MIT and Sakana AI's SIFT finishes a coding agent's self-improvement search on about $34 of API calls
MIT and Sakana AI's SIFT ran a coding agent's full self-improvement search on roughly $34 of API calls, about a tenth of the Darwin Godel Machine's resources. The saving comes from a language-model judge screening patches, so it holds only while that judge picks correctly.
Reality
- Evidence40
- Adoption
- Not scored
- Hype gap+25
- Incentives
- Not scored
- Confidence45
buildConfirmed3 publishers Specific Labs scores coding agents on licensed production codebases. The best setup clears 38.8%. The analysis covers ten tasks at eight runs each, so every published score is a count of passing rollouts out of 80.
Perspective Coverage
3 publishers
- Builder
- Builder 52%
- Operator
- Operator 33%
- Investor
- Investor 15%
Reality
- Evidence48
- Adoption
- Not scored
- Hype gap+30
- Incentives70
- Confidence58
Antigravity gives away five frontier models on a quota Google keeps trimming
Antigravity's free tier includes Gemini 3.1 Pro and Claude Opus 4.6 with unlimited tab completions. XDA reports Opus burns credits about four times faster than Gemini, and Google moved the free tier onto credits in March 2026.
Reality
- Evidence36
- Adoption
- Not scored
- Hype gap+12
- Incentives58
- Confidence40
buildOne report1 publisher JetBrains ships a 50/50 weight average of two Qwen checkpoints in Junie Local
The merged 27B finished 37 of 100 internal coding tasks against 34 for the fast checkpoint and 39 for the reasoning one, and it did that while emitting 71% fewer output tokens than the 39, with no post-training in the recipe.
Reality
- Evidence55
- Adoption30
- Hype gap+18
- Incentives78
- Confidence58
buildOne report1 publisher Alibaba's Open Code Review hands file picking and line positioning back to deterministic code
Alibaba ran the reviewer internally for two years across tens of thousands of developers before releasing it. The write-up is specific about how files get selected and comments get positioned, and it stops short of publishing the benchmark scores.
Reality
- Evidence32
- Adoption30
- Hype gap+55
- Incentives68
- Confidence38
buildOne report1 publisher JetBrains' Kotlin leaderboard prices the same 86 solved tasks at 3.7x apart
The Kotlin Benchmark grades agents on 105 verified repository tasks. Its token column shows setups that solve within a few tasks of each other burning between 66,000 and 777,000 tokens per fix.
Reality
- Evidence62
- Adoption30
- Hype gap+22
- Incentives60
- Confidence58
buildOne report1 publisher A refactoring benchmark stops the best agent at 41.2%, and the tests are the story
SWE-Bench ProMax puts frontier coding agents on 170 curated refactoring commits. The number that should move procurement is a different one: nearly 60% of unsolved SWE-bench Verified tasks have flawed tests.
Reality
- Evidence38
- Adoption14
- Hype gap+12
- Incentives62
- Confidence42
A Government Switched Off Two Frontier Models. Your Board Will Want The Fallback Plan.
A June 13 Commerce Department order cut non-US users off from two Anthropic models overnight, and OpenAI followed with limits of its own. Model access is now a sovereign risk, not a vendor term.
Reality
- Evidence22
- Adoption20
- Hype gap+45
- Incentives68
- Confidence30