Deep dives into LLM context optimization, graph-based code retrieval, and agentic workflows.
A research paper reveals agentic coding tasks consume 1,000x more tokens than standard code reasoning. We break down why — and how Synapse MCP's precision retrieval, AST outliner, and SmartCrusher tackle each root cause.
Read Article →An architectural deep dive into why Synapse MCP's local AST graph and zero-latency file events beat cloud-based RAG and Merkle trees used by Cursor and Windsurf.
Read Article →An empirical 'Show, Don't Tell' benchmark comparing traditional shell grep loops against Synapse MCP's local in-memory AST graph engine. 2ms latency vs 12s, 56.4% token savings, 85% fewer tool calls.
Read Article →Full analysis across Cursor, Windsurf, Devin, Warp Terminal, Claude Pro, and Synapse. Why $20/mo is the universal price anchor and how Synapse pays for itself.
Read Article →Real data from our R&D: How replacing blind grep/read loops with AST-backed caller/callee graphs saves 30-60% of context tokens, eliminates false confidence, and solves multi-app refactoring.
Read Article →Why standard AI agents waste 70% of session time re-reading files, and how local AST caller graphs eliminate discovery loops for zero-breakage refactoring.
Read Article →How Synapse MCP uses ETS, GenServer-per-repo supervision, pure Elixir BM25F embeddings, and in-memory Shadow Graph safe writes to give AI agents microsecond codebase context on the BEAM.
Read Article →A side-by-side comparison of the leading codebase context engines for AI agents — cloud RAG, vector search, and local AST graphs.
Read Article →Vector RAG chops functions in half and misses alias imports. AST graphs preserve exact structure for reliable agent refactors.
Read Article →A real incident transcript showing how agents claim tool success without evidence — and the grounding policies that stop it.
Read Article →We installed shell tools, Synapse MCP, and codebase-memory-mcp on the same machine, indexed the same codebase, and ran five identical queries. We lost on per-query token count. We're publishing the results anyway — here's why total session cost is what matters.
Read Article →We installed both tools on the same machine, indexed the same codebases, and ran the same queries — including the Linux kernel. Synapse is faster, leaner, and safer across every dimension. Full results, raw timing, token counts.
Read Article →Andrej Karpathy's LLM Wiki gist is brilliant for prose —but code isn't prose. Applied to a codebase,the wiki pattern collides with a live, structured artifact. Here's where a persistent code graph — not a folder of summaries — is the right tool,and the honest reasoning behind every trade-off.
Read Article →