About ContextStream

Let humans
be human.

AI was supposed to give us time back. We’re building ContextStream so more of that time goes to creating, connecting, and deciding what matters.

Why we’re building this

Our story

We were tired of repeating ourselves.

After 18 years of building and shipping software, we kept running into the same problem. Every new AI session started with another briefing: the stack, the architecture, the decisions we had already made, and the lessons we had already learned.

First the file. Then the dependency. Then the reason we built it that way. We were spending 10 to 15 minutes getting an assistant up to speed before the actual work could begin.

The same thing happened between people. A teammate would join a project and have to piece together its history from old messages, outdated docs, and whoever happened to be available.

So we built the context engine we wished we had. A way for the project’s code, history, decisions, and lessons to stay connected and reach the person or agent doing the work.

The future we’re building toward

The project should remember.The agent should act.The human should decide what matters.

Humans should spend their best hours exercising judgment, building relationships, and creating things that matter. Agents should carry the context forward and do the digital work that follows.

Today, that begins with software projects. Our destination is a trusted context engine connected across applications, helping agents act with continuity while people decide what matters.

What we believe

Context comes with responsibility.

Relevance over volume.
A larger context window is temporary working space. What matters is finding the code, decision, constraint, or lesson that helps with this task, and showing where it came from.
Context belongs to the work.
What a project knows should remain useful when a session ends, a teammate joins, or an agent changes. Decisions and lessons should travel with the work, across tools and time.
Trust is part of the foundation.
The right context must reach the right agent, for the right purpose, with the right permissions. Capable agents need clear boundaries and a place for human judgment.

How we got here

We built the context engine first.

Every step since has been about making that context more useful to the people and agents doing the work.

  1. 2024

    The breaking point

    After 18 years of shipping software, we were spending the start of every session explaining the same architecture, decisions, and patterns. We wanted that time back.

  2. 2025

    We built the context engine

    A context layer that captures project decisions, connects them to code, and brings the relevant context into the tools we already use through MCP.

  3. 2025 to 2026

    The project became connected

    Decisions, lessons, documents, tasks, and code came together in a knowledge graph. The work was no longer scattered across isolated conversations.

  4. Today

    Context for capable agents

    Precise code search and recall, decision learning, and live agent orchestration and coordination. Built for individual developers and teams working across projects and tools.

The person behind it

Erik, founder.

Find me on LinkedIn

I’ve spent 18 years building software across early-stage startups and growing teams. ContextStream started with a problem I was living with every day. It’s still the product I use to build.

We’re bootstrapped, building alongside individual developers and paying teams. The ambition is bigger than a better coding session. I want a future where software asks less of our attention, and gives us more room to be human.

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