The primary bottleneck to achieving AGI is the speed of human validation and typing, not compute power or model architecture.
The most effective way for AI agents to interact with and control computers is by writing code, which is why coding agents have achieved product-market fit while others have lagged.
AI tools like Codex will increase the demand for software engineers over the next five years, shifting their role from writing code to reviewing AI-generated code.
OpenAI's core competitive advantages are its superior compute infrastructure and its ability to produce the best models, which it leverages by providing API access even to direct competitors.
The most significant opportunity for new startups is building vertical AI applications for specific, underserved customer segments rather than competing on foundation models.
August 2023
A period of rapid user adoption for OpenAI's Codex product begins, leading to 20x growth over the following months.
December 2023
OpenAI releases GPT 5.2 Codex, which Embirikos identifies as a key inflection point where developers shifted from pair-programming with the AI to fully delegating tasks to it.
Late 2023
The user base for the Codex product is reported to have grown by a factor of 20 since August.
Recent Period
OpenAI ships multiple model and infrastructure updates, including GPT 5.1 Codex Max and API optimizations that increased model serving speed by 25-40%.
Present
Embirikos states that coding agents are the only AI tool with clear product-market fit, while progress in non-coding and multimodal domains has been slower than expected.
2026 (Projected)
Embirikos anticipates this will be the 'year of agents,' suggesting a significant leap in the capabilities and adoption of agentic AI.
▶The AI-Driven Transformation of Software EngineeringFeb 2026
Embirikos details a fundamental shift in software development, driven by tools like Codex. He claims developers at OpenAI are moving from pair-programming with AI to fully delegating tasks, often bypassing traditional IDEs, and that the vast majority of code is now AI-written and AI-reviewed.
This suggests a future where engineering value shifts from implementation skill to problem decomposition and rigorous validation, potentially creating a new class of 'AI-augmented' senior engineers and altering how talent is evaluated.
▶OpenAI's Vertically Integrated Product EcosystemFeb 2026
The claims outline OpenAI's strategy of building both foundational models (Codex) and end-user applications (Atlas browser, Sora app) that leverage them. This ecosystem is designed for high user stickiness through integrations and is supported by a business model that includes providing API access to competitors, confident in its superior models and compute.
OpenAI is not just a model provider but is building a full stack, from infrastructure to applications, aiming to control key distribution points like the browser to ensure its agents have a secure and effective environment to operate in.
▶The Primacy of Code in Agentic AIFeb 2026
Embirikos posits that writing code is the most effective method for AI agents to interact with computers, which explains why coding agents are the only ones to achieve product-market fit. This belief underpins OpenAI's development of tools like the Atlas browser and OS-level sandboxing for Windows, creating controlled environments where code-writing agents can operate safely.
This 'code-first' philosophy suggests that progress in general-purpose AI assistants may be gated by the ability to translate any user intent into executable code, making the security of these code-executing environments a critical battleground.
▶Redefining the Bottlenecks to AGI
Embirikos challenges the common narrative that compute is the main obstacle to AGI. He argues the true bottleneck is the slow speed of human feedback, typing, and validation, as the models need vast amounts of high-quality, human-verified data to improve.
For investors, this perspective implies that the most valuable long-term investments in the AI space may not be in raw compute, but in companies developing novel human-computer interaction paradigms that can dramatically accelerate the human feedback loop.