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Some 2025 takeaways in LLMs: reasoning as a signature feature, coding agents were useful, subscriptions hit $200/month, and Chinese open-weight models impressed

This is the third in my annual series reviewing everything that happened in the LLM space over the past 12 months.

Simon Willison's Weblog Simon Willison

Context & Ripple Effects

The prior year’s review described multimodal vision becoming routine while model prices fell; this year’s account shifts the emphasis from broad capability access to differentiated reasoning, agent usefulness and premium service tiers. A separate year-end review likewise identified Claude Code as an early convincing agent example, reinforcing that coding had become a practical test case rather than merely a demo category.

Earlier coverage noted that LLM-assisted coding could be difficult and unintuitive, even as it exposed new ways to explore models’ capabilities. The reported usefulness of coding agents suggests that those hands-on coding experiments matured into a more consequential product benchmark, while impressive Chinese open-weight models broadened the set of credible model sources.

First-order effects

  • Developers and teams evaluating LLM tools now have stronger evidence to assess reasoning and coding-agent performance as distinct product capabilities, rather than treating chat quality as the sole criterion.
  • Providers can support higher-priced subscription tiers where users perceive agentic coding and reasoning workflows as materially useful; Chinese open-weight model makers gain visibility as credible alternatives.

Second-order effects

  • Closed-model vendors face pressure to justify premium plans through measurable workflow value, while open-weight models give developers more options for balancing capability, control and operating cost.
  • Coding-tool vendors and enterprise buyers will increasingly compare products by the cost and reliability of completed tasks, not just model access—an instance of lessons from real-world LLM application building.

Third-order effects

  • If useful agents continue to concentrate value in repeatable work, LLM competition may shift from generic model subscriptions toward integrated workflow products and the infrastructure that runs them.
  • The combination of premium hosted tiers and capable open-weight alternatives could make inference economics and distribution—not raw model availability alone—more decisive sources of market power.

The trend: LLMs are moving from broadly accessible conversational models toward a segmented market where reasoning, agents, deployment choice and cost per useful task determine adoption.

Discussion

  • @carnage4life Dare Obasanjo on bluesky
    Simon Willison has a great summary of LLM progress in 2025:  —  • Reasoning models have made LLMs useful for web search.  —  • AI agents now work well for Deep Research and Coding.  —  • AI image generation went mainstream.  —  • Vibe coding became a big business. …
  • @mikehadlow.com Mike Hadlow on bluesky
    Enjoyed @simonwillison.net 's wrap up of the year in AI.  His is probably my favourite developer-focussed AI blog.  Definitely worth a regular read:  —  simonwillison.net/2025/Dec/31/ ...
  • @jeremymorrell.dev Jeremy Morrell on bluesky
    I'm glad Simon puts these together.  It's honestly hard to believe how much things have changed in just a year [embedded post]
  • @simonwillison.net Simon Willison on bluesky
    Here's my enormous round-up of everything we learned about LLMs in 2025 - the third in my annual series of reviews of the past twelve months  —  simonwillison.net/2025/Dec/31/ ...  This year it's divided into 26 sections!  This is the table of contents: [image]