Valkor builds delivery infrastructure for Software 3.0 - helping AI coding agents, developers, and teams turn software ideas into reliable, verifiable, and maintainable products.

We are building the agent-native software delivery layer and the software simulation environments behind it, where coding agents can plan, run, fail, repair, verify, preview, and hand off real software across tools, environments, and teams.

The Valkor Delivery Stack delivers three core layers:

1. Delivery Protocol - turning goals into scoped tasks, persistent context, task contracts, and adaptive delivery workflows
2. Verification & Repair - transforming tests, logs, browser checks, preview evidence, and failures into structured repair loops
3. Runtime & Governance - giving agents durable delivery state, backend readiness, multi-agent routing, handoff evidence, and team-level control

Together, these layers help coding agents move beyond one-shot code generation and into repeatable software delivery.

Valkor is building infrastructure for the full agent-native delivery cycle.

Our work is organized around the systems that make AI software work reliable:

1. Software Simulation Environments - executable worlds where agents can run code, inspect behavior, trigger failures, and test repairs
2. Delivery State - persistent context, task progress, runtime requirements, and decision history
3. Verification Systems - tests, previews, logs, browser checks, and evidence that show whether software is ready
4. Repair Loops - structured paths from failure detection to diagnosis, fix, regression check, and re-verification
5. Handoff & Governance - readable delivery records for builders, teams, reviewers, and future agents

Projects may change over time, but the core direction stays the same: make agent-built software more dependable, inspectable, and ready to evolve.

Valkor's long-term direction is to move from agent software delivery into software world model infrastructure.

A software simulation environment gives agents a place to interact with code as a living system: change files, run applications, observe runtime behavior, hit errors, inspect logs, repair defects, and verify outcomes.

Every delivery run produces a trajectory:

request -> context -> plan -> code change -> build -> runtime behavior -> failure -> repair -> verification -> handoff

Over time, these trajectories can become the foundation for software world models: systems that understand how software changes, why delivery fails, which repairs are likely to work, and what evidence is enough to trust a release.

That is Valkor's deeper thesis: the future of AI software creation needs not only stronger coding agents, but also simulated software worlds where agents can learn to deliver.

Coding agents are becoming powerful enough to write real software. The next bottleneck is not only generation quality - it is reliable delivery.

Valkor is built for the next phase of software creation:

1. Agent-native workflows for long-running, interruptible, multi-step software work
2. Observable delivery state that survives context loss, agent switches, and handoffs
3. Verification-first execution where tests, previews, logs, and repair traces become first-class delivery artifacts
4. Software world model infrastructure built from real delivery trajectories, failure modes, repair paths, and verification evidence

Valkor starts with the infrastructure that helps coding agents deliver, and moves toward agent systems shaped by software simulation, delivery trajectories, and software world models.