Executive Summary: The Conversational Computer & the Future of Human-Centered Enterprise Computing

Mark Uppelschoten
Nov 21, 2025
2 min read

Updated: 5 days ago

The documents outline DevRev’s vision for a new era of computing: the rise of the conversational computer, a system that moves beyond apps, screens, and static workflows toward a computer that can reason, remember, collaborate, and act like a digital teammate.

Below is a concise, enterprise-grade summary.

1. From tools to collaborators: the computer becomes a peer

The modern computer is no longer limited to executing commands. With long-term memory and reasoning models, it becomes capable of:

understanding multi-step business logic,
maintaining context across workflows,
prioritizing and classifying decisions,
acting with a form of “agency,”
and collaborating with humans as a thinking partner.

This transforms the computer from a productivity tool into a cognitive collaborator.

2. Dynamic capabilities: Search, Answer, Reason, Generate

The conversational computer doesn’t just retrieve data. It:

finds information,
explains it,
reasons with it,
generates new content,
connects existing knowledge,
and adapts to user needs in natural language.

Content becomes user-generated, self-organized, and explainable.

3. Agents replace apps

Instead of isolated applications, the new architecture uses agents:specialized modules with their own skills, memory, and access rights.

Agents:

execute defined responsibilities,
collaborate across departments,
integrate with external systems,
and carry domain knowledge.

Some agents are integrated, others federated, depending on legacy constraints.

This creates a multi-agent ecosystem optimized for enterprise work.

4. The importance of long-term memory

Enterprise memory is now organized as:

graph databases,
vector stores,
knowledge warehouses,
structured and unstructured data collections.

This allows the conversational computer to:

recall past actions,
learn from interactions,
reason over historical data,
and provide continuity across workflows.

It’s the opposite of the “stateless app” world.

5. Large Reasoning Models (LRMs)

Beyond language generation, LRMs bring:

logic,
long-chain-of-thought,
problem solving,
workflow planning,
knowledge-based reasoning,
and instruction following.

Where LLMs speak, LRMs think.

Together they create enterprise-grade intelligence.

6. Organizing complex enterprise data

The conversational computer bridges the gap between:

planet-scale search (like Google),
enterprise systems buried behind authentication,
legacy apps with weak APIs,
and human workflows that previously held everything together.

It enables:

semantic search,
analytical answers,
structured data reasoning,
knowledge retrieval across billions of records,
and enterprise-grade governance.

This shifts the burden of interpretation and synthesis from humans to machines.

7. Human-in-the-loop: indispensable

Even with agents and reasoning models, humans remain essential.They provide:

oversight,
goal setting,
judgment,
and ethical guidance.

The system is built to augment human intelligence, not replace it.

8. Displays become less important

The future moves:

from big desktops to mobile experiences,
from “billboard interfaces” to contextual assistants,
from clicking through apps to conversational interaction.

Work happens on the go, across devices, with minimal friction.

9. Team intelligence: the next evolutionary step

The conversational computer unlocks:

cross-department collaboration,
shared organizational memory,
consistent customer experiences,
and faster problem solving.

Teams and agents operate as one unified intelligence, supported by long-term memory.

10. The third rebirth of the computer

We have entered the third major transformation:

Desktop computing
Mobile computing
Conversational computing

This new era blends:

natural language,
reasoning,
agents,
enterprise memory,
and integrated workflows.

The result is a truly human-centered computer.