Applied AI systems studio
For technical program leaders, prospective clients, and partners evaluating what comes next. We turn specific domain challenges into LLM-based workflows designed to produce results teams can inspect, trace, and verify.
Four engineering disciplines, unified by a common goal: building agentic systems that tackle real scientific and engineering problems.
How you frame a problem shapes what an LLM can do with it. We design the information structures — retrieved content, conversation history, and task framing — that give a model what it needs to reason well and stay on target.
What the model knows, precisely when it needs it.
Prompts are the interface between intent and model behavior. We write, test, and refine the instructions that guide models toward reliable, repeatable outputs — treating prompts as first-class artifacts that deserve the same rigor as any other engineered component.
Consistent behavior, not just a good first answer.
An LLM working alone is rarely enough. We build the orchestration layer — the pipelines, routing logic, memory systems, and coordination patterns — that let multiple models and tools work together as a coherent, controllable system.
Purpose-built systems, not improvised chains.
Choosing the right model for a task is an engineering decision, not a default. We evaluate capability, latency, cost, and fit against the actual requirements — so the model doing the work is the right one for that work, not just the most familiar.
The right model for the job, evaluated on evidence.
The disciplines above come together in agentic systems: LLM-based workflows where models reason, plan, and act across scientific and engineering problems. This is where Prompt’Ed Labs does its applied work — designing, building, and deploying solutions that produce results you can trace and verify.
Prompt’Ed Labs began in late 2022 as an initiative to learn and teach prompt engineering techniques. Inspired by Professor Synapse and others who were doing serious work in the field at the time, we set out to design prompts that could align language models for agentic tasks.
As the field has matured, so has our focus. Today, Prompt’Ed Labs builds and deploys LLM-based solutions that draw on prompt engineering, context engineering, and Harness Engineering to construct agentic systems for scientific and engineering problems.
We think technical systems should be clear enough to inspect, practical enough to use, and disciplined enough for teams to rely on in daily work.
Aura Dilone
Founder
Luis Veras
Member of Technical Team
Josmery Veras
Member of Technical Team
A useful first exchange
Technical program leaders, science and engineering teams, prospective clients, and partners can reach out when a specific workflow or domain challenge may benefit from applied AI.
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