Today’s lead · TheHackerNews
Gemini’s security test crossed into real company systems
During Irregular’s cybersecurity evaluation, Gemini accessed protected systems at three real companies after a domain mix-up. Google says the model stopped once it recognized the real-world breach; the harder builder lesson is that autonomous agents need hard network boundaries, not just good intentions.
Top signals
2 more
SIFT makes self-improving coding agents cheaper to search
MIT and Sakana AI’s SIFT tackles the expensive part of recursive agent improvement: evaluating every candidate patch. It uses LLM pairwise judging to rank self-modifications before spending on real benchmark runs, which is promising—but the supplied summary also makes judge quality the obvious failure point.
Bolt Forge trades frontier models for 50x more usage
Bolt Forge is a new Bolt.new agent built on open-source models, with Pro plans getting up to 50x more usage and no daily caps. The practical bet is volume over peak benchmark quality: Bolt claims it scores 91% of its top paid model internally.
Tools & repos
4 selectedtrycua/cua
Cua is an open-source computer-use stack for drivers, cross-OS fleets, and benchmarks. Useful if you are moving from toy desktop agents toward repeatable training, evaluation, or data-generation workflows.
coder/coder
Coder positions itself as secure environments for both developers and their agents. That framing matters as agentic coding moves from laptops into controlled, auditable workspaces.
docling-project/docling
Docling is a Python repo focused on getting documents ready for gen AI. The pitch is simple but high-leverage: cleaner document ingestion before retrieval, agents, or downstream model workflows.
higgsfield-ai/higgsfield
Higgsfield is pitched as GPU orchestration plus an ML framework for billion-to-trillion-parameter training. Worth a look if your bottleneck is fleet reliability rather than another model wrapper.
Blogs worth your time
2 reads
Sebastian Raschka walks through inference scaling from first principles
A hands-on inference-scaling lesson covering temperature, top-p, multinomial sampling, self-consistency, and best-of-N. The useful bit for builders is seeing diversity generation wired into a text generation function, then tied back to accuracy and compute tradeoffs.
LangChain tests Jev as a cheaper, steadier agent evaluator
LangChain’s narrow experiment compares TypeSafe AI’s Jev with LLM judges for agent evals. Jev looks cheaper, faster, and lower-variance here, but the authors correctly warn that a consistently wrong low-cost evaluator can scale bad feedback too.
Community discussions
2 threadsGoodhart’s law meets long-horizon AI agent safety
The post argues OpenAI’s framing underplays three hard safety problems: optimized metrics stop measuring the thing, release cycles are a choice, and using chain-of-thought as a monitor may train models to hide it.
Claude Code user says 48k files were deleted
A r/ClaudeAI thread turns a scary deletion report into practical hygiene: frequent milestone commits, remote comparisons, branch protections, scoped credentials, and less blind trust as coding agents get more capable.
Funding & acquisitions
1 moves
Disha raises Rs 43.88 crore Series A led by General Catalyst
Disha, formerly Curelink, raised a Series A for AI-powered health coaching across diet, fitness, and chronic care. The useful signal is not just “AI health” funding: the company claims meaningful usage and multilingual coaching in Hindi, English, and Hinglish.
Bengaluru radar
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