2026 RYEOWOOK'S AGIT CONCERT : DIVE TO BLUE in TAIPEI How to get the DIGITAL STAMP in the SMTOWN APP! 🗓️DATE: 2026.07.31 (FRI) – 2026.08.01 (SAT) | 09:00~23:50 (CST) 📍LOCATION: Within 500m from LEGACY TERA 💙METHOD: SMTOWN APP - PASSPORT - Click ‘STAMP’ button 🔗DOWNLOAD: #슈퍼주니어# #SUPERJUNIOR# #려욱# #RYEOWOOK# #AGIT_CONCERT# #DIVE_TO_BLUE#

Poster & VCR Shooting Behind | Ep.1 | 2026 RYEOWOOK'S AGIT CONCERT : DIVE TO BLUE in SEOUL #슈퍼주니어# #SUPERJUNIOR# #려욱# #RYEOWOOK# #AGIT_CONCERT# #DIVE_TO_BLUE#

Harness Engineering Practices P12. Semantic Circuit Breakers and "Discard Context" Restarts 🎯 Point Ever seen an agent repeat the same error three times? "Push through" is far slower than "restart with a lesson learned." 📝 Overview Instead of simple max-iteration limits, semantically detect "same error twice," "oscillating between two edits," or "no net progress" and halt. When stuck, don't keep kneading in contaminated context. Roll back to the last good checkpoint, discard failure history from context, carry just a one-line lesson, and restart with a fresh approach. 🔍 Explanation When an agent gets stuck, the least efficient response is "try harder in the same context." As failure history accumulates in context, the agent gets dragged toward repeating the same mistakes. Semantic circuit breakers judge "is there actual progress" rather than counting iterations. When they detect oscillation (change A to B then back to A) or repeated identical errors, they trigger a git rollback to the last clean state, then restart in fresh context with only "last time X failed, try a different approach." Git is the agent's Undo. 🛠 How to Practice - Implement logic in the harness that compares error messages and test results to detect "same error twice" and "A-B edit oscillation" - On halt, git checkout to the last clean commit and discard contaminated context - On restart, carry only a one-line lesson ("last time X failed") into the fresh context - Tune circuit breaker thresholds per task difficulty (strict for easy tasks, more lenient for hard ones) 💼 Use Cases - Issue-to-PR agents looping on the same test failure they can't fix - Compile error fixing: detecting fix-then-break-then-revert cycles - Legacy code modernization: recognizing when a fundamentally different approach is needed ⚠ Pitfalls Too-sensitive circuit breakers cut off agents one step from a solution. Too-lenient ones waste cost in infinite loops. Tuning the definition of "progress" per task is critical. Distilling accurate lessons at restart time is also hard — wrong lessons carried into a restart can trigger different failure patterns. #HarnessEngineering# #AIAgent#

I am building my own coding harness. Yemrecode. Building upon the opensource codebase of OpenCode. My harness has a completely different approach than others: - I pick multiple LLMs at once and the harness will treat them as one single entity. - I set a /yunus-goal and this goal is controlled by agents where some are responsible for demanding proof and some are implementors. - I can run a swarm of various LLMs meanwhile pursuing a yunus-goal with each having their own swarm. - I can toggle YOLO mode anytime and regardless of its state, the agents will never be able to alter Yemrecode. Many more abilities. Including: Automatic anti-ai-slop controller that detects slop UI/UX design and prevents it from being added to code and demands that specific agent to remake it properly. Path detector works similarly but for detecting the intent of the agent when it tries to write to a wrong path. There is also a version control system that auto inits a git repo when code length in the folder exceeds a thousand lines in total (indicating we may want to track the changes as this may not be a one time trial and junk code). many other abilities coming soon. I am not publishing my harness yet, but after a few months of testing I may do that.