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.
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.
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.
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.
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.
Stop cascading failures in Go microservices.
A circuit breaker stops your Go service from hammering a failing dependency, preventing cascading failures that consume goroutines, sockets, and memory until the entire system collapses.
Process depth vs portability, not best tool.
Developers comparing Spec-Driven Development setups in 2026 are usually not asking which model is smartest. They are asking which workflow will keep an AI agent aligned without burying them in ceremony.
Five phases from intent to verified code.
Spec-Driven Development works when the specification is a workflow, not a document you file away after kickoff. The point is not to produce a large product requirements document.
Protocol security is who may act, not the model.
Prompt injection gets most of the security attention in LLM systems, and it deserves attention, but it is not the whole problem once agents start calling tools and delegating work to other agents.
Long-running A2A tasks outlive chat sessions.
Most AI agent demos still behave like chat completions with extra steps: you send a prompt, wait a few seconds, and get an answer back in one response.
40% of multi-agent pilots fail. Here's how to pick the right orchestration pattern - and avoid the ones that break.
Single-agent AI systems peaked in 2025 — you gave one LLM a prompt, some tools, and a goal, and it did reasonably well on bounded tasks.
Write the event with the data. Never split them.
Two writes that should succeed together will eventually fail separately.
Your order service saves the order to the database, then publishes an order.created event to a message broker.
Go context is control flow, not storage.
Go’s context.Context is simple enough to use badly — and that is the problem.
