haven’t seen. You might get something generic, but you won’t get anything useful.
And that’s been our whole thesis at Autoplay from day one.
Why Context Is Everything
Context engineering is about giving AI the right inputs, not just clever wording, but actual awareness.
For autoplay that means:
What is the user trying to do?
Where are they in the flow?
What do they already know (or not know)?
What’s happening on the screen, right now?
If you can answer those, you can build AI that actually helps.
At Autoplay, this is what we do. We don’t just watch session replays, we understand what’s going on in them. Our system learns your UI, your feature layout, your internal language. We detect user hesitation, frustration, and intent - all without needing manual tags.
We call that part Genie.
It’s our real-time context engine. And it’s why users can type:
“Show me sessions where people got stuck trying to connect Mailchimp”
and get real results, without ever needing to label what “connect” or “stuck” even looks like.
Because Genie already knows.
The Hardest Problem in Context Engineering
Acquiring the context, shaping it into the optimal format, and ensuring the delivery of the most relevant, updated information at the right moment—all while managing costs—are crucial.
Additionally, assessing the effectiveness of the context remains a significant challenge.
There’s no benchmark yet for “context quality.” No standard for evaluating how well an AI system was set up to succeed.
Most LLM-based tools throw everything into the prompt and hope for the best. But context isn’t just a dump of text; it’s about selection, timing, format, and relevance.
That’s what we’re working on behind the scenes:
Prioritizing what information to include
Formatting it so it makes sense to the model
Deciding when to deliver it
And doing all that in real time, without waiting for the user to ask.
Why It Matters
The next wave of AI tools won’t be about model size or token count. It’ll be about understanding the moment; what the user is doing, what they need, and where they’re blocked.
That’s what context engineering enables.
And if you’re building AI products without thinking about context—what’s in the prompt, what’s not, and what the model should already know—then you’re building blind.
We’re betting everything on this shift.
Because helping users right when they need it is what actually moves the needle.