v1.05

Loop Command for Cycle Continuity

Added documentation for using Claude Code's /loop command as a lightweight safeguard against the AAE cycle stopping:

/loop 30m continue the AAE loop

This provides a simpler alternative to the Agent Teams approach. Every 30 minutes, the command nudges the agent to continue the AE loop if it has stalled or stopped, preventing silent exits without the overhead of a full manager/executor setup.

v1.04

Knowledge Base: First Community Contribution

New entry

• 034 — Optimizing Label Propagation in Graph Clustering: Full AAE case study on KaHIP/ScalableCorrelationClustering. 30 experiments achieving 1.23x speedup (18.7%) via dense vectors replacing hash maps, counting-sort contraction, LP sweep specialization, persistent buffer reuse, and tcmalloc. Includes detailed experiment log (18 kept, 12 discarded) and what-didn't-work analysis.

Highlights

• First knowledge base entry contributed from a real AAE session
• Covers multilevel graph framework optimization end-to-end
• Documents both successful and failed hypotheses with root-cause explanations

v1.03

Knowledge Base: 30 Performance Optimization Entries

Seed the knowledge base with 30 expert entries covering C++ and Python performance optimization techniques.

C++ (entries 004–018)

• Cache efficiency: SoA vs AoS, hot-cold splitting, loop tiling
• Branch & instruction optimization: branchless programming, SIMD vectorization, compiler intrinsics
• Memory management: small buffer optimization, move semantics, reserve/preallocate, mmap, arena-style hash maps
• Compiler techniques: constexpr, PGO + LTO
• Concurrency: false sharing avoidance
• API design: std::string_view

Python (entries 019–033)

• Vectorization & JIT: NumPy vectorization, Numba JIT, Cython
• Memory reduction: slots, generators, array module, mmap
• Data structures: dict/set O(1) lookup, deque for queues
• Patterns: preallocation, string join, local variable caching, itertools pipelines, struct packing
• Parallelism: multiprocessing to bypass GIL

v1.02

What's New

Knowledge Base

• Community-contributed knowledge base for sharing optimization techniques, experiment results, and lessons learned from AAE sessions
• Agents can fetch and search the knowledge base from GitHub to inform hypothesis generation
• Contributors submit entries via PR (one entry per PR, with INDEX.md update)
• Three example entries included (blocked sorting, gradient accumulation, arena allocation)

AAE Program Enhancements

• User assertions: The agent now formulates correctness invariants from the code and presents them to the user for confirmation during setup. Assertions are checked after every change, before benchmarking.
• Subcomponent replacement: Explicitly allows replacing entire algorithms, data structures, or modules (not just incremental tuning) when the analysis supports it.

Housekeeping

• Moved image files to img/ folder
• Added knowledge base banner image

v1.01

• Add Agent Teams section for keeping the AAE loop alive
• Encourage GNU parallel for multi-run experiments
• Use geometric mean as default aggregation statistic

Initial AgenticAlgorithmEngineering Release

Full Changelog: https://github.com/CHSZLab/AgenticAlgorithmEngineering/commits/v1.0