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llm
478 postsClaude Code vs OpenCode: Is That 33k-Token Preamble Worth It?
A teardown of Claude Code vs OpenCode shows why token count alone misleads on cost — caching behavior actually decides the real bill.
Designing a Coding Agent Loop: Goals, Verification, Stopping
How to design a coding agent loop: goal-check separation, a verification ladder, isolated attempts, and explicit stopping states.
nebius-actions: Fine-Tune and Deploy LLMs via GitHub Actions on Nebius
nebius-actions is a GitHub Actions toolkit for fine-tuning and deploying LLMs end-to-end on Nebius GPU infrastructure using Axolotl and vLLM.
CommitBrief — AI code reviews, right in your terminal
A provider-agnostic, local-first CLI that reviews your staged changes, a historic range, or a whole GitHub pull request. Zero telemetry, no server. Free and open source.
commitbrief.comCodeGraph Turns Repos into Queryable Graphs to Predict Breakage
CodeGraph converts GitHub repos into a Neo4j knowledge graph, using GraphRAG and a blast-radius score to predict code change impact.
PromptLedger v0.7 adds CI regression gates for prompt evaluation
PromptLedger v0.7 adds evaluation runs, metric comparisons, and policy-based regression gates for CI-safe prompt releases.
Five ways your LLM cost tracking is lying to you
Five silent failure modes in LLM cost metering — streaming, prompt caching, serverless flush, cancelled streams, and stale pricing tables.
Small Models by Choice: Running an Autonomous Agent on a 16GB M1 Mac
Why one engineer deliberately runs an autonomous agent on a 16GB M1 Mac with small models instead of scaling up to cloud LLMs — a design case study.
Token Economics: Why Your LLM Bill Outgrows the Pricing Page
Why LLM API bills exceed pricing-page estimates: workload ratios, tokenizer variance, caching, batch discounts, and retry overhead explained for engineers.
Autonomous agents' two big fears: runaway loops and exposed APIs
rysh's loop engineering and Forge features address the runaway-loop and API-exposure risks that come with building autonomous agents.
A deterministic memory layer for local LLMs at near-zero cost
An open-source deterministic memory layer bolts onto frozen LLMs, enabling zero-forgetting recall beyond context at near-zero marginal cost.