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Home » Reload wants to provide shared memory to AI agents
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Reload wants to provide shared memory to AI agents

Bussiness InsightsBy Bussiness InsightsFebruary 19, 2026No Comments4 Mins Read
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Newton Asare realized that AI agents are no longer just tools. “They were acting like teammates,” he told TechCrunch.

This realization crystallized when Serial founders Asare and Kiran Das realized they were using AI agents to perform tasks they would normally do themselves. Asare said he has come to believe that the future lies in people managing AI employees.

“And if that is true, we will need a real system for managing digital workers, with structures around onboarding, coordination, and monitoring of digital workers,” he added.

Last year, the duo launched Reload, an AI workforce management platform. On Thursday, the company announced its first AI product, Epic, and a $2.275 million round led by Anthemis with participation from Zeal Capital Partners, Plug and Play, Cohen Circle, Blueprint, and Axiom.

Reload is a platform that enables organizations to manage AI agents across teams and departments. Enterprises can connect agents, assign roles and permissions to them, and track the work they perform, regardless of who built them (third-party or in-house). “Reload acts like a system of record for the AI ​​workforce, providing visibility, coordination, and oversight as agents work across multiple departments,” said CEO Asare.

He said his team now uses multiple agents simultaneously for tasks such as coding, debugging, and refactoring. The problem is that these agents are often focused only on what they are told to do and do not necessarily maintain long-term memory about what the product is or why they were told to perform a certain function. In other words, they operate only on short-term memory.

Over time, agents can lose context or systems can evolve away from their original intent. That’s why Reload is launching Epic. Built on the Reload platform, it acts as an architect alongside other coding agents, continuously defining the requirements and constraints of the product, and reminding agents what they’re building and why they’re building it to keep the systems they’re developing consistent.

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“Especially in software development, coding agents can generate large amounts of code, but cannot maintain a shared understanding of the system over time,” Asare says. “Epic complements these agents by predefining the system and maintaining a shared context as it evolves. Rather than replacing coding agents, it makes agents more efficient.”

Epic is designed to work within the coding environment that developers are already working in. It can be installed as an extension to AI-assisted code editors such as Cursor and Windsurf, and can run alongside other agents within those tools.

“When teams start a project, Epic helps them create core system artifacts such as product requirements, data models, API specifications, technology stack decisions, diagrams, and structured task breakdowns,” Asare said, adding that these are the foundations that coding agents build on.

“Epic maintains a structured memory of decisions, code changes, and patterns as development progresses,” he continued. “When you switch coding agents, structure and memory follow. When multiple engineers use different agents on the same project, they are all building from the same shared source of truth.”

Asare and Das previously ran a company together, but it was acquired and this is their second company together.

The AI ​​infrastructure space is crowded. Competitors include LongChain, which helps AI agent deployment and memory management, and CrewAI, which helps enterprises manage AI agents.

Das said Epic is unique because it focuses on building the infrastructure to maintain an AI workforce, especially because it “predefines systems and maintains project-level context that is shared across agents and sessions.” “Traditional workforce systems were not designed for AI agents acting as teammates,” said Das, the company’s CTO. “That’s the demographic we’re focusing on.”

The new funding will go towards jobs and product advancements, especially the infrastructure expansion needed to support the growing number of AI agents. “We are building for the next era of work,” Asare said.

This part has been updated to add other investors to the round.



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