OpenAI's Codex and GPT-4.1, Y Combinator, Anthropic & Windsurf updates

Good morning! Welcome to your Monday edition of First AI Movers—your daily roundup of the most significant developments in artificial intelligence. Let's dive into last week's top stories.

Y Combinator Sees a New Wave of AI Tools Coming

Y Combinator’s Dalton Caldwell is sounding the horn on a looming surge of AI innovation. Caldwell noted that recent AI breakthroughs have “unlocked a wave of new startup opportunities” – meaning we’re about to see a flood of new AI tools and companies tackling ideas that were impossible just months ago. In YC’s latest Requests for Startups, he highlights how AI agents can now control computers (via tools like Operator), and new “reasoning” models can even match or surpass human problem-solving. The message: an AI gold rush of novel applications is inbound, so buckle up.

Anthropic’s Claude Goes Sonnet and Opus

Anthropic is reportedly preparing to launch two advanced Claude models – codenamed Claude Sonnet and Claude Opus – in the coming weeks. What’s special? These models can switch into deep “reasoning” mode whenever they get stuck, essentially pausing to think harder before using external tools or data. It’s a dynamic one-two punch: if a straightforward answer doesn’t work, Sonnet and Opus will seamlessly flip between heavy internal reasoning and calling on outside apps or databases to crack the problem. This hybrid approach aims to push Claude’s capabilities even closer to GPT-4 territory. Anthropic’s focus on reasoning loops and tool use underscores the industry’s shift toward “smarter,” not just larger, AI.

Windsurf Enters the Frontier with SWE-1 (…and Hints of SUI-1)

In a surprise move, vibe-coding startup Windsurf rolled out its own AI models last week, unveiling SWE-1, a family of AI co-pilots built by and for software engineers. The largest model, SWE-1 (with “lite” and “mini” variants), is optimized for the entire software development lifecycle – not just code completion, but jumping between IDE, terminal, and web to handle real dev workflows. Windsurf claims SWE-1’s performance rivals OpenAI’s and Anthropic’s mid-tier offerings: internal tests showed SWE-1 holding its own against Claude 3.5 Sonnet and OpenAI’s GPT-4.1 on coding tasks. (That said, it does fall short of the latest frontier models like Claude 3.7 Sonnet). Perhaps most telling: this launch comes right as rumors swirl that OpenAI is acquiring Windsurf, suggesting the team wanted to prove they can build top-tier models too. Windsurf also hinted at an experimental next step dubbed “SUI-1” – a concept model geared toward handling long-running, multi-surface engineering tasks via the platform’s “flow awareness” approach (the same tech that lets Windsurf’s AI track incomplete work across tools). While details on SUI-1 are sparse, it’s clear Windsurf plans to double down on AI that can follow developers through an entire project, not just spit out code in one file.

OpenAI Launches Codex – Your Autonomous Coding Buddy

Not to be outdone, OpenAI dropped a major update for developers: Codex, an AI coding agent that lives inside ChatGPT. Unlike a normal chatbot, Codex can actually write, execute, and test code autonomously – essentially a tireless junior developer in the cloud. It spins up a sandboxed cloud developer environment that can even preload your GitHub repositories. You can assign it multiple tasks in parallel, and it will merrily chug away for up to 30 minutes on each, building features, squashing bugs, or answering questions about your codebase. OpenAI’s AI agents lead described Codex as a “virtual teammate” meant to tackle tasks that normally take human engineers hours or days. Early users (ChatGPT Pro, Team, and Enterprise customers get first dibs) can queue up several coding to-dos and watch Codex handle them simultaneously. The goal is clear: bring agentic coding mainstream. OpenAI’s not alone here – Anthropic’s Claude has a coding mode, and Google’s Gemini is beefing up its Code Assist – but Codex is OpenAI’s most assertive step yet toward AI that doesn’t just suggest code, it builds entire solutions on its own.

GPT-4.1 Lands in ChatGPT – Faster, Smarter, and Stirring Debate

Last week, OpenAI’s flagship GPT-4.1 model finally hit ChatGPT, and user reactions are rolling in. For Plus and Pro subscribers, ChatGPT now defaults to GPT-4.1 – a model tuned especially for coding and complex instructions. Many users immediately noticed ChatGPT feeling “sharper, faster, and more capable” across the board. GPT-4.1 delivers answers with improved reasoning, better code generation, and a memory window up to 1 million tokens (beating the previous 128k limit by a mile). Even free users benefit: the older GPT-4o mini has been swapped out for a GPT-4.1 mini model, giving everyone a taste of the upgrade. OpenAI touts GPT-4.1 as not just more powerful but also more practical – it’s faster and thus “more appealing for everyday coding tasks” than some of their specialized reasoning models. However, the rollout hasn’t been without controversy. With GPT-4.1 (and its mini version) joining the lineup, some paying users now see nine different model options in ChatGPT, prompting complaints about a confusing model zoo. OpenAI’s rapid model iterations (GPT-4.5 came and went; now 4.1 is the new hotness) have left some folks’ heads spinning. Still, the consensus among devs is that GPT-4.1 greatly improves quality and speed, so most are happy to trade a little confusion for better results.

Meta’s LLaMA 4 “Behemoth” Delayed Amid Internal Strife

Meta’s grand plan to leapfrog the AI pack hit a snag: the company has indefinitely delayed the public release of its next big model, LLaMA 4, nicknamed “Behemoth”. Originally slated for an unveiling at April’s LlamaCon, Behemoth’s launch was first bumped to June and now is pushed to fall 2025 or later. Why the holdup? According to insiders, Behemoth just isn’t delivering a big enough performance jump over its predecessor. Meta’s top brass is reportedly not pleased – there’s mounting frustration and “tension” between leadership and the LLaMA 4 development team over the lack of progress. In fact, a shake-up of Meta’s AI unit is on the table if the team can’t break through the current plateau. The broader context here is an industry reality check. For years, the playbook was “just scale up,” but we may be hitting the wall on giant models. OpenAI has famously struggled to ship a true GPT-5 and instead pivoted to multiple specialized models, and Google/Anthropic have also run into setbacks training their largest systems. Meta’s Behemoth delay underscores that bigger isn’t always better, and even the AI giants are rethinking their approach. (It probably doesn’t help Meta’s mood that they boasted early on that Behemoth would outdo GPT-4 – a claim that now looks premature). The takeaway: expect Meta to go back to the drawing board and possibly explore the kind of hybrid reasoning techniques others are chasing, rather than simply scaling up parameter counts.

Cohere’s Enterprise Pivot Pays Off – $100M and Counting