@davepband@jetbrains Unfortunately, I can't reveal any non-public plans. Just for your consideration: you may continue using your IDE with an ACP agent paid through a frontier lab subscription if you find more value there.
@davepband@jetbrains We also have made additional steps to improve the value for individual users and small teams during the transition by offering Junie Lite for free to all users. It’s powered by a model capable of taking care of a lot of daily tasks. have a look
@davepband@jetbrains Speaking on behalf of JetBrains Air, sorry to hear this change has disappointed you @davepband.
This product change has improved the value most companies get from JetBrains Air by making AI credits more longlasting and interchangeable between team members.
@davepband@jetbrains As part of the change we have discontinued some legacy discounting policies that were no longer sustainable in the current reality. Unfortunately, this is the part that seems to have affected you most.
Code review is one of the Air Teams automations we use most internally.
Ours reviews every push, tracks which findings you fixed, and collapses old comments so you only see the latest.
Oh, and you can argue with it too. Explain why a fix can wait, and it accepts that.
Meet JetBrains Air Teams.
Agentic workflows used to live on one developer's laptop. We built Air Teams to change that: you configure a workflow once, and the whole team can run, validate, and improve it.
1/4
@pwendell@databricks Surprised to see such a limited impact of context optimisation. Have you tried codebase search as an extra improvement?
For us at JetBrains and for our early adopters works exceptionally well on large code bases - up to 48%.
See here
https://t.co/9dmedhivzj
Our Anthropic bill is about to jump from $400K → $1.4M/yr.
Not because usage exploded, but because we're about to cross 150 seats.
Past 150 seats you're forced into Enterprise tier. Seats stop including any usage, every token bills at standard API rates. At our current run rate that's 3.5x overnight.
Unfiltered thoughts on AI spend:
1. We should spend tokens to grow as aggressively as possible. But most people (me included) aren't conscious of what they're spending.
2. Visibility comes first. People see their personal number and they're shocked. I accidentally spent $4,000 in 3 days in Claude Code.
3. For engineering the spend is clearly worth it. Pay for the best model, it saves more than it costs.
4. For a lot of other roles it's questionable. Apps nobody uses, skills someone already built. No ROI.
5. Spend limits are coming. We already require approval for more tokens on our support team.
The era of token-maxxing is coming to an end.
Mellum started with code completion.
Mellum2 is built for more – handling both natural language and code.
A 12B-parameter open-source LLM for routing, RAG, and sub-agents, optimized for ultra-low-latency inference.
Now on @huggingface.
Learn more: https://t.co/28sG8Ql52L
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