Local Hermes memory with controlled writes.
Mnemosyne is a local-first memory provider for Hermes Agent, storing working memory, structured facts, temporal data, and episodic history in local SQLite — no hosted service, no mandatory network calls, and unusually granular write control.
When remembered conclusions become new evidence.
Persistent memory turns an agent from a re-explained tool into one that carries context forward — but it opens a failure mode stateless chat avoids: an interpretation can become memory, retrieved as fact, and justify a stronger version of itself.
No reject state. Here's the workaround.
An agent that proposed “move persistence into a shared library” six months ago will happily propose it again unless something durable says it was already rejected – and OpenSpec has no built-in state for that today.
Specs as deltas, not a 40-page PRD.
OpenSpec is a free, open-source CLI from Fission AI that gets you and your coding agent to agree on a change in plain Markdown before any code gets written, without the phase-gated ceremony of heavier spec-driven frameworks.
A safe cutover beyond the one-line import
Migrating an AI assistant is not the same as copying an application config. The hard part is preserving identity, memory, tool behavior, scheduled work, and messaging access without two gateways acting as the same bot.
When llama-server beats Ollama
Ollama and llama.cpp are often compared as if they were rival inference engines. The real choice is between a managed model service and a toolkit you operate directly.
Choose the right AMD backend per engine
ROCm and Vulkan both accelerate AMD GPUs for local LLM hosting, but they are not interchangeable. The right choice depends on the engine, GPU, and workload.
Why 128K context dies on 16 GB
A model can advertise a 128K context window and still fail at 40K tokens on a 16 GB GPU. The architecture ceiling never promised that weights, KV cache, compute buffers, and the desktop compositor would fit on your card at the same time.
What comes after LLMs? The post-transformer era.
AI hype follows a rhythm: roughly every three years, the architecture everyone is betting on gets replaced by something newer. The next shift is already forming in research labs.
OpenCode from the command line, in practice
OpenCode’s command-line interface is built for scripting, CI pipelines, and unattended agent runs. This article is a practical guide to using it in daily work.
Enforced SDD skills, installed in one command.
Superpowers packages a full spec-driven methodology into installable Claude Skills, enforcing brainstorming, planning, subagent-driven implementation, and strict TDD instead of leaving that structure up to you.
A small coding agent that expects you to shape it.
Pi Coding Agent is a minimal, open-source terminal coding harness that ships with four default tools and leaves most of the behaviour to extensions, skills and your own workflow.
Why your AI stack gets stickier every month.
Every API call feels like a simple transaction - until enough of them accumulate that your fine-tuning data, evaluation harnesses, and tool schemas are all shaped around one vendor, and switching stops being a routing change.
Delegate the noisy work, keep your context clean.
Most Claude Code sessions get slow and cluttered for the same reason: every exploratory grep, every log dump, and every “let me check one more file” stays in the main conversation forever.
When to move from Ollama to vLLM
Ollama is one of the easiest ways to run a local language model, but convenience can conceal the moment when a local experiment becomes a shared inference service that needs better scheduling and observability.
Stop AI agents drifting from specs, tests, and code.
AI coding agents ship features fast, but specs, tests, and code quietly drift apart. This guide covers a traceability model, spec-to-test and spec-to-code mapping, and the CI checks that catch drift before a merge.
