The GPT-5 Breakthrough in AgentOne: Scale Meets Privacy

Shomron Jacob, Head of Applied Machine Learning and Platform
September 16, 2025

A Milestone in Enterprise AI Development

With the release of AgentOne 8.5, enterprises now have access to something the industry has been waiting for: a coding assistant that combines the unprecedented power of GPT-5 with the strict security and privacy requirements of enterprise environments.

AgentOne isn’t just another AI assistant that helps autocomplete code. It is the first enterprise-ready platform to fully integrate GPT-5, delivering scale, flexibility, and compliance in ways that competitors simply cannot match. For organizations building and maintaining massive, complex software systems, this represents a fundamental shift.

Unprecedented Context with GPT-5

At the heart of this breakthrough is GPT-5’s ~2 million token context window—a leap forward in memory and reasoning ability.

To put that into perspective, most current coding assistants, including Windsurf, Cursor, and Cline, max out at 32K–128K tokens. That’s enough to handle small projects or snippets of a codebase, but nowhere near enough for enterprise-scale applications.

With AgentOne powered by GPT-5, enterprises can now:

  • Load and process 500,000+ lines of code in a single session
  • Understand and maintain entire application architectures at once
  • Preserve dependencies, naming conventions, and design patterns without context breaks
  • Enable true multi-step planning and execution without developers constantly re-prompting the AI

This level of context transforms the assistant from a reactive tool into a strategic coding agent that sees the bigger picture, understands the entire system, and supports developers in long-running, complex workflows.

Choice of Models Based on Security Profile

Every enterprise operates under different regulatory, compliance, and performance requirements. A one-size-fits-all AI solution doesn’t work. That’s why AgentOne was designed with model flexibility at its core.

Developers and IT teams can select the model that best fits their use case:

  • GPT-5 — Maximum reasoning ability and the industry’s largest context window (~2M tokens).
  • GPT-5 Mini (512K tokens) — Optimized for rapid prototyping, iteration, and faster turnaround tasks.
  • Anthropic Claude 4 (200K tokens) — Private deployments via AWS Bedrock for organizations prioritizing compliance with cloud security standards.
  • Local LLMs — Iterate-tuned models running fully inside the enterprise firewall, offering OpenAI-style API compatibility while ensuring no data ever leaves the organization.

This flexibility means enterprises never have to choose between power and privacy. They can match the right model to the right project, scaling securely across diverse environments.

Seamless Model Switching

AgentOne goes beyond static model selection. It enables dynamic model switching within workflows.

For example, a development team might start with GPT-5 Mini for early-stage iteration, switch to GPT-5 for scaling across the full codebase, and then deploy with a local LLM to meet compliance requirements.

This fluid movement between models ensures enterprises can balance speed, cost, and security without trade-offs—something competitors cannot offer today.

Market Response

The market’s reaction has been immediate and telling. At our most recent webinar showcasing AgentOne’s GPT-5 integration, registrations included leaders from United Airlines, Foot Locker, RE/MAX, The Motley Fool, Amazon, Microsoft, Meta, Blackstone, UCHealth, Rippling, Nielsen, and even Chamath Palihapitiya of the All-In Podcast.

This mix of enterprises, technology giants, financial institutions, and thought leaders highlights one thing: organizations are actively seeking enterprise-grade coding agents that marry scale with privacy.

The takeaway is clear: AgentOne 7.8 isn’t just an upgrade—it’s a redefinition of what enterprise AI development can be.

Frequently Asked Questions

Q: What’s the difference between a 32K and 2M token context window?
A: A 32K token window (~24,000 words) can only handle a fraction of a project. By contrast, a 2M token window (~1.5M words) enables reasoning across an entire application architecture, including 500K+ lines of code, dependencies, and documentation—all in one coherent view.

Q: Does AgentOne only use GPT-5?
A: No. AgentOne offers a portfolio of models: GPT-5 for maximum scale, GPT-5 Mini for rapid iteration, Anthropic Claude 4 for secure Bedrock deployments, and Iterate-tuned local LLMs for fully private, firewall-contained use cases.

Q: How does AgentOne preserve context across long sessions?
A: AgentOne uses a proprietary Context Preservation Engine that captures key changes, dependencies, and decisions across sessions. Developers don’t need to re-prompt or re-explain—the AI remembers and adapts.

Q: Why can’t other coding assistants handle this scale?
A: Competitors like Windsurf, Cursor, and Cline remain capped at 32K–128K tokens. They lack the context depth, summarization, and compression techniques that AgentOne employs to maintain accuracy across massive, enterprise-scale codebases.

The Future of Enterprise AI Development

With AgentOne 7.8, enterprises don’t have to compromise between scale, speed, and security. By combining the unprecedented memory of GPT-5 with flexible model selection and enterprise-grade privacy, AgentOne sets a new benchmark for what coding assistants can achieve.

For organizations managing large, complex applications, this isn’t just an incremental improvement—it’s the foundation of a new era in agentic AI development.

Learn more about AgentOne