What Relations of Production Do New Productive Forces Require?
From job replacement to reshaping organizational and industry divisions of work.
RIKKALAB / AI & Digitalization
Putting enterprise AI to work starts with rebuilding the digital world
Business is already complex. Stronger AI alone is not enough: we also need to reorganize the relationships among business, systems, and intelligence, reducing repeated definition, judgment, and coordination so that people and AI can work in the same digital environment.
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Why
What Relations of Production Do New Productive Forces Require?
From replacing jobs to reshaping organizational and industry divisions of work.
HowFrom business to code: Reasoning across three architecture models
Keep business definitions connected to implementation
What it means for AIWhy do AI agents stall when put to work?
From improving agents to improving their environment
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Continue through the five topic groups.
New Productive Forces and the Digital World
Why rebuild the digital world
Business Modeling and Gaps in Ownership
What to define, and who defines it
Business Modeling is fundamentally about defining how business is represented
Modeling is not simply drawing existing workflows. It decides which distinctions in reality enter the Digital World and what structures give them form.
- The Hidden Gap in Enterprise Digitalization: Who Defines How Business Is Represented?
- Why has system implementation become configuration hell?
- Why Systems Can't Make Up for Unresolved Business Problems | Why System Development Must Start with the Business
- Why do businesses still rely on group chats and shared Excel files despite having so many systems?
From Business Definitions to System Implementation
Turn structure into working systems
Product requirements define the gap between the business and its digital twin
Identify the gaps between business needs and the existing digital twin behind requests for workflows, reports, usability improvements, and agents. Define the scope of development and verify its effects in actual business operations.
Tasks, Functions, and the Division of Work with Agents
First understand where tasks come from
Why enterprise AI must start with the business: Business → organization → systems → agents
What an agent can do depends on whether the business is clearly defined, responsibilities are explicit, and systems reliably represent and maintain those structures. Enterprise AI can start within a limited scope, but it cannot skip these prerequisites.
- What do we mean when we say “let AI help people complete tasks”?
- Before designing an agent, understand where tasks come from
- Before discussing where to use agents, rethink business functions and the division of work in organizations
- Agents will not eliminate workflows; they will force us to rethink them
Agents and Environment Engineering
The boundaries of harnesses, context, and memory
Why do AI agents stall when put to work?
Complexity left unresolved in business definitions, product design, and technical implementation ultimately lands on the agent.