SatStack launches free local AI coding agent with Ollama + qwen2.5 and SQLite memory

SatStack’s two‑part guide shows developers how to replace costly cloud‑based code‑generation APIs with a self‑hosted stack that runs on a modest $600 desktop. By pairing Ollama—a lightweight runtime that wraps local LLMs behind an OpenAI‑compatible REST endpoint—with Alibaba’s qwen2.5 14B model, the setup delivers “excellent” code‑quality across Python, Bash, JavaScript, Go and Rust while consuming roughly 16 GB of RAM, according to the company’s own documentation. The entire pipeline fits on a single Ubuntu machine, and once the model is pulled (about 9 GB) Ollama handles GPU or CPU routing automatically, exposing the service on localhost:11434 with just two commands — install and pull — as SatStack outlines in its “Run a Local AI Coding Agent for Free” post.

Beyond raw inference, SatStack tackles the perennial “goldfish‑bowl” problem of LLMs forgetting prior interactions. Their second tutorial, “Give Your AI Agent Long‑Term Memory with SQLite and Ollama,” adds a persistent memory layer that stores raw conversation logs and compressed summaries in a local SQLite database. The Python script creates two tables—one for full session transcripts and another for summary vectors—then injects relevant history into each new request before the model generates a response. Because SQLite is built into Python, the solution requires no extra dependencies beyond the Ollama service itself, keeping the footprint lightweight and fully offline.

The practical impact is significant for teams that run code‑generation at scale. As SatStack notes, per‑token fees on services like OpenAI’s Codex or Claude can balloon quickly, especially for refactoring or documentation pipelines that process thousands of tokens daily. By offloading those workloads to a 14‑parameter model that “handles 80 % of daily coding tasks,” developers can eliminate recurring cloud bills altogether. The approach also sidesteps data‑privacy concerns, since all prompts and generated code stay on the developer’s hardware—a point highlighted in ZDNet’s coverage, which calls the stack a potential free alternative to Claude Code and Codex.

Early adopters are already testing the stack in real‑world environments. ZDNet’s David Gewirtz reported that Block’s Goose agent, when paired with Ollama and the newer Qwen 3‑coder model, performed comparably to Claude Code in his hands‑on trial, reinforcing the claim that locally hosted models can match commercial cloud offerings for many coding scenarios. Meanwhile, TechCrunch’s coverage of Reload’s shared‑memory architecture underscores a broader industry trend: developers are increasingly looking to embed persistent context into AI agents, a need that SatStack’s SQLite layer directly addresses.

In short, SatStack’s open‑source recipe offers a cost‑free, privacy‑preserving alternative for everyday coding assistance. With a $600 workstation, 16 GB of RAM, and a few minutes of setup, developers can run a 14 B‑parameter LLM locally, achieve “excellent” code quality, and retain conversational memory across sessions—all without touching a cloud provider’s API. The stack’s simplicity and zero‑cost model could reshape how software teams think about AI‑augmented development, especially as the price pressure from token‑based services continues to rise.