Desperate pivot aside, I don't see how anyone competes with the big labs on coding agents. They can serve the models at a fraction of the API cost, can trivially add post training to fill gaps and have way deeper enterprise penetration.

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pjjpo 3 hours ago | parent | next [-]

Don't need to compete - demonstrate some ability to use AI in an easy to understand way, get bought out at valuation. Bad for investors, awesome for founders.

Reference: Browser Company

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ianbutler 5 days ago | parent | prev | next [-]

Specialization into specific parts of the life cycle, specific technologies and integration into specific systems.

Things like self hosting and data privacy, model optionality too.

Plenty of companies still don’t want to ship their code, agreement or not over to these vendors or be locked into their specific model.

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oceanplexian 5 days ago | parent | prev | next [-]

I feel like it's totally the opposite.

The differentiator is the fact that the scaling myth was a lie. The GPT-5 flop should make that obvious enough. These guys are spending billions and can't make the models show more than a few % improvement. You need to actually innovate, e.g. tricks like MoE, tool calling, better cache utilization, concurrency, better prompting, CoT, data labeling, and so on.

Not two weeks ago some Chinese academics put out a paper called Deep Think With Confidence where they coaxed GPT-OSS-120B into thinking a little longer causing it to perform better on benchmarks than it did when OpenAI released it.

	▲	manquer 4 days ago \| parent [-]
		Scaling inference not training is what OP means I believe . The smaller startups like cursor or windsurf are not competing on foundational model development. So whether new models are generationally better is not relevant to them. A cursor is competing with Claude code and both use Claude Sonnet. Even if Cursor was running a on par model on their own GPUs their inference costs will not as cheap as those of Anthropic just because they would not be operating at the same scale . Larger DCs means better deals, more knowledge about running an inference better because they are also doing much larger training runs.

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4 days ago | parent | prev | next [-]

[deleted]

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kristopolous 5 days ago | parent | prev [-]

I've pitched people working there this multiple times. Warp is not just a terminal, it's a full stack of interaction, they have more of the vertical of the development cycle to leverage.

You need different relationships at different parts of coding, ideation, debugging, testing, etc. Cleverly sharing context while maintaining different flows and respecting the relationship hygiene is the key. Most of the vscode extensions now do this with various system prompt selections of different "personas".

I used to (6 months ago) compare these agentic systems basically as if they were John Wayne as contract programmer, parachuting in a project, firing off their pistol, shooting the criminals, mayor, and burning the barn down all the while you're yelling at it to behave better.

There's contexts and places where this can be more productive. Warp is one of them if executed with clean semantic perimeters. It's in a rather strong positioning for it and an obvious loyalty builder

	▲	orangebread 4 days ago \| parent [-]
		What's your strategy, technique, or rules you setup?