Do you need to fine-tune a model?
Habib says Writer's models spare customers fine-tuning. Srinivasan says most open-model use cases she sees involve fine-tuning.
One view
Not for Writer customers: its domain-specific models capture the business logic from examples without fine-tuning.
May Habib, Writer EP 1 · The State of AI: Open-Source Models & Enterprise Trust | May HabibAnd so the customer doesn't need to fine tune to get the kind of accuracy.
The other
Most open-model use cases Srinivasan sees involve fine-tuning rather than running them out of the box.
Aishwarya Srinivasan, Fireworks AI EP 42 · Architecting AI Agents: The Shift from Models to Systems | Aishwarya Srinivasanmost of the use cases when I'm seeing enterprises or startups use these open source models, they are not using it out of the box. They are either like using supervised fine tuning methods to fine tune it or reinforcement learning fine tuning
EP 1 was published November 6, 2024; EP 42 was published October 8, 2025. Habib is describing Writer customers using its domain-specific models, and Srinivasan is describing enterprises and startups building on open source models. Both can be true: whether you fine-tune depends on whether a model is already close to your use case.
Beyond the podcast
Both guests describe what they see from their own platforms. Habib speaks for Writer, which sells preconfigured domain-specific models, and says capturing business logic with examples takes less data than fine-tuning appropriately (42:16). Srinivasan speaks for Fireworks AI, which hosts and fine-tunes open models, and describes Notion fine-tuning models where it could not get the latency and response quality it needed from proprietary models (35:19). Read both as positions from vendors.
Fine-tuning vs. RAG vs. prompting walks through when each approach fits, and open vs. proprietary AI models covers the model choice underneath this question.
Disclosure: Episode 1 was sponsored by Galileo, where Conor then worked; he introduces himself as Galileo's head of developer awareness at 0:08.
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- Where do AI agent frameworks add value? Two founders emphasize different parts of the problem: operating the agent stack and improving the context it uses. These positions can coexist.
- Should AI companies build in the open? One guest hopes more companies take an open source route with AI. Another believes in open source but says it is hard to turn into a profitable business.